The answer depends significantly on what kind of business you are. According to BrightLocal’s 2026 Local Consumer Review Survey, 45% of consumers are now using generative AI platforms such as ChatGPT or Google Gemini for local recommendations – up from just 6% in 2025. That one data point speaks volumes about how fast things are moving.

A local service provider whose customers are asking Perplexity for recommendations right now has a different and more urgent problem than a B2B SaaS company with a long enterprise sales cycle. Most businesses are adapting their strategies mid-flight, tailoring their strategies to their specific industries and measurement goals.

What’s becoming clearer is where the real leverage sits – third-party coverage and off-site mentions are driving AI citation rates far more than owned content. Measurement tools built specifically for AI visibility are starting to emerge. And the businesses seeing the strongest results are those treating SEO and GEO as connected disciplines rather than separate ones.

We put the question to the specialists. Here’s what they said.

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Our Experts

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• Myles Anderson, CEO, BrightLocal
• Marcus Hearn, SEO Specialist, Another Concept
• Mindy Faieta, Head of Customer Success, Stateshift
• Monica Tomasso, Chief AI Visibility Expert, Monic AI Systems
• Jeremy Moser, CEO, uSERP
• Cathy Farmer, Head of GEO, Third City
• Ben Gibson, UK CEO, Cosmo5
• Jo Wilmot, PR Director, The Think Tank
• Kat Gibbons, Strategic Director, Bamboo
• Fiorela Imerai, Account Director, Wildcat Digital
• Hannah Spelman, Head of Organic Marketing, I-COM
• Andrew McLernon, CEO and Co-founder, Interlink
• Chris Pitt, CEO, GAIN Performance

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Myles Anderson, CEO, BrightLocal

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“Our 2026 Local Consumer Review Survey found that 45% – up from just 6% in 2025 – of consumers are now using generative AI platforms such as ChatGPT or Google Gemini for local recommendations.

“In the era of AI-driven search and zero-click results, local success is no longer just about ranking – it’s about becoming the most trusted and verified option in your market. Search engines now look for a consistent pattern of activity rather than one-off changes.

“The traditional SEO playbook is ready for an update, and businesses need to start taking a tailored approach to each platform. Google Business Profiles, websites and third-party directories are the sources of truth for AI – keep your information updated and accurate so LLMs and search engines can verify your legitimacy. On TikTok and YouTube, focus on content that answers questions: how-to and explainer videos for service businesses drive strong visibility in AI search. And don’t overlook Maps – our research found that one in five people conduct local searches directly in maps, which means your Google Business Profile deserves as much care as your website.

“Local SEO is only as good as the leads it generates. Focus on what actually matters by measuring the actions that drive revenue, not vanity metrics. The growth of generative AI search means brands must lean into Google’s E-E-A-T framework more than ever. Search success in 2026 involves maintaining a consistent presence across a wide variety of touchpoints and making sure your business is positioned as trustworthy and helpful to consumers.”

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Marcus Hearn, SEO Specialist, Another Concept

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“Your approach to GEO should really depend on the vertical in which you’re operating.

“F�ǰ� publishers, we’ve seen very little benefit from optimising to increase citations, and in terms of traffic it has effectively become a form of brand PR. Someone else is ultimately going to get cited if you’re not there, so it should still be on your radar but the time would be better spent optimising for Google Discover, which in our experience provides up to five times as many sessions versus organic search.

“F�ǰ� ecommerce and lead gen it’s slightly different, as the user is, for the moment, still required to visit your website to achieve their goal. For ecommerce, we’ve found implementing product-level reviews to be the most influential factor in increasing citations and recommendations. Product-level FAQs or bullet point summaries of key product information have also delivered positive results.

“One of our best performing clients for AI referral sessions, of which it sees around a 40% conversion rate, has none of the technical optimisations implemented. They simply have a strong SEO strategy, really great reviews, get natural recommendations on UGC forums like Reddit, and are active in digital PR. So therein probably lies your answer.”

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Mindy Faieta, Head of Customer Success, Stateshift

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“The old SEO playbook assumed a click was the prize, but that’s changing fast. When AI Overviews, ChatGPT and others answer the question right on the page, the click never happens, so chasing rankings for traffic that no longer shows up is wasted effort most of the time.

“What still works is being useful and being citable. AI tools pull from sources they can parse and trust, so the most important thing now is making your content easy for models to extract and quote. We bind the brand name and ICP language into the first 100 to 150 words of every post, structure it so an LLM can lift a clean answer, and lead with real data and direct quotes instead of surface-level summaries. But just being cited isn’t enough. You want to be mentioned by brand name. There’s not much benefit if AI uses your information without naming you.

“The biggest mistake I see founders make is dragging old SEO habits into this, especially the instinct to chase prompt volume and keyword breadth. GEO rewards depth, not coverage. The opportunity is that most businesses haven’t caught up yet. I recommend tracking your AI visibility with a tool like Peec AI, Otterly or Profound. And it’s more than the content on your own site. It’s the full digital PR picture: mentions on Reddit, LinkedIn and third-party outlets. Join the conversation where it’s already happening.”

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Monica Tomasso, Chief AI Visibility Expert, Monic AI Systems

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“One of the biggest shifts I’m seeing is that AI search is no longer a single-query experience. Users ask a question, refine it, compare options and continue the conversation in the same session. That means brands are no longer competing just to ‘rank’ once. They’re competing to stay in the conversation.

“What I’m seeing in practice is that the businesses performing best in AI search usually have enough depth and consistency for AI systems to keep returning to them as the conversation evolves. I often describe this as conversational persistence or conversation survivability.

“Companies optimise only for the first question. The real opportunity is building enough connected expertise, trust signals and conversational content for AI systems to confidently continue recommending the brand throughout the buyer journey.”

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Jeremy Moser, CEO, uSERP

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“Every GEO and AEO solution on the market tells you to publish significantly more content to ‘show up in AI engines.’ Structure that content for LLMs. Spin off 100 programmatic posts per month. Chunk your content. Listicles. Comparison posts. While publishing great content in multiple formats on core keywords and prompts is a good foundation, that’s one of the smallest pieces of the puzzle. It’s table stakes now. Everyone is doing it.

“As a business, you don’t actually want more citations in AI. You want more mentions for decision-making prompts. You want your brand to be recommended when someone asks ChatGPT ‘what are the best solutions for XYZ’ more than you want ChatGPT to cite your article as a source for an informational, broad prompt.

“And the best way to make that happen? Off-page SEO, link building, brand building and PR. AI engines only pull from your site 8% of the time when recommending you. Meaning 92% of the time an LLM gives a brand recommendation, it’s pulling from other websites that mention and discuss the topic.”

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Cathy Farmer, Head of GEO, Third City

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“The old SEO playbook assumed one thing: the user would click. That assumption is now broken. AI platforms like ChatGPT Search, Perplexity and Google AI Overviews are synthesising answers directly from source material, and the visit never happens. Ranking first means nothing if the model answers the question before the user reaches your site.

“What still works is credibility at scale. LLMs draw on patterns across everything that’s been published about a brand, not just your own website. Third-party coverage in high-authority publications, consistent messaging across owned and earned channels, a clear and distinctive point of view that actually exists in the world – these things matter more now than ever.

“What’s broken is the feedback loop. Traditional SEO gave you rankings, click data and clear signals. GEO doesn’t. You’re not optimising a page, you’re shaping how a model understands your brand across hundreds of sources. To get any meaningful read on that, you need to run queries at volume and track patterns. That’s exactly why we built our own AI visibility tool, GEOView, which runs LLM searches at scale so clients can see how, and how consistently, they’re being cited. It starts with understanding where you actually stand.”

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Ben Gibson, UK CEO, Cosmo5

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“The core of the problem is that ranking and reaching an audience are no longer the same thing. Businesses are holding their positions in search results and still watching traffic fall, because the question is being answered before anyone clicks through. That breaks the assumption the old SEO playbook was built on.

“What still works is authority. AI systems weight trusted media coverage, thought leadership, structured content that addresses real questions and signals from peer communities and review platforms. The brands surfacing consistently in AI-generated responses tend to have a coherent presence across the sources these models draw on, not just a well-optimised website.

“The opportunity lies in treating SEO and GEO as connected rather than parallel. Content built around genuine user intent, distributed across credible sources and reinforced by consistent brand signals serves both. Visibility is moving upstream, and those that understand where in that journey they are being defined, and by what, are the ones better positioned for where search is heading.”

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Jo Wilmot, PR Director, The Think Tank

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“One big change we’re seeing: a few months back, we were telling prospects about GEO and AI search and the reaction was somewhere between a blank stare and ‘I’ll worry about this when it’s time to worry about it.’ Over the last six weeks, that’s changed. Every company that approaches us for PR services is asking us if we can help get them discovered in GEO. With about 90% of AI search citations coming from earned media, according to a recent Muck Rack report, the answer is definitely yes.

“AI pays attention to media coverage in a way that makes it a direct input into whether AI surfaces you. Since AI cites it when delivering instant answers, humans have to pay attention too.

“F�ǰ� companies that have already invested in SEO for years, your money wasn’t wasted. AI search is still informed by the fundamentals of good SEO. But the added layer is getting coverage in the media, whether that’s in big outlets or niche, relevant trade publications. Different LLMs use different media sets – research shows that Claude cites niche titles more than ChatGPT. So depending on your audiences and which LLMs they use, you might need to select different campaign approaches.”

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Kat Gibbons, Strategic Director, Bamboo

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“AI hasn’t killed SEO, but it has fundamentally changed what success looks like. For years, the goal was winning clicks from search results. Now, the challenge is winning visibility and trust in a world where AI tools answer questions without sending users to a website.

“What’s broken? The old playbook of producing high volumes of keyword-led content designed to rank. If your strategy relies on being the tenth version of an answer, AI will summarise it before a user ever sees your site.

“What still works is creating genuinely useful content rooted in expertise, experience and originality. AI models need sources, opinions and evidence to reference. Brands that publish unique insights, expert commentary and real-world perspectives are more likely to be surfaced than those repackaging information already available elsewhere.

“The opportunity is to think beyond rankings and focus on discoverability. People now encounter content through AI-generated answers, LinkedIn posts, industry publications and peer recommendations as much as traditional search. SEO is no longer about being searchable; it’s about being the source that AI, journalists and industry peers choose to reference. That’s a much bigger opportunity than a click.”

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Fiorela Imerai, Account Director, Wildcat Digital

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“AI search is not killing SEO, but it is making lazy SEO much harder to hide. If a strategy is built around generic blog content, broad keywords and traffic for traffic’s sake, it’s going to struggle, because AI Overviews, ChatGPT Search and Perplexity can answer a lot of those basic queries without sending anyone to the site.

“The brands that will win in 2026 are the ones that become harder to summarise without citing. That means sharper product and service pages, genuinely useful expert content, clear answers to real customer questions, strong technical foundations, structured data and authority signals beyond the website itself – reviews, digital PR, industry mentions and credible third-party coverage.

“What is broken is the idea that SEO is only about rankings and sessions. Those still matter, but they are no longer the full picture. The question for businesses is no longer just ‘are we ranking?’ It is ‘are we giving search engines and AI tools enough confidence to choose us as the answer?’”

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Hannah Spelman, Head of Organic Marketing, I-COM

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“A winning SEO strategy in 2026 must prioritise brand visibility across all search spaces, not just website traffic. While direct traffic remains important, the rise of AI Overviews and AI-powered search tools means users increasingly find answers without visiting your site. A modern SEO strategy needs to account for this reality and actively work to get your brand into these new spaces.

“This shifts how success should be measured. You should also track brand mentions and impressions in AI Overviews and LLMs like ChatGPT, as well as your market share against competitors, looking at how often your site appears versus your main competitors. That said, website traffic hasn’t disappeared. Commercial and transactional queries still drive conversions, making on-site optimisation critical. Pages that do generate traffic must be well-optimised, fulfil search intent and convert users effectively.

“The solution isn’t to abandon SEO. Google’s own AI optimisation guide confirms that solid SEO fundamentals are essential for appearing in these new spaces. Instead, adopt a consistent, integrated strategy that secures visibility across traditional search results, AI Overviews and LLM responses. The competitive advantage lies in appearing everywhere your audience is looking.”

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Andrew McLernon, CEO and Co-founder, Interlink

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“F�ǰ� a winning SEO strategy in 2026, ranking is no longer enough. When AI Overviews appear in more than half of all search results and 70% of B2B searches include an AI-generated answer, appearing at the top of the page no longer guarantees a click, let alone a conversation.

“What’s broken is the assumption that search behaviour signals buying intent in a way that’s actionable. Click-through rates drop by nearly 50% when AI summaries are present, which means a significant volume of queries are now resolved directly within the results page. The buyer gets their answer and moves on without ever visiting a website.

“F�ǰ� B2B businesses specifically, this accelerates a problem that already existed. Buyers form opinions, build shortlists and develop category preferences before their behaviour becomes visible to vendors. AI tools are making that hidden phase longer and harder to influence. By the time a prospect’s activity registers in a CRM or intent platform, the evaluation process is often already well underway.

“What still works is substance. AI systems surface content that is authoritative, specific and genuinely useful, so the quality bar has gone up, not down. The real opportunity is for businesses willing to build presence beyond their own websites. Third-party credibility, through contributions to industry publications, consistent association with the right topics and presence in trusted communities, shapes how AI tools represent a brand and whether they recommend it.”

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Chris Pitt, CEO, GAIN Performance

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“AI Overviews, chatbots and generative search are changing how people discover and evaluate brands, but they haven’t changed what actually wins. The journey is messier, more conversational and far harder to track: buyers bounce between AI summaries, social feeds, forums, reviews, traditional search and messaging long before they ever hit your site. Yet underneath that complexity the fundamentals of SEO remain. Experience, relevance, authority, technical performance and offsite signals – it’s all still there.

“The brands that come out on top are the ones that show up consistently, credibly and memorably across all commercially relevant touchpoints, not just in one channel’s dashboard. What has shifted is the centre of gravity: individual platform metrics are less useful in isolation, while commercially relevant, targeted brand visibility has become the key performance outcome. Off-page tactics like branded mentions, digital PR and link acquisition are now core brand infrastructure, because they fuel both search and AI visibility. As AI handles more of the mechanical optimisation, the real human advantage moves upstream into strategy and creativity.”

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For any questions, comments or features, .

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The package has four components: Chips Act 2.0, which refreshes the 2023 semiconductor legislation and creates an excellence label for European chip manufacturing regions; the Cloud and AI Development Act (CADA), which aims to triple EU data centre capacity within five to seven years and establishes a sovereignty framework for cloud and AI in public sector workloads; a new Open Source Strategy scaling up European alternatives in AI and cybersecurity; and a Strategic Roadmap for Digitalisation and AI in Energy, which promotes AI “trained on European data and developed by European companies.”

For UK founders selling into European markets, timing is key. The package is moving through the Commission while the UK-EU relationship is still settling post-Brexit, and the regulatory distance between the two is growing rather than shrinking.

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What The Package Actually Does

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At the heart of the initiative is CADA. It highlights the EU’s struggle to compete in the cloud, holding less than 13% of the global market while US giants – AWS, Microsoft Azure and Google Cloud – secure the vast majority. CADA sets out to address that directly, with a binding target of 50% sovereign cloud adoption across EU public sector workloads by 2030. It also creates a formal sovereignty assessment framework, meaning EU governments will need to evaluate cloud and AI providers against defined sovereignty criteria before procurement.

Chips Act 2.0 builds on the original legislation’s goal of reaching 20% of global semiconductor production by 2030, adding an excellence label for European chip regions and measures to bring manufacturing physically closer to major customers including data centres and cloud providers. The Open Source Strategy is the least prescriptive of the four components but signals EU intent to invest in home-grown AI and cybersecurity tooling as a deliberate alternative to US-built incumbents.

The full package requires endorsement from all 27 member states and European Parliament approval before any of it becomes binding. Implementation timelines remain unclear, and the package will face lobbying from US technology companies with significant European operations. However, the trajectory is clear: the EU is building a framework that systematically preferences European providers for public sector technology contracts.

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The Brexit Complication

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Since Brexit took the UK out of the Single Market, British companies don’t automatically count as ‘European’ under the EU’s sovereignty rules – that has two practical consequences. First, UK founders using US cloud infrastructure – AWS, Azure, GCP – for EU customers, particularly public sector ones, may face compliance hurdles as the sovereignty requirements come into force. Second, as EU procurement actively preferences sovereign-certified European providers, UK businesses competing for those contracts will face a disadvantage they didn’t have before.

UK founders selling into Europe already carry a dual regulatory burden: EU AI Act compliance on one side, the UK’s own pro-innovation framework on the other. The Tech Sovereignty Package adds a third layer – sovereignty certification for cloud and AI – that UK businesses will need to manage from outside the bloc. The UK government has indicated it’s engaging with the European Commission to assess CADA’s impact ahead of the upcoming UK-EU Summit, but no formal position has been announced.

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Is The UK Aligned, Diverging Or At Risk Of Being Left Behind

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The UK and EU are taking distinctly different approaches to AI and digital infrastructure, and the divide is growing.

The UK’s strategy is pro-innovation and market-led: light-touch regulation, sector-based oversight and an ambition to become a global AI leader through private investment rather than state-driven industrial policy. The EU approach is the opposite – comprehensive risk-based regulation combined with a state-backed infrastructure buildout designed to create European alternatives to US technology.

According to analysis by Forrester, UK firms are expected to accelerate past EU counterparts in production AI deployment, partly because lower regulation and no language gap make adoption faster. France is already replacing Zoom and Teams with domestically developed alternatives. If EU member states move toward sovereign cloud and open-source AI at scale, UK businesses selling those markets will need European partnerships or European infrastructure to remain competitive for public sector contracts.

For UK startups and scaleups with European ambitions, the practical checklist is short: audit which cloud infrastructure you’re using for EU customers, monitor EU procurement rules as CADA moves through the legislative process, and consider whether a partnership with an EU-based provider makes sense ahead of the sovereignty mandates coming into force.
The package still has a long road through Brussels before it becomes binding – but the direction has been set and the time to prepare is before the requirements land.

The post What The EU’s New Tech Sovereignty Plan Means For UK Businesses appeared first on 91̽��.

now automate bidding, audience targeting and creative testing across entire platform networks from a single campaign. AI determines who sees an ad, when and where, without relying on the third-party cookie infrastructure that underpinned targeting for years. According to analysis of 2026 ad platform developments, smart bidding systems are adjusting bids in real time based on behavioural signals at a speed and scale no human team can match. Meta has indicated it’s moving toward full campaign automation and ad creation by the end of 2026.

The debate is over; AI has undeniably transformed paid media. The tough part – and what founders and marketing leads are really asking – is what that means for strategy, creative, measurement and where budget should go.

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What’s Actually Changed

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The transformation runs deeper than new campaign types. Performance Max runs across Search, Display, YouTube, Gmail, Discover and Maps from a single campaign structure. Advantage+ handles audience discovery and creative delivery across Facebook and Instagram with minimal manual input. Both systems are built on the same principle: feed the algorithm a conversion goal and strong creative inputs, and the machine handles the rest.

There’s a real upside to this shift – what used to take weeks of creative testing now only takes days. Audience segmentation that required manual hypothesis and iteration now happens automatically. Budget allocation responds to real-time signals rather than weekly human review. For businesses with clear conversion data and strong first-party data, these systems can outperform what a human team would achieve manually.

The complication is what happens when those inputs are weak, and what happens when the platform’s optimisation goals diverge from the advertiser’s actual commercial objectives. AI optimises ruthlessly for whatever goal it’s given. If the goal is set wrong, or if the data feeding the system is poor quality, the machine will optimise efficiently toward the wrong outcome. The current debate boils down to one question: are platforms optimised for their own efficiency, or for ?

We asked the experts.

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Our Experts

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• Chester Scott, Chief Strategy Officer, Lunio
• San Nakra-Shah, Co-Founder and Managing Partner, ChilliMint Europe
• Thomas Harpointner, CEO, AIS Media
• André Picart, Managing Partner and Co-Founder, Tribera
• Matt Benton, CEO, Real Time Marketing
• Kamel Ben Yacoub, Founder and CEO, Getuplead
• Max von Weber, CEO, adnomaly
• Charlotte Sheridan, Director, The Small Biz Expert
• Sam Dadd, Senior Paid Media Executive, Arke Agency
• Ashley Fletcher, CMO and VP of People, Adthena
• Neil Baker, Head of Media Europe, Tug
• Georgia Doyle, Senior Paid Media Manager, TAL Agency

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Chester Scott, Chief Strategy Officer, Lunio

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“The genuine transformation in paid media is the sheer scale and speed at which AI-driven campaigns, like Google’s Performance Max and Meta’s Advantage+, can test and iterate. When fed accurate data, these smart bidding algorithms are incredibly powerful.

“However, the idea that these platforms are a ‘set-and-forget’ magic bullet is massively overhyped. The biggest blind spot founders and marketers have right now is trusting the ad networks to grade their own homework. AI models are ruthless optimisers; they do not understand the difference between a high-intent human and a sophisticated bot. If your campaigns are polluted with invalid traffic or zero-value engagements, the AI will learn from those fake clicks and optimise your budget to find more of them. This drives up your true Customer Acquisition Cost while giving the illusion of efficiency.

“Right now, operators must stop treating ad fraud as a cybersecurity problem and start treating it as a foundational data hygiene issue. You cannot control the black box of AI bidding, but you can control the data going into it. Leadership should invest in third-party waste intelligence to independently audit and filter their traffic. By blocking invalid engagements before they hit the algorithm, you force the AI to learn exclusively from genuine human interactions, ensuring your budget drives actual business outcomes.”

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San Nakra-Shah, Co-Founder and Managing Partner, ChilliMint Europe

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“Yes, AI is transforming media buying. Targeting, bidding, optimisation and audience selection are increasingly handled by Google, and other platforms, usually more effectively than humans can manage themselves. For the last twenty years, marketers have built expertise around understanding channels, audiences and optimisation techniques. The best teams won because they understood the mechanics of digital advertising better than their competitors.

“AI is rapidly eroding that advantage because every advertiser has ready access to the same optimisation engines and algorithms. These capabilities are becoming less like key differentiators and more like common utilities. AI is commoditising media buying and fundamentally changing where competitive advantage sits in marketing.

“But here’s the irony. As marketing becomes more automated, the most valuable skills are becoming more human. Creativity, judgement, storytelling, brand building and customer understanding are increasing in importance, because they’re harder to automate.

“The value is rapidly shifting from targeting towards ideas, content and creative development. The smartest brands have already recognised this. They are taking the efficiencies gained from media and investing more in content, creative production and customer insight. Because when every competitor has access to the same AI, the real advantage comes from knowing something about your customers that the algorithm doesn’t. Media buying is becoming a utility and customer understanding is becoming the differentiator. And that’s the one thing AI still can’t commoditise.”

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Thomas Harpointner, CEO, AIS Media

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“AI is absolutely making paid media better, but not because brands can simply ‘set it and forget it.’

“The biggest gains are coming from creative speed. AI helps marketers bring more ideas to life, produce more ad variations faster, lower the cost of creative testing and identify winning messages sooner. That matters because increasing spend behind weak creative does not improve performance. It just wastes money faster.

“Platforms like Google Performance Max and Meta Advantage+ can work extremely well, but only when marketers give them the right inputs. That means clean conversion tracking, clear revenue goals, strong first-party data and enough creative direction for the system to learn from. Without those inputs, automation simply scales whatever is already broken.

“What is overhyped is the idea that AI replaces paid media expertise. It does not. It moves the expertise upstream. Marketers now need a sharper understanding of the brand’s objectives, voice, style, audience and unique selling points. AI does not automatically understand brand personality or business strategy. Skilled marketers have to train, guide, evaluate and refine the output.

“F�ǰ� founders in 2026, the smart move is not to blindly increase paid media budgets because the platforms are ‘AI-powered.’ The smart move is to fund disciplined testing. Use AI to develop creative faster, test more angles, find what is working and what is not, then put more budget behind proven winners. AI rewards disciplined advertisers. It punishes lazy ones.”

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André Picart, Managing Partner and Co-Founder, Tribera

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“AI has genuinely changed the mechanics of paid media for the better. Major platforms are now incredibly good at optimising budgets, finding audiences and testing creative variations at a speed no human team could realistically match. In that sense, the technology absolutely works.

“Where I think people get carried away is assuming that faster automatically means better. AI can generate and optimise ads quickly, but it doesn’t necessarily make them memorable. In a feed full of content, blending in is a problem, and a lot of risks looking and sounding exactly like everyone else’s.

“Another challenge is transparency. As more of the process becomes automated, it can be harder to understand where results are actually coming from. Marketers are often asked to trust the platform’s recommendations, without always seeing the full picture behind the decisions being made.

“With that in mind, the businesses getting the strongest results are the ones using AI as an execution tool, rather than a replacement for strategy. They’re letting the platforms handle the heavy lifting, while staying closely involved in measurement, creative direction and decision-making. They know what success looks like before they launch a campaign, and they’re willing to challenge what the dashboard is telling them when something doesn’t feel right.

“In 2026, the competitive advantage won’t come from having access to AI – everyone will have that. The advantage will come from brand strategy, distinctive creative and the quality of the thinking behind the campaigns.”

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Matt Benton, CEO, Real Time Marketing

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“AI has simultaneously enhanced and obfuscated paid advertising. Platforms like Google Performance Max and Meta Advantage+ have delivered on their promise of efficiency for conversion-driven campaigns. Smart bidding gets to real business outcomes faster than any human, and automated creative testing workflows have shortened timelines from weeks to days.

“Where they fell short was predictably in control. The platforms take more and more control of the targeting and placement decisions that used to be made by campaign managers. Budgets that don’t have clean conversion tracking get thrown at ineffective placements that are difficult to diagnose. AI is only as good as the goal you set it. When your goal is not buying customers, it will efficiently optimise for something else.

“Measure before you spend is your best paid media strategy for 2026. Google Local Services Ads consistently deliver strong ROI for contractors because the intent is clear and a pay-per-lead model decreases variance. Stack Performance Max on top of your conversion-ready campaigns to scale your successes, not replace them. Ultimately, AI can’t help you if your follow-up is slow, and speed-to-lead is what determines whether your paid traffic converts.”

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Kamel Ben Yacoub, Founder and CEO, Getuplead

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“The challenge right now is separating AI noise from AI signal. In my first-hand experience managing B2B SaaS budgets, AI is transformative on the operational side but largely overhyped for core acquisition metrics.

“What’s actually working: significant productivity gains in AI-assisted workflows – reviewing search term reports, running structured account audits and generating ad copy drafts as a starting point. Ad creation is also the best use case. But optimisation for paid search is where it gets more complicated. Google rotates headlines and descriptions in different combinations but doesn’t tell you which specific combinations are actually performing. You get asset-level ratings, but no impression or conversion data per combination. So it’s difficult to assume your AI-generated headlines are better than your human-written ones.

“What’s overhyped: for clients working with hundreds of conversions per month, full automation in bidding or targeting doesn’t improve performance. We haven’t seen better performance with AI-native tools that promise to improve performance with AI-assisted management and optimisation. Human expertise remains essential.

“Founders must combine AI analysis with expert manual review. Prioritise fixing the conversion funnel: once ads are solid, the landing page is almost always where things break down. A faster iteration loop between ads, landing pages and sales data will drive commercial results far better than automated bidding alone.”

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Max von Weber, CEO, adnomaly

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“The conversation around AI in paid media tends to focus on the upside: better targeting, faster creative, smarter bidding. What we see daily, working across paid social, programmatic and paid search, is the other half of the story.

“The most underrated risk isn’t that AI doesn’t work; it’s that AI is changing settings, expanding audiences and swapping creative elements in the background, often without the operator noticing. We’ve seen approved ads suddenly play music the client never signed off on. We’ve seen ‘AI-optimised’ audience expansions reach segments the brand explicitly excluded. We’ve seen creative variants pushed live that nobody on the team can fully account for. The front-end has never been easier; the back-end has never been more closed off.

“That’s the part you have to be careful with. When the interface becomes simpler and the platforms tell you to ‘trust the system,’ it’s tempting to take that at face value when the rest of your day is already stressful enough. But the back-end tells a completely different story and you only notice when something has already gone live, gone wrong or gone over budget.”

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Charlotte Sheridan, Director, The Small Biz Expert

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“Firstly, what anyone running ads on platforms such as Meta or Google needs to bear in mind is that those platforms want to make money. They are less bothered if their advertisers do, so many automations are designed to either get more clicks or more views – but not necessarily more sales for your business.

“Nor do automations take into account specific audience requirements. If you are in a regulated industry, be very careful, as using things like Advantage+ or AI Max may mean that you’re allowing those platforms to write your ad copy for you, which means you may no longer be compliant with any regulations.

“However, if you run an, allowing the platforms to get creative or find audiences for you can work exceptionally well. Rather than using your own hypothesis, AI can look at huge data sets and decide where your budget is best placed, what type of creative is likely to convert and when.

“It’s also important to note how manipulative some of the language now is when pushing users towards automation. Meta ads will say ‘further limit your audience’ when you want to add specific targeting, while Google will tell you that you may be ‘missing out on clicks’ by not using broad match terms. Missing out on clicks is not an issue. Paying for irrelevant clicks is the issue for most advertisers, as they will burn through budget with nothing to show for it.”

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Sam Dadd, Senior Paid Media Executive, Arke Agency

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“From our perspective, AI is absolutely transforming paid media, but it is not a replacement for strong strategy, clear testing and human review.

“What is working well is the ability to scale faster. Tools like Performance Max and Meta Advantage+ can be really effective when they sit within a wider marketing mix, particularly where there is strong conversion data, clear audience signals and a full-funnel strategy behind them. Smart bidding, automated placements and AI-led creative testing all have their place, but only when the foundations are already there.

“What feels overhyped is the idea that AI can simply be switched on and left to perform. It is only as powerful as the person behind it. Without proper brand safety checks, creative review, first-party data and clear measurement, AI can very quickly optimise towards the wrong outcomes.

“Right now, founders and marketers should not jump on the bandwagon for the sake of it. They should understand their audiences, test standard ad formats, compare manual and automated bidding, and build a strong A/B testing framework first. Once those foundations are in place, AI can support scalability and efficiency. The main takeaway is simple: use AI, but do not hand over control.”

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Ashley Fletcher, CMO and VP of People, Adthena

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“AI is reshaping paid media in 2026, with the biggest shift happening inside AI-generated search environments. Ads now appear directly in Google’s AI Overviews and ChatGPT conversations, marking a fundamental change in how search is monetised. Adthena was the first to detect these placements, spotting early Google AIO ads across 25,000 SERPs at just 0.052% frequency – a small signal of a major structural shift. That volume has since grown, with competition in AI ad auctions rising 35% year on year.

“What’s working today is AI-native optimisation combined with real competitive visibility across both Google and ChatGPT. Performance Max, Advantage+ and now Google’s emerging AI Mode roadmap are powerful, but they’re black boxes – and this automation is often mistaken for strategy.

“What’s overhyped is the idea that AI will ‘do it all for you.’ If anything, AI has made paid media more complex. Founders should prioritise cross-channel visibility, especially across Google and ChatGPT, where behaviour and ad delivery are already diverging. Success depends on rapid creative and bidding iteration grounded in real market data rather than platform-reported metrics, which increasingly obscure what’s actually happening in the auction.”

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Neil Baker, Head of Media Europe, Tug

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“AI is nothing new to performance marketing – since 2016 we have been using automated bidding strategies. However, the space is still evolving. With search we have intent-based strategies which means first-party data integration is more important than ever. With paid social, algorithm changes such as Andromeda show that creative is now the new targeting, and creative variation is incredibly important.

“Whilst creative variation is now more important than ever, that doesn’t mean making lots of variations of the same ad. It means developing creative themes that touch on the different values of your customer and allowing the algorithm to find the people who would relate. Don’t develop AI creatives just for the sake of it – use them with purpose.

“Another watch-out is people’s over-reliance on LLMs for strategy. The recommendations can often be dated and misleading and still need an expert to validate. The real value from AI comes in speed – if you can accelerate creative development or streamline workflows – and in measurement: MMM, incrementality modelling and causal modelling are where some of the most useful developments are happening.”

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Georgia Doyle, Senior Paid Media Manager, TAL Agency

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“AI, like anything in digital marketing, can be very useful for taking care of repetitive tasks and freeing up time for real creativity, so long as it doesn’t seep into creative and ad copy. As consumers become more savvy to how AI looks and feels, it’s crucial that paid media specialists understand its limitations and don’t let it take over creative aspects that require humans throughout the full process.

“, audience expansion and bid management. Meta and Google can process far more data signals much quicker than any human could in real time, and features that improve efficiency and performance should absolutely be embraced. But the industry has become far too quick to assume that every AI feature automatically adds value.

“Paid media specialists should be very selective about what’s enabled and disabled across ad platforms. No one understands a brand as much as a human marketer, and marketing requires much context and nuance to ensure it’s landing well with an audience. One of the biggest issues I’m seeing is that AI-generated advertising is becoming increasingly recognisable. Consumers and marketers are becoming much more savvy to it, and AI-generated content is seen as inauthentic and can immediately erode trust.

“Many ads are starting to look and sound the same, with similar visuals, messaging and creative styles, which is off-putting to audiences and risks reputational damage. Differentiation is crucial, as consumers connect with brands when they feel authentic as opposed to sounding like every other advertiser using the same AI prompts. The strongest paid media strategies in 2026 are using AI as a tool for optimisation and efficiency, whilst keeping humans firmly in control of strategy, creativity and brand voice.”

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For any questions, comments or features, .

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The data makes the case – women-only founded startups received 1.2% of VC funding in MENA in 2024, up from 0.47% in 2023. August 2025 broke the mould: two deals alone channelled $72.3 million to female-led ventures in a single month.

One was Gathern, a Saudi AI-powered vacation rental platform founded and led by Hala Aldosari, which raised $72 million in a round led by PIF’s Sanabil Investments, reaching a $266 million valuation. That makes Gathern the highest-valued in MENA founded and led by a woman.

The other deal was Phys, a Saudi youth health platform co-founded by Zainab Alshaber, focused on gamified activity tracking for children. Different sector, same indicator – the trend is spreading.

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The Founders Building It

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Nour Taher is targeting a major blind spot in the . As CEO of intella, a Saudi-based company originally founded in Egypt, she’s leading the development of Arabic-first AI – speech-to-text, natural language processing and analytics that work across 25 Arabic dialects. The company raised a $12.5 million Series A in 2025, led by Prosus, bringing total funding to $16.9 million.

The company is now launching Ziila, an Arabic digital human designed for enterprise customer engagement. With Arabic-first AI wide open globally, Taher is the closest to dominating the sector.

In the UAE, CozmoX is showcasing a completely different type of AI venture worth watching. Co-founded by Nuha Hashem, the company builds AI employees capable of doing the work of 100 people: customer service, sales, debt collection, audits, invoice processing. Only five months into its launch by early 2025, CozmoX had onboarded more than 50 companies in the Emirates.

This rapid growth proves both the product’s value and market demand – the UAE’s regulatory infrastructure and AI-first national strategy have created conditions that compress the distance between launch and traction.

Over in Egypt, Dr. Rasha Rady and Dr. Doaa Aref have turned Chefaa into one of the most interesting female-led healthtech startups to watch – an AI-powered e-pharmacy platform with GPS-enabled services now operating across eight Saudi cities, having raised $5.25 million from Newtown Partners and Global Brain.

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What Changed To Make This Possible

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Several changes aligned simultaneously to create this momentum. The UAE’s National AI Strategy 2031, Saudi Arabia’s PAISDA and the active involvement of both the UAE Ministry of AI and the Saudi Authority for Data and AI in backing women-led AI startups created a structural tailwind that has fundamentally changed what’s possible for founders in the region. Regulatory sandboxes, 100% foreign ownership rules and dedicated startup infrastructure have made the region considerably easier to build in than it was at the start of the decade.

Capital followed the strategy. AI startup funding in MENA rose 22% in 2025, with more than 60% directed to the UAE, and between 2022 and 2024 the region saw $660 million raised across 322 AI deals, with one in five VC deals in 2024 involving an AI company. Saudi Arabia led MENA VC in 2025 with $1.72 billion raised, up 145% year on year – that surge in capital helps serious startups secure funding, including female-founded ventures.

Dedicated programmes filled in the spaces that capital alone doesn’t cover. Google’s Women in AI Growth Academy, launched in 2024 as a partnership between Google for Startups, the Saudi Authority for Data and AI and the UAE Ministry of AI, offered an equity-free development programme to ten women-led in its first cohort.

The programme is designed precisely to address the pre-seed and seed stage where women-led companies have historically been most disadvantaged.

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What The Next Generation Can Expect

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The upward trend is clear and unmistakable. Government strategy, international capital and dedicated programmes have created a foundation that simply didn’t exist five years ago, and the founders who moved early are now demonstrating what’s possible at large. Gathern, intella and CozmoX are the proof of concept that the next generation can point to.

Gathern’s $266 million valuation, intella’s Prosus-backed Series A and CozmoX’s rapid UAE adoption all demonstrate something that wasn’t demonstrable three years ago: women-led AI companies in can reach serious scale with serious investors. Female entrepreneurs in the region are projected to double by 2030. The infrastructure – government strategy, VC investment, dedicated programmes – is more developed than it’s ever been.

The opportunity that remains most open is also the most distinctive: Arabic-first AI. Global models still underperform significantly on Arabic language tasks. The founders who build locally grounded, culturally specific AI tools for a 400 million-person Arabic-speaking market have a true first-mover advantage that no Silicon Valley lab can replicate from a distance.

Rather than a niche market, this represents one of the most underexplored segments in global AI development. Currently, women like Nour Taher are best positioned to capture it.

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Google AI Overviews, Perplexity, ChatGPT Search and Google’s AI Mode are answering more queries before the user ever reaches the results list. According to research cited by Ahrefs, position-one pages see an average 58% lower click-through rate when an AI Overview is present on the results page. A separate study found that on pages with AI Overviews, only around 8% of users clicked a link, compared to 15% on traditional results pages. Links inside the AI Overview itself were clicked approximately 1% of the time.

The most straightforward way to explain this situation: search used to direct traffic to the answer – is now becoming the answer. This kind of business hurdle in SEO has never been seen before, and the playbooks built on “rank and collect” are colliding with a reality where ranking and collecting have been separated.

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Where The Traffic Went

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The break is concentrated in informational queries – the how-to content, explainers, comparison pieces and definitional articles that built a generation of content-led businesses.

These are exactly the query types that AI systems are most confident answering, and where zero-click behaviour is most pronounced. A user asking “what is a stablecoin” or “how do I reduce my CAC” in 2026 is more likely to get a sufficient answer from AI Overviews before they ever see the organic results than they were in 2023.

Commercial and transactional queries are holding up better. Users closer to a decision – comparing specific products, looking for pricing, seeking a service provider – are less satisfied by a summary and more likely to click through for evidence, specificity or to take action. The businesses most exposed to the current shift are those that built their organic traffic on top-of-funnel informational content with limited commercial intent. The businesses least exposed are those whose organic traffic was always more transactional in nature.

What this means for is a shift in objective – ranking is no longer the finish line. The new goal is being the answer, the citation, or the next best click when a summary isn’t enough. That requires a different kind of content, a different set of KPIs and, for many businesses, a fairly uncomfortable conversation about which parts of their organic traffic were always less valuable than the analytics suggested.

We asked SEO strategists, founders and growth leads who are navigating this shift to share what’s broken, what still works and what the right response actually looks like.

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Our Experts

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• Kshitij Chaudhary, Founder, Dintellects Solutions
• Courtney Garner-Curley, SEO Strategy & PR Lead, Visualsoft
• San Nakra-Shah, Co-Founder and Managing Partner, ChilliMint Europe
• Ryan Gliozzo, SEO Lead, Waggel Pet Insurance
• Paarath Sharma, SEO Specialist, Pixis
• Danny Sullivan, CEO and Founder, Nomada Digital
• Brian McGrath, President, Keller-Heartt Oil Company
• Carmen Hughes, Founder, Ignite X
• Matthew Robinson, Senior PR and SEO Strategist, Definition
• Amanda Walls, Founder and Director, Cedarwood Digital
• Aidan van Vuuren, Head of Digital, Peak Digital
• Anna O’Brien, SEO Specialist, Solve

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Kshitij Chaudhary, Founder, Dintellects Solutions

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“AI Overviews now appear on 48% of all queries. Organic CTRs have dropped between 15 and 89% where they show up. 60% of Google searches end without a single click and in AI Mode, that number hits 93%.

“But here’s what most people are getting wrong: they’re blaming the traffic drop and missing the real problem. Rankings and visibility are no longer the same thing. The overlap between top-10 Google rankings and citations collapsed from 75% in mid-2025 to just 17 to 38% by early 2026. You can sit at number one and still be completely invisible to the majority of your audience.

“What I tell every client right now is this: stop trying to rank, start trying to be quoted. LLMs don’t reward keyword-stuffed pages. They cite content that’s factually dense, clearly structured and genuinely authoritative. If an AI can’t extract a clean, credible answer from your page, it won’t reference you.

“The bigger opportunity nobody’s moving fast enough on: the mention graph is replacing the link graph. Digital PR, expert contributions and getting featured in authoritative roundups are now AI visibility plays, not just brand marketing tactics. And the visitors who do click through from AI-influenced results convert at 23 times the rate of standard organic traffic. The volume is lower, but the intent is razor sharp.”

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Courtney Garner-Curley, SEO Strategy & PR Lead, Visualsoft

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“2026 will not be about just ranking on the search results page for keywords any more. A successful SEO strategy will be about becoming a trusted, well-organised resource that both users and AI can easily find and reference information from.

“With the emergence of AI search results, the old concept of ‘one keyword, one page’ is no longer a viable strategy. Traffic is being valued differently than ever before because many informational searches will not find their way to your website when responses are already found in the form of Google AI Overview, ChatGPT Search or Perplexity. This does not mean SEO is dead. It means SEO now requires being viewed as a conversion, authority and visibility-based marketing effort, rather than a traffic-generating one.

“Aside from needing to reimagine how to structure your content, many of the fundamental pieces of technical SEO still remain. Technical SEO, speed and crawlability, a clear information architecture, high-quality content and topical authority are still highly relevant. But how we organise our content is changing. In 2026, instead of focusing on isolated keywords, brands should develop topic clusters around their core service offerings – each with logical relationships to each other through informational, educational and expert content, use cases, FAQs, case studies and reviews.

“In 2026, top online search strategies will not only be asking ‘how do we obtain the click?’ but also ‘how do we earn an AI’s trust to be used as a source?’”

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San Nakra-Shah, Co-Founder and Managing Partner, ChilliMint Europe

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“F�ǰ� years, SEO has been about one thing: getting found. The objective was simple. Rank highly, attract visitors to your website and convert them into customers. AI is changing that objective.

“The biggest shift in 2026 is that SEO is becoming less about winning clicks and more about winning citations.

“With Google AI Overviews, , Perplexity and other AI-powered search experiences, users are increasingly getting answers without ever visiting a website. The question is no longer whether your business ranks number one – it’s whether your content becomes one of the sources the AI chooses to reference.

“And many organisations are missing this shift. Discussions about AI and SEO still focus on content generation: how quickly can we create blogs, articles and landing pages? But AI has effectively removed content scarcity. When every company can publish hundreds of articles a week, the real differentiator becomes authority, expertise and reputation.

“In many ways, SEO is morphing into digital PR. The winners won’t necessarily be the companies publishing the most content. They’ll be the companies building the strongest reputation within their market. And that’s particularly important in sectors such as fintech, payments and financial services, where trust and credibility matter far more than content volume.

“Because when content becomes infinite, trust becomes the competitive advantage.”

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Ryan Gliozzo, SEO Lead, Waggel Pet Insurance

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“The biggest thing that’s broken in SEO is the obsession with rankings as the main measure of success. In 2026, ranking position alone does not tell the full story because Google AI Overviews, ChatGPT Search and Perplexity can answer the query before anyone clicks. Businesses need to think less about ‘how do we get the click every time?’ and more about ‘how do we become the source the machines trust?’

“What still works is the fundamentals. Strong technical SEO, fast pages, useful content, internal linking, authority, brand demand and clear topical expertise. But the way we package that content has changed. Pages need to answer questions clearly, show real experience, use structured information, cite facts properly and be genuinely useful enough to be referenced by both people and AI systems.

“The opportunity is in building brands that are visible across the whole search ecosystem, not just Google’s ten blue links. That means investing in content that solves real customer problems, digital PR, original data, comparison pages, FAQs, expert commentary, appearing in Reddit, Quora and forums, as well as having assets that can easily understand and quote.

“F�ǰ� me, winning SEO in 2026 is about becoming unavoidable. You still need rankings, but you also need to be present in every touchpoint where customers are researching before they buy.”

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Paarath Sharma, SEO Specialist, Pixis

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“The old playbook optimised to win the click. In 2026, the click is no longer guaranteed and chasing it is the wrong goal. The winning move is to become the source the AI quotes.

“What’s broken: ranking number one to capture a click that AI Overviews and ChatGPT now intercept. We’re seeing impressions hold while CTR quietly collapses on informational queries. If your whole strategy was traffic volume, you’re optimising a metric the machine already ate.

“What still works, and harder than ever: genuine authority. AI systems pull from sources they can parse, trust and attribute – clear structure, original data, named experts, strong entity signals. Thin, derivative content was always weak; now it’s invisible. Depth and primary research are the moat.

“Where the opportunity sits: stop measuring rankings, start measuring citations and share-of-voice inside AI answers. We’re restructuring client content for extractability – direct answers up top, schema markup, statistics AI can lift cleanly – and tracking which brands get named in Perplexity and ChatGPT responses. Being cited builds brand recall even without a click; that recall converts later through branded search and direct visits.

“The honest truth: traffic will fall and that’s fine. treat AI search as a distribution channel for authority, not a faucet for clicks.”

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Danny Sullivan, CEO and Founder, Nomada Digital

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“Most businesses are still judging SEO by traffic, and that’s exactly why they’re panicking. Rankings hold, clicks drop, and everyone assumes something’s broken – but really nothing is. The search result answers the question now, so the user often never needs to land on a site to get what they came for.

“The bigger shift is in how people buy. A single B2B decision now runs across ten or more touchpoints and at least four platforms. Buyers aren’t on one channel, so a business that only shows up in one place is invisible where the decision is really made.

“SEO still matters and businesses still want to rank, but ranking is now one touchpoint among many. The real job is being the source these tools quote when they answer users’ queries, because most buyers read that answer before they click anything, if they click at all.

“Being cited in AI answers is far less crowded than page one of Google has been for years, and that traffic converts better, because the buyer arrives already half-sold by a source they trust. We recently took a client from zero to 20% ChatGPT visibility in a week, with one piece of content and a single well-placed article.”

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Brian McGrath, President, Keller-Heartt Oil Company

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“The old SEO playbook assumed a human clicking a blue link. That assumption is dead.

“At Keller-Heartt, a century-old industrial lubricant distributor, we watched organic traffic flatten even as our rankings held. AI Overviews were consuming our content and returning the answer without the visit. For a while, that felt like a crisis. Now we treat it as a structural reset.

“What’s broken: thin informational content, generic category pages and any strategy built around volume over authority. AI engines don’t reward whoever published the most – they cite whoever explained it best.

“What still works: specificity and trust signals. Our cross-reference guides, product comparison pages and application-specific content – ‘which hydraulic fluid for a cold-storage warehouse’ versus just ‘hydraulic fluid’ – still drive qualified traffic because the query is too nuanced for a one-sentence AI answer.

“The real opportunity is entity authority. We’ve invested in building a named expert voice – a consistent spokesperson across video, trade press and schema-marked content – so AI systems learn to associate Keller-Heartt with a credible human source, not just a domain. FAQPage and HowTo schema aren’t just ranking tactics any more; they’re your citation application to the AI layer.”

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Carmen Hughes, Founder, Ignite X

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“SEO has evolved into something harder. Three things are broken: keyword-volume thinking, blog-volume strategies and the assumption that ranking number one still means traffic. AI engines now answer most queries directly, so users no longer click through.

“Profound’s analysis of 27 million citations found that earned editorial captures 25 to 33% of AI citations on B2B prompts, while owned content gets just 4.3%. The ranking-first traditional SEO playbook isn’t returning the ROI that it used to.

“What still works is the foundation: technical hygiene and structured content that AI engines can parse. What’s new is the measurement layer. Citation share across each AI engine matters more than impressions. Citation recency matters too: Profound’s benchmark shows the median time-to-first-citation is 6.81 days, with 90% of cited pages within 37 days. Freshness is now a measured discipline.

“The opportunity sits in citation infrastructure: building the earned media, peer-validated and technically clean digital footprint that AI engines weight as trustworthy. Brands that invest here in 2026 will compound for years. The ones still optimising for clicks will spend two more years asking why their sales tanked.”

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Matthew Robinson, Senior PR and SEO Strategist, Definition

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“AI search isn’t a crisis for SEO – it’s an evolution. The fundamentals that have always driven visibility still apply: clear brand positioning, high-quality content and genuine trust built across the right online spaces. LLMs don’t pull answers from thin air. They draw on both their training data and, increasingly, real-time retrieval of web content. In both cases, information reinforced across multiple credible sources wins out – it’s a form of distributed consensus.

“That means third-party validation through PR, editorial coverage and an active presence on platforms like Reddit, LinkedIn and YouTube matters more than ever. Brands also need to focus on information gain – the unique data, expert-led thought leadership and fresh content assets that add something new and are citation-worthy. Anything generic simply won’t cut it.

“The biggest change is measurement. Linear, unbroken organic journeys are increasingly rare. Organic visibility is likely contributing to brand awareness and direct search in ways that are difficult to attribute – some call this the dark SEO effect. The bottom-line impact of SEO is harder than ever to track from start to finish, which means conversions and revenue need to become , not rankings or traffic.”

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Amanda Walls, Founder and Director, Cedarwood Digital

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“The biggest impact AI is having on SEO strategy is the growing importance of trust and external validation. Google AI Overviews, ChatGPT Search and Perplexity are increasingly deciding which businesses are credible enough to cite, summarise and recommend. The most effective SEO strategies in 2026 extend far beyond technical optimisation, keyword targeting and content production.

“This is where what I call E-E-A-T 2.0 comes into play. While Google’s original E-E-A-T framework focused on Experience, Expertise, Authoritativeness and Trust, E-E-A-T 2.0 recognises that AI-powered search systems are evaluating these signals across the entire web, not just on your website. They are looking at who you are, what expertise you can demonstrate, what independent sources say about you and whether your reputation is consistently validated by trusted third parties.

“F�ǰ� businesses, this means SEO is becoming increasingly intertwined with digital PR, thought leadership and brand building. Media coverage, expert commentary, industry awards, speaking opportunities, research and authoritative mentions all contribute to a stronger trust profile that search engines and AI systems can verify independently.”

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Aidan van Vuuren, Head of Digital, Peak Digital

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“We’ve watched clients lose 20 to 30% of their informational blog traffic over the past year without their rankings moving at all. Rank one, zero traffic. That’s the new normal for that intent layer.

“What still works well is anything with commercial or transactional intent. ‘Best X’, ‘X vs Y pricing’, ‘’ – AI tools are still cautious about recommendations and commercial decisions. They tend to refer rather than resolve. We’ve actually seen CTR improve on conversion-intent pages as the informational layer has thinned out.

“The real opportunity is becoming a source the AI cites rather than a page it replaces. That means content with real specificity – data-backed, author-attributed, with clear positions rather than hedged generalities. Schema markup helps, but the bigger lever is simply raising the credibility bar on what you publish. Businesses that do this consistently are building compounding authority across both traditional SERPs and AI results simultaneously.

“The old playbook assumed visibility was the end goal. In 2026, the goal is citation authority – being the source the AI trusts.”

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Anna O’Brien, SEO Specialist, Solve

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“The conversation with clients has changed. A few years ago it was ‘how do I rank higher?’ Now it’s ‘why has my traffic dropped when I’m still in position one?’ It’s important to remember that ranking was never the end goal, it was just the easiest thing to measure. Zero-click search is forcing a more grown-up conversation about what digital marketing is actually delivering – and frankly that’s long overdue.

“AI systems don’t just crawl your site, they pull from everywhere your brand appears: reviews, mentions, third-party articles, directory listings, forum discussions. Digital word of mouth has always mattered for trust but in 2026 it’s also a direct input into whether AI surfaces you or your competitor.

“Page structure matters more than most people realise. AI systems favour content that leads with a clear answer, uses logical headings and clearly translates the information without filler. If your page isn’t structured for easy extraction then it isn’t structured for 2026.

“The businesses that will benefit are the ones that stop thinking about SEO as a single channel and start treating every touchpoint as part of the same system. Consistent, accurate data fed across your website, your profiles, your reviews and your is what the machine learns from. Give it good information everywhere, and it will work for you.”

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For any questions, comments or features, .

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While the data looks strong, it masks a persistent pattern. A disproportionate share of the companies built on the back of that early-stage investment end up acquired by American buyers, relocated to access US markets or starved of the late-stage capital needed to scale independently. The UK builds and then watches them leave. The pattern has continued for long enough that it now has its own name: the late-stage funding gap, estimated at between $4 billion and $11 billion annually.

The data specifies exactly where the break occurs – UK institutional investors participate in 57% of domestic deeptech seed rounds, by late stage, that figure drops to under 10%. The capital to get a company started in Britain is available, but the capital to keep it British is not.

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Failing By Design, Not By Chance

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The Royal Academy of Engineering’s State of UK Deep Tech report and the 2026 European Deeptech Report from Dealroom and Walden Catalyst trace back to identical core issues: the UK is proportionally strong at creating deeptech companies and proportionally weak at scaling them.

University spinouts account for 34% of the UK deeptech sector and generate 37% of enterprise value, confirming the research pipeline is working, even as the scaleup infrastructure around it hasn’t kept pace.

The initial numbers show that the UK really does have some solid advantages. British deeptech startups reach development milestones at 40% to 60% of the cost of their US equivalents, according to analysis presented to the British Consulate General. The sector is focused on areas with real long-term commercial value – AI (39% of deeptech funding), quantum computing (18% of global investment since 2020), biotech, medical devices – rather than chasing funding cycles. has attracted 18% of all global quantum investment since 2020 from a country of 67 million people – the foundations aren’t the problem.

The problem is what happens at Series C and beyond, when the cheques needed to grow a deeptech company to commercial independence require institutional capital that British pension funds and sovereign wealth vehicles still allocate at a fraction of American equivalents. The US investors who fill that gap come with US expectations: listings on American exchanges, access to American talent pools, proximity to American customers. Accepting the capital often means accepting the trajectory.

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What Would Change The Pattern

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The policy response has historically focused on early-stage incentives: R&D tax credits, Innovate UK grants, the Enterprise Investment Scheme. These have worked, which is why the early-stage numbers look strong. What’s absent is equivalent support for the growth stage, where companies need patient capital over a five-to-ten-year horizon rather than venture returns over a three-to-five-year one.

The UK government committed £2 billion to AI over four years and approximately £1 billion toward sovereign compute capacity – neither of these is primarily a growth-stage deeptech instrument. The distance between building a world-class quantum or biotech company to Series B and having the domestic capital base to take it to independent scale hasn’t been closed by any announced policy so far.

The unvarnished truth of this discussion also involves a point the industry rarely admits: some of the UK’s best deeptech founders choose American acquisition not because they’re forced to but because British capital markets offer a less attractive exit pathway, British institutional investors are less willing to hold illiquid positions at scale, and the cultural default in remains selling early rather than building long.

Those aren’t problems that more government grants fix. They’re problems that require a different relationship between Britain’s institutional capital and its most ambitious technology companies.

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The Gulf region provides a compelling response to that. Saudi Arabia, the UAE and Qatar are in the middle of some of the most ambitious infrastructure buildouts in the world – dense new city districts, automated port and logistics hubs, advanced manufacturing zones, AI-powered hospital networks and utility infrastructure designed from the ground up for intelligent automation. These are new projects built with AI at their core, avoiding the need to retrofit outdated systems. According to GCC states treat AI as a core strategic capability rather than a trial, which changes the procurement dynamics.

Sarah Rees, CEO of Signwl, which tracks GPU cloud pricing and AI infrastructure capacity globally, points to an unusual indicator in the current data. “MENA is the tightest major GPU region we track in terms of capacity,” she says. “H200 spot pricing is currently trading 5% above on-demand price, which suggests material utilisation relative to supply – a highly unusual occurrence.

MENA tech founders also have local access to frontier silicon including Nvidia’s Blackwell GB200, which vision-language-action models and robotics depend on.” She also notes a concentration risk: 85% of GPU SKUs available across MENA cloud regions are Nvidia, compared to 62% in the US and 65% in Europe, which she says founders should build around now to maintain silicon flexibility.

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Which Sectors Feel It First

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Logistics and ports offer the most immediate potential for development.

The Gulf has been automating container terminals for years and the arrival of production-ready gives operators what they’ve been waiting for: the ability to close the distance between ambition and execution. Elmer Morales, a two-time founder and former big tech engineering leader currently building AI-native software infrastructure, is direct about this. “Jebel Ali is an obvious candidate. So is NEOM’s logistics backbone,” he says. “These are environments with controlled variables, high transaction volume, and clear ROI on automation. The infrastructure appetite is already there.”

Healthcare is the sector Morales describes as the “sleeper.” The Gulf has invested heavily in hospital infrastructure but faces a persistent shortage of skilled labour in diagnostic and operational roles. “Physical AI agents that assist in triage, inventory, and patient flow are not science fiction at this point,” he says. “They are procurement decisions.” Rees adds a data sovereignty dimension: locally-run agents are particularly relevant for healthcare given the low energy prices in the region and the sensitivity of medical data, with low latency and data localisation both practical operational advantages rather than theoretical ones.

Smart-city operations are another early fit, where physical AI can layer onto existing sensor networks, asset management systems and automation stacks already being built across Gulf projects. This blend of greenfield environment and state-backed procurement appetite is rare globally – most markets require physical AI to prove itself against existing infrastructure. In much of the Gulf, the infrastructure is being designed with these systems in mind.

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The Future-Focused Playbook for Founders and Operators

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Morales challenges the dominant belief that physical AI is strictly a hardware phenomenon. “What founders and operators need to think about now is integration, not innovation,” he says. “The technology stack is now largely commoditised. The competitive advantage in the next 24 months will belong to whoever figures out how to deploy these tools inside existing operational structures without requiring a full rebuild. That means deep partnerships with regional operators, not just pitching to government programmes.”

The winners in this field will likely be companies that can localise hardware support, data pipelines, safety systems, maintenance and operator training for regional conditions – the heat, dust and fast-changing infrastructure that characterise Gulf deployment environments. Proving ROI in narrow, high-frequency use cases first, rather than pitching all-encompassing robotic solutions, is the approach most consistent with how large Gulf operators actually make procurement decisions.

Morales puts the broader opportunity straightforwardly: “ is not just a deployment zone. It’s one of the few places on earth where the capital, the political will, and the infrastructure ambition exist at the same time. That window is open now.” The Gulf may not invent every robot first. But right now, it’s building the environments where those robots will learn to operate at scale – and that might matter more.

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It’s the third time in under a year that a major US AI lab has made the same decision. In April 2026, OpenAI opened its first permanent London office at King’s Cross, with capacity for 544 workers, having designated the city its largest research hub outside the US in February. That same month, Anthropic expanded its London presence to 158,000 square feet in the Knowledge Quarter, scaling from 200 to 800 staff capacity.

When three top-tier AI firms choose the same city in a single year, it begs the question: why this location, and is the momentum as solid as it looks?

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The Data Behind The Hype

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London is home to about 758 AI companies, according to a report released during London Tech Week 2026, which is more than Paris and Berlin combined. Almost 30% of Europe’s new generative AI startups are based in the city.

raised a record $3.5 billion in VC investment in 2024, a 52% increase from the year before, making the city third globally for AI venture capital behind New York and the Bay Area. The UK AI market had a combined valuation of $230 billion in Q1 2025, the largest in Europe, with 20 AI unicorns and more than 2,300 VC-backed AI startups.

The investment is unusually concentrated geographically: 90% of UK AI investment over the past five years went into the London-Cambridge-Oxford triangle, with London alone accounting for 71% of total UK AI investment and $13.3 billion over five years. The UK government has backed the momentum with £2 billion committed to the AI sector over four years, approximately £1 billion toward sovereign compute capacity with a 20-fold expansion target by 2030, and up to £500 million for a Sovereign AI Unit. On talent, the UK ranks second globally for tech talent, just behind San Francisco.

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Why US Labs Keep Landing Here

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The reasons aren’t hard to find – London shares a time zone with European clients, has the deepest research talent pool outside the US, and offers labour costs considerably below San Francisco. Google DeepMind is London-based. Synthesia, one of Europe’s most valuable AI companies, is headquartered in the Knowledge Quarter alongside Anthropic’s new office. The concentration creates a pull: more AI companies mean more talent, which means even more AI companies.

Regulatory strategy is part of the calculation too. London gives them a base inside the European market without full exposure to EU regulation, access to the UK’s relatively pragmatic , and proximity to financial services, insurance and legal sectors where enterprise AI has the clearest near-term commercial value. According to data covering 2021 to 2024, London is the second most attractive destination globally for AI-related foreign direct investment, behind only Dubai.

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But Let’s Not Get Carried Away

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The celebration is warranted, but the picture isn’t uniformly positive.

Access to capital and talent remain the two biggest growth barriers cited by UK AI startup leaders, despite the record investment numbers. The $3.5 billion raised in London in 2024 is impressive in European terms and negligible compared to the Bay Area’s $60.7 billion in the same year. The US labs choosing London are doing so partly because of what the city offers and partly because it’s the least difficult European option – which is a different kind of endorsement.

The arrival of and Runway is either going to create the dense commercial and research environment that pulls in the next generation of AI startups and talent, or the infrastructure investment will flow mostly to the US labs themselves while the domestic startup base continues to struggle for capital at scale. Those are two very different versions of the same headline, and the data won’t make clear which one is playing out for another two years at least.

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That picture is changing – MBZUAI in Abu Dhabi, KAUST in Saudi Arabia and a wave of AI-focused academic programmes across the region are now producing graduates specifically trained for the AI economy. Saudi Arabia’s SAMAI programme trained 1.2 million participants in under a year, reaching its three-year target ahead of schedule. Qatar has certified 13,000 professionals in AI skills as of 2025, targeting 50,000 by 2030. MBZUAI’s retention data is notable too: nearly 80% of alumni continue working in the UAE’s AI sector within their first year

That said, the fundamental problem is still unresolved. The UAE holds just 0.7% of global AI talent, ranked 16th worldwide. Saudi Arabia holds 0.4%, ranked 19th. Despite salary packages exceeding $1 million, the Gulf still struggles to attract senior AI researchers at scale, because mature Western hubs offer network density, equity upside at high-growth startups and peer research communities that took decades to build. The pipeline is real, and the sustainability question is still open.

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Education Alone Has Never Been Enough

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The retention challenge is the crux of it. Producing graduates is a solvable problem – every government with money and intent can build a university. Keeping those graduates once they’re good enough to have options is harder.

The data from MBZUAI suggests the Gulf’s approach to this is working better than expected, with long-term residency pathways, competitive compensation and a clear narrative around building AI for regional challenges rather than serving global platforms all contributing to higher-than-expected retention rates.

Education in the region is growing faster than the commercial AI sector around it, which creates pressure on the most talented graduates to seek environments where they can work on consequential problems immediately after graduating. The Gulf’s solution to that challenge is building both simultaneously – universities and the AI startup infrastructure for graduates to work in. Whether that commercial layer can develop quickly enough is the central question.

We asked five experts across AI education, talent development and Gulf business to share their take on the matter.

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Our Experts

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• Corina Goetz: Gulf Business Culture Specialist, Star-CaT
• Pranav Bhatnagar: Book Author and AI Commentator
• Mariusz Bajorek: Founder and Strategic Lead, Momentum Bridge Consulting
• Edward Tian: Co-Founder, GPTZero
• Jitesh Keswani: CEO and Founder, e intelligence

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Corina Goetz, Gulf Business Culture Specialist, Star-CaT

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“I can only answer for the Gulf. MENA is a category that flattens very different countries, and I will not pretend to speak for places I do not work in.

“Inside the Gulf, the question itself is the problem. or homegrown talent – pick one. The Gulf is doing both, deliberately, at the same time, and the West keeps missing it.

“MBZUAI in Abu Dhabi is training graduates on regional problems, not Bay Area problems. KAUST is doing the same in Saudi. Real institutions, real research output. But the more interesting move is what is happening around them. UAE Golden Visas for AI specialists. Equity stakes at G42. Housing packages at NEOM that would embarrass a Series B startup in San Francisco. Saudi salaries that London cannot match. The Gulf is not waiting for its graduates to be ready in ten years. It is importing senior talent now while training the next generation, and it is paying enough to keep both.

“Is the pipeline at the scale the ambition requires? Not yet. Will the region depend on imported expertise for another decade? Yes. But I have sat in offices in Abu Dhabi and Riyadh where the AI teams are half Emirati or Saudi, half hired from London, Cambridge, MIT. That is not failure. That is how Silicon Valley was built in the 1970s. The Gulf understands this. The West has not noticed.”

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Pranav Bhatnagar, Book Author and AI Commentator

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“MENA is at a very interesting turning point. A few years ago, the conversation was mostly about attracting AI talent from outside the region. Today, it is increasingly about whether the region can develop and retain its own talent at scale. The fact that institutions like MBZUAI, KAUST and other AI-focused programmes exist at all is already a sign of progress, because they are creating a generation of graduates specifically trained for the AI economy rather than adapting traditional pathways later.

“That said, education alone does not create a sustainable talent pipeline. People stay where they find opportunity, mentorship, challenging work, funding, and the ability to build meaningful careers. If the most ambitious graduates still feel they must move to Silicon Valley or London to access world-class research, startup ecosystems, or career growth, talent leakage will continue regardless of how many graduates are produced.

“The encouraging sign is that MENA is no longer investing only in education. The region is also investing in , research, startups, sovereign AI initiatives, and innovation ecosystems. That combination is far more powerful than education alone. The real measure of success over the next decade will not be how many AI graduates MENA produces. It will be how many choose to build companies, conduct research, create intellectual property, and lead AI innovation from within the region itself.”

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Mariusz Bajorek, Founder and Strategic Lead, Momentum Bridge Consulting

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“The honest answer is: both things are true at the same time, and that’s what makes this question so difficult. MENA is genuinely building something. MBZUAI and KAUST are producing graduates who can compete globally – I’ve seen CVs coming out of Abu Dhabi that would get interviews at any European or US tech company. That was not the case five years ago.

“But “can compete globally” is exactly the problem. The moment a graduate is good enough to work in San Francisco or London, they have a real choice. And right now, compensation, visa pathways, and the density of high-growth companies still tip the scales westward for many of the best ones. What I’m watching from the talent market side is whether MENA can close that gap fast enough – not just with salaries, but with the kind of career trajectory that makes staying feel like the ambitious choice, not the safe one. That shift is starting. But it’s not there yet.”

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Edward Tian, Co-Founder, GPTZero

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“MENA is creating real opportunities to train people on how to use AI. Universities like MBZUAI and KAUST are creating technically competent graduates. The problem is after they graduate. The best students are looking for environments that have dense research activity, rapid product development, and strong peer relationships. Those ecosystems still exist primarily in Silicon Valley, London, and a few other places.

“I see a timing issue here. Education is growing faster than the industry can grow. This creates an outward pull on people training in the local areas. Retention is better when graduates can work on production systems soon after they graduate. The sooner they can work on projects with real users and get feedback loops, the better. The pipeline is real. The sustainability question hinges on whether the local ecosystems can develop as fast and as deeply as the best of the global AI world.”

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Jitesh Keswani, CEO and Founder, e intelligence

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“The question is not whether the MENA region can produce people who are good at AI. The region is putting money into universities, research and government programmes. The big question is whether it can give these people jobs so they stay for a long time.

“What is encouraging about MENA now is that people are talking about building a community for AI, not just teaching it. We see investment going into AI startups, companies using digital technology, and countries making plans for AI that create real jobs for skilled people. Keeping these people will depend on whether they can have good careers where they live. If the best projects, the fastest-growing companies and the startup capital are still elsewhere, people will still leave.

“MENA is starting to have its own people who are good at AI. But we should not say it is successful just because many students finish AI programmes. We should say it is successful when these people stay, start companies, come up with new ideas and create more AI opportunities in the region itself. The next five years will be about giving people reasons to stay, not just making people who are good at AI.”

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For any questions, comments or features, .

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Revolut posted £1 billion in profit in 2024 and generated £1.1 billion in EBITDA. reported revenue above £1 billion and pre-tax profit of £53.5 million, up from £13.9 million the year before, according to Reuters. Between them, those two companies account for roughly 50% of UK fintech revenue – the sector looks healthy from a distance.

Take a closer look, and you’ll see there’s a lot more going on. Curve, which once had ambitions of a $50 to $60 billion valuation and raised more than £250 million since 2016, has sold to Lloyds for £120 million – less than half what it raised. GoCardless is heading for a discounted exit via a £920 million sale to Mollie, below its peak valuation. The median EBITDA margin across UK fintech improved from -97% in 2022 to -6.4% in 2024 as companies cut costs hard. And excluding Revolut’s £1.1 billion contribution, the entire rest of the UK fintech sector combined produced just £100 million in EBITDA last year.

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One Decision Made Years Ago

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The divide between the winners and the distressed exits doesn’t trace back to luck or market timing. It traces back to a strategic choice made years before the funding environment changed: whether to build for unit economics and profitability from early on, or to chase growth at all costs and worry about the rest later.

Revolut and Monzo chose the former – both pushed hard on efficiency as the cheap capital era ended, reached positive EBITDA sustainably and built revenue models that could actually support their scale. The companies now struggling chose the latter – raised at inflated valuations during the years when capital was essentially free, scaled aggressively without a clear path to profitability and are now selling at discounts or restructuring in a market where investors have stopped accepting “we’ll figure out the margins later” as a plan.

The data speaks for itself, showing exactly this evolution across the industry. While 17 major achieved profitability in 2023, that number rose to 22 the following year. The mantra across the industry has moved to “low growth but high efficiency”. It’s a direct reversal of the logic that defined the 2019 to 2022 boom years, and the companies that didn’t start making that shift early enough are the ones now selling for less than they raised.

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What The Curve Case Study Illustrates

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Curve is the most instructive case study because the distance between ambition and outcome is so stark.
The company set out to build a supercard product that consolidated multiple bank cards into one – a compelling consumer idea that attracted serious investment and real users. But the unit economics never caught up with the vision. After a decade of trying, it sold for £120 million to , a company it was arguably trying to make irrelevant.

GoCardless is a different kind of exit. The business has genuine scale and a real product – direct debit and recurring payment infrastructure – but the £920 million sale to Mollie still represents a significant discount from its peak £4 billion+ valuation.

The founders get their payday, but the peak-to-exit trajectory tells the classic Curve story: valuation inflation followed by a reckoning when hypergrowth stopped being enough.

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The Takeaway For Business Builders

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While the UK fintech sector hit £8.9 billion in revenue in 2024 and continues to grow, a distinct and permanent divide is locking in between top performers and lagging firms. The companies with a future in this market are the ones that figured out how to make money while they were growing, not the ones that assumed profitability would materialise once they hit a certain scale.

The era of cheap capital that made the growth-at-all-costs model viable is over. Investors want to see the money-making mechanics today, not just a “trust us” on future margins. Those building today who are still operating on the logic that scale comes first and economics comes later are building toward the same outcome as Curve. The data from the last 18 months is about as clear a warning as the industry has ever produced.

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