The AI and Marketing Voices Actually Worth Following

Most "who to follow" lists are just a roster of people with large audiences. This one is organized differently: by what you are actually trying to figure out, and what each person is genuinely good for.

Three problems are covered here. First, how brands actually grow, because the evidence base here is deep and most marketers still haven't internalized it. Second, how AI is changing search and discovery, because this is moving fast and the people thinking most clearly about it are not always the loudest ones. Third, how to build an organization that uses AI well, not just as a productivity toy but as a structural advantage.

Full disclosure: this site is Patrick Gilbert's, so treat his entry and Isaac Rudansky's accordingly. Both are here because the list would be dishonest without the people who actually do this work at AdVenture Media, but you should weigh a self-inclusion for exactly what it is.

Pick whoever is solving your current problem. Ignore the rest until you need them.

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How Brands Actually Grow

Evidence is strongest here, and marketing practice is most consistently wrong in this area. Researchers in this section are not offering opinions. They are reporting findings from datasets most marketers will never have access to.

Byron Sharp

Professor of Marketing Science and Director, Ehrenberg-Bass Institute, University of South Australia

Sharp's central argument in How Brands Grow: What Marketers Don't Know (2010) is that most of what marketers believe about loyalty, targeting, and differentiation is contradicted by the data. Brands grow primarily by reaching buyers who purchase the category infrequently, not by deepening loyalty among existing customers. Mental availability, being easy to think of in buying situations, matters more than most paid media teams want to admit.

Ehrenberg-Bass Institute, which Sharp directs, is described as the world's largest centre for marketing research. That standing is what gives his empirical claims their weight. These are not thought experiments.

Begin with How Brands Grow. If the book's argument about light buyers doesn't change how you think about audience targeting, read it again.

Jenni Romaniuk

Research Professor, Ehrenberg-Bass Institute, University of South Australia

Romaniuk's specific contribution is distinctive brand assets: the colors, shapes, sounds, and characters that let buyers recognize a brand without consciously processing it. Her book Building Distinctive Brand Assets is the most operationally useful thing the Ehrenberg-Bass school has produced for practitioners. It tells you how to audit what you have, measure how well it works, and build new assets deliberately.

Her follow-up, Better Brand Health, extends this into measurement frameworks for tracking brand salience over time. If you are responsible for brand identity decisions, or you're being asked to change them, Romaniuk's work should be your first stop, not a rebrand agency's pitch deck.

Open with Building Distinctive Brand Assets. It is more practical than How Brands Grow and more grounded than almost anything in the brand strategy consulting world.

Mark Ritson

Founder, MiniMBA

Ritson does not have a single named research framework to cite the way Sharp and Romaniuk do. What he has is an unusual ability to translate dense academic marketing evidence into arguments that practitioners can use in a boardroom on Tuesday morning. He is consistently willing to state conclusions plainly when the evidence supports them, which is rarer than it should be among marketing educators.

His MiniMBA programs are built around applying the same body of evidence, Ehrenberg-Bass, IPA effectiveness data, marketing science, that the researchers above produce. For those who want to understand the research without reading the papers, Ritson is a reasonable route in.

Les Binet

Author, Consultant and Visiting Professor, Ravensbourne University

Les Binet and Peter Field built the most widely cited framework in marketing effectiveness from decades of IPA Databank analysis. Their core finding, published in The Long and the Short of It (2013), is that sustainable growth requires both brand-building and sales activation working together, and that most marketing budgets are skewed too heavily toward short-term response. Their research points toward a 60/40 brand-performance split as a general guide, not an absolute rule, but a starting point that most performance-heavy organizations have badly violated.

Binet is currently the more active of the two in publishing and speaking. His work through 2026 continues to draw on the IPA evidence base, and his warnings about the long-term cost of pure efficiency-chasing are worth taking seriously. We covered his Cannes 2026 presentation in detail in our breakdown of his death-spiral warning.

Start with The Long and the Short of It. It is short, densely evidenced, and the most useful single document for anyone trying to argue for brand investment inside a performance-obsessed organization.

Peter Field

Marketing effectiveness consultant and co-author

Field's current institutional affiliation could not be verified from available sources, so it is not stated here. What is verified: he co-authored The Long and the Short of It with Les Binet in 2013, along with Effectiveness in Context and Media in Focus. The IPA effectiveness framework that carries both their names is the most comprehensive body of marketing effectiveness evidence in published form.

Read his work alongside Binet's. They are largely inseparable.

Rory Sutherland

Vice Chairman, Ogilvy UK

Sutherland's territory is different from the Ehrenberg-Bass researchers. He is not reporting brand-growth data. He is applying behavioral economics to explain why rational optimization so often produces worse outcomes than psychologically informed creative thinking. His book Alchemy: The Surprising Power of Ideas That Don't Make Sense (2021) is the best argument in print for why irrational-seeming marketing decisions sometimes work precisely because they are irrational.

He founded a behavioral science practice inside Ogilvy UK, which is where his ideas get tested against real briefs. That applied context keeps his arguments grounded in a way that pure academic behavioral economics often isn't.

Start with Alchemy. It will not give you a framework to run in a spreadsheet, but it will change how you evaluate creative ideas, and that is worth something.

Karen Nelson-Field

Founder and CEO, Amplified; former Professor of Media Innovation, University of Adelaide

Nelson-Field's focus is attention: specifically, measuring it, understanding why it varies across formats and platforms, and using that understanding to predict advertising effectiveness. Her 2020 book The Attention Economy and How Media Works established a research-based framework for thinking about attention as a measurable currency. Her 2024 follow-up, The Attention Economy: A Category Blueprint, extended this into practical guidance for media planning.

Amplified, the company she founded and leads, exists to turn this research into tools that planners can actually use. If you are making media allocation decisions without accounting for attention differences across placements, you are working with an incomplete model.

Turn to The Attention Economy and How Media Works first. Then look at what Amplified publishes if media planning is a significant part of your work.

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How AI Is Changing Search and Discovery

This section matters because AI search is not just a new version of Google. It changes which content gets surfaced, how brand visibility works, and what optimization even means. Below are the people thinking about this most clearly in 2026.

Rand Fishkin

Co-founder, SparkToro

Fishkin co-founded SparkToro and has spent years publishing research on how people actually discover content and make search decisions, as opposed to how marketers assume they do. His 2026 book Zero Click Marketing, co-authored with Amanda Natividad, addresses what happens to audience-building when search increasingly answers questions without sending traffic anywhere.

Zero-click search is a real and growing problem. Fishkin's work on it is more data-grounded than most of the commentary, because SparkToro gives him access to behavioral data that opinion writers do not have.

Start with the SparkToro blog if you want his current thinking. Read Zero Click Marketing when it publishes for the strategic argument in full.

Aleyda Solís

SEO and AI search consultant, speaker; affiliated with Orainti and SEOFOMO

Solís is producing some of the most operationally specific public work on how to maintain organic visibility as AI search changes the rules. Her 2026 framework "Winning organic in 2026: A framework for surviving Google's AI era" and her work on "Third-Party Citation Optimization Prioritization in an AI Search Era" are not think-pieces about the future. Both are structured approaches to a problem practitioners are facing right now.

Her Speaker Deck presentations are worth reading in full. They are dense with frameworks and light on filler, which is not the norm in SEO content.

Go to her Speaker Deck page and filter to her 2026 presentations. The organic visibility framework is the right starting point.

Andy Crestodina

Co-founder and Strategic Director, Orbit Media Studios

Crestodina has built a long-running body of work on content marketing strategy through Orbit Media Studios, including multiple editions of Content Chemistry: The Illustrated Handbook for Content Marketing. His 2026 coverage addresses how AI search changes content strategy, and his approach is consistently more rigorous than the average content marketing advice because he publishes original research rather than recycling received wisdom.

Start with the Orbit Media blog. His annual content marketing survey is one of the few practitioner-research documents in this space worth treating as actual data.

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How to Build an Organization That Uses AI Well

At this point the conversation shifts from understanding AI's effect on marketing to building the internal capability to act on that understanding. Knowing that AI search works differently from traditional search is one thing. Having a team that can respond to it systematically is another.

Ethan Mollick

Professor, Wharton School, University of Pennsylvania

Mollick is the most useful public thinker on what it actually feels like to work alongside AI, and what organizations need to understand to do it well. His 2024 book Co-Intelligence: Living and Working with AI is not a hype document or a fear document. It is a careful argument about how humans and AI systems should collaborate, grounded in his research at Wharton and his own extensive use of these tools.

His Substack newsletter, One Useful Thing, publishes practical experiments and findings from his ongoing work with AI systems. He tests things, reports what he finds, and revises when the evidence changes. That epistemic honesty is rare in this space and worth paying for.

His second book, Co-Existence: The Next Phase of AI, is scheduled for late 2026 and extends the argument into longer-term organizational questions.

Start with One Useful Thing on Substack. Read Co-Intelligence if you want the full argument. Both are accessible without a technical background.

Paul Roetzer

Founder and CEO, Marketing AI Institute; Founder and CEO, SmarterX

Roetzer has spent longer than almost anyone building the infrastructure for thinking about AI in marketing specifically. Marketing AI Institute, which he founded, has been publishing on this topic since before most marketing teams had a ChatGPT account. His 2022 book Marketing Artificial Intelligence is the most structured attempt to give marketers a framework for evaluating AI's role in their work. His 5Ps of Marketing AI, Planning, Production, Personalization, Promotion, Performance, give practitioners a vocabulary for the conversation that is more useful than the generic "AI strategy" language most organizations use.

He also created the Marketing AI Conference (MAICON), which is the most practitioner-focused event in this space.

Read Marketing Artificial Intelligence first. Then subscribe to the Marketing AI Institute's newsletter if you want ongoing coverage.

Christopher Penn

Co-founder, Trust Insights

Penn's current title could not be verified from available sources, but his association with Trust Insights is clear. Trust Insights publishes the 5P Framework, Purpose, People, Process, Platform, Performance, which is one of the more operationally useful structures for thinking about how to build an AI-first marketing team. He is described as the author of over two dozen marketing books, and his work on AI for marketers is among his more cited output.

The Trust Insights site is the right place to begin. The framework documentation is free and worth reading before you buy anything.

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The Two Entries From This Site

Both of these are from AdVenture Media, which is the disclosure at the top of this article in practice rather than in principle. Judge them on the specifics like every other entry here.

Patrick Gilbert

CEO, AdVenture Media, and author of Never Always, Never Never

The argument in Never Always, Never Never: Strategic Marketing in an AI World is that the marketing evidence base does not get less relevant in an AI environment. Ehrenberg-Bass, the IPA effectiveness work, behavioral economics: all of it matters more, because AI amplifies whatever strategic foundation you feed it. A weak brief fed to a powerful model produces better-looking weak work, not strong work.

The book also takes on the structural question of building an AI-first culture, treating it as a change in how work gets done and how teams are organized rather than as a tool-adoption project. The AI Double Helix framework addresses this in two strands, internal efficiency and external value, each feeding the other in a compounding loop. You can read more about how that framework works at the AI Double Helix implementation guide.

Start with the book if you want the full argument. The blog and learn sections of this site expand on specific chapters.

Isaac Rudansky

Founder, AdVenture Media and The Modern Marketing Institute

Rudansky founded AdVenture Media and The Modern Marketing Institute, and his performance media course is among the most widely taken paid-media trainings on Udemy. The reason to follow him is narrower and more useful than most entries on this list: he teaches the mechanics of paid platforms to people who have to run them, at a level of detail that strategy writing usually skips. That matters more now, not less, because how ad platform AI actually learns from your data determines what a media buyer can still control.

Start with the Udemy courses if you are building or rebuilding paid media understanding from the ground up. Start with his AI training work if your problem is getting a team competent rather than getting a campaign live.

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Where to Start Based on Your Most Urgent Problem

Read one section based on your most urgent problem, not all three.

If your organization is debating brand versus performance budget allocation, start with Les Binet and Peter Field. Read The Long and the Short of It before you sit in that meeting. The 60/40 framework gives you a grounded starting point for that argument.

If your SEO and content strategy feels destabilized by AI search changes, start with Rand Fishkin and Aleyda Solís. Their 2026 work is the most current and specific.

For those trying to figure out how to move a team from using AI tools occasionally to building it into how work actually gets done, begin with Ethan Mollick's One Useful Thing newsletter, then read Paul Roetzer's Marketing Artificial Intelligence. Organizational AI adoption is a different question from which tools to buy, and Mollick and Roetzer address the former more directly than almost anyone else.

Sharp and Romaniuk are long-term reads. Their work does not expire. If you have not read How Brands Grow or Building Distinctive Brand Assets, put them on the list for the next time you have a week that is not on fire.

Everyone else: background reading that pays dividends when it connects to a real decision you are facing.