“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”
— John Wanamaker
AI is transforming the advertising industry like the introduction of a sophisticated robotic manufacturing line into a traditional artisan workshop. The big platforms (Google, Meta) own the factories and the robots, allowing them to rapidly produce and distribute standardised goods (ads) with incredible efficiency.
Do startups even have a chance to compete in this environment? It turns out that the answer is yes, but not by competing head to head with giants, but rather creating the quality control systems needed to ensure the robots don’t produce faulty or toxic products (governance) or by providing the highly specialised, proprietary tooling and data that influences the robots’ core programming, ensuring a brand’s specific materials are chosen over the competition.
For investors, this creates a big tension between backing innovative solutions that AI enables while trying to avoid ‘frontal collision’ with the big tech incumbents.
Marketing and sales is one of the leading use cases for AI in the enterprise
McKinsey’s 2025 Global Survey confirms AI has moved from experiment to operational reality: 88% of organizations now use AI regularly in at least one business function. Marketing and sales leads adoption and, critically, is the function most commonly reporting revenue increases from AI use.
That being said, when it comes to AI adoption at the enterprise level, most companies remain in pilot mode: nearly two-thirds haven’t begun enterprise-level scaling. High performers (those attributing 5%+ of EBIT to AI) are the exception, aggressively scaling AI in marketing and sales while pursuing growth and innovation, not just efficiency.
Platform Power: How Incumbents Are Pulling Away
The four advertising giants: Google, Meta, ByteDance, and Amazon controlled over half of global ad spending last year. AI is accelerating their dominance as they leverage it to improve targeting, creation, and measurement:
- Meta’s Advantage+ claims a 22% increase in return on ad spend, with Zuckerberg promising brands can soon “tell us what objective they’re trying to achieve… and then we just do the rest”.
- Google’s Performance Max lifts sales by 10%+, while its AI Overviews—where queries are 2-3x longer—provide richer intent data for targeting. They are also deploying AI agents, such as Google’s shopping agent, which users can instruct to notify them when a product price drops
- TikTok now generates video commercials from text or photos and offers AI influencers as a service.
The ability of AI to perform functions like planning, buying, and creative execution at a fraction of traditional costs is a significant threat to the traditional Ad agencies like WPP, despite the fact that they’re leaning in on AI.
The endgame? As OpenAI’s Sam Altman suggests, 95% of what marketers rely on agencies for could soon be handled instantly at near-zero cost by AI.
Where Startups Are Finding Opportunity
While incumbents dominate the platforms, startups are moving into highly specialised areas related to measurement, data, and influencing the AI models themselves:
Vertical integration and consistency: Israeli startup Weavy AI, which recently sold to Figma in a reported $200M deal, understood that AI gives designers magic powers, but it’s not consistent. In addition, a designer needs a programmer to use existing open-source tools like ComfyUI. The result? they set out to build the application layer for design professionals (with a focus on advertising).
Creative A/B testing: Israeli startup Alison.ai scans and analyses thousands of creative elements (e.g., colors, sounds, text, visual objects) within ads using multiple AI models. It cross-references these elements with performance data to identify exactly which components drive results for specific audiences and platforms.
The new SEO: Israeli startup Brandlight uses proprietary data, real-time sentiment tracking, and customized optimization strategies to provide a “heat map” of the internet, showing which sources AI engines use when referencing a brand.
Agent to Agent communication: While still in stealth, Aigency (disclosure: a Remagine Ventures portfolio company) is dedicated to developing technology that enables AI agents to act autonomously and engage with complex online environments for the transactional web.
Automating social media content creation: Israeli startup Munch Studio (disclosure: a Remagine Ventures portfolio company) is an AI-powered platform that handles the full social media management for businesses, generating content, automating scheduling, and repurposing long-form videos into short clips.
And the list goes on. Of course, the challenge here is the risk of commoditisation: every few months the incumbents announce a new feature that can instantly make startups redundant.
Where is AI Advertising still attractive for investors
The current moment presents a dual investment opportunity: the need for tools to leverage AI and the need for tools to control AI.
1. AI Governance and Safety: The rush to adopt AI is outpacing safeguards. Over 70% of marketers have reported an AI-related incident, such as hallucinated outputs (factually incorrect content), bias, or off-brand material. Only a small fraction of marketers plan to increase investment in governance.
This creates a massive market opportunity for startups focused on:
- AI Oversight Tools: Tools for regular AI audits, bias testing, automated evaluation, and continuous monitoring that can scale with content volume and model complexity.
- Transparency and Compliance: Solutions that track how AI is used and flag risks to ensure regulatory compliance (like GDPR) and protect consumer trust. Over 90% of marketers are open to considering a third-party solution to evaluate risks like hallucinations, bias, or off-brand content, signaling a strong need for external expertise.
2. Specialised AI Agents: As AI-powered agents increasingly make buying decisions on behalf of human users, startups that focus on influencing these agents or providing hyper-targeted data insights (like Alembic and Evertune) will be highly valuable.
3. Creative automation: As mentioned in my previous post, vertical integration is the only real defensibility in AI. Startups that understand deeply the existing workflows for advertising and creative professionals have an opportunity to bring automation and increase the productivity of professionals in manual, repetitive tasks. This is true for many roles in the business, but also applies to advertising.
The environment creates fertile ground for startups positioned either to provide essential governance solutions to mitigating risk, or to fundamentally redefine how consumers interact with content and commerce using AI, forcing the incumbents to adapt.
The ad industry is currently navigating a chaotic transition. The biggest winners will be those companies, large or small, that not only adopt AI but fundamentally redesign workflows around it, treating AI as a catalyst for transformation rather than just a tool for incremental efficiency.
This mirrors the dot-com transition when dollars shifted from legacy media to digital upstarts. The winners won’t just adopt AI—they’ll redesign entire workflows around it, treating AI as a catalyst for transformation rather than incremental efficiency.
The ad industry’s trillion-dollar business model is being rewritten these days. The question isn’t whether AI will transform advertising but rather who will capture the value that transformation creates.
He is a former General Partner at Google Ventures (GV) in Europe, former head of Google for Entrepreneurs in Europe, and founding head of Campus London, Google's first startup hub. Eze writes on Israeli tech, venture capital, artificial intelligence, and founder strategy.
He is also the founder of Techbikers, a nonprofit that brings together the startup ecosystem on cycling challenges in support of Room to Read.
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