If 2025 was the year marketers finally got hands-on with AI, then 2026 promises to be the year that marks a shift from experimentation to execution.
At least, this was a recurring theme when we asked marketing experts from both inside and outside Adverity for their marketing predictions for 2026. As Lee McCance, CPO at Adverity puts it, “Next year we’ll see less noise about AI, but the impact and results will be much more tangible”.
Beyond that, others point to a narrowing of AI efforts around the use cases that genuinely move the needle, alongside a growing need for AI-literate teams and flexible, composable tech stacks as models continue to evolve.
At the same time, trust across data quality, governance, measurement, and content emerges as a defining battleground, while AI agents begin to transform workflows, channels, and even the structure of the web.
Read on to discover what our team of experts believe will be the key challenges and opportunities that will matter most in 2026, and where teams should focus their efforts to turn AI experimentation into real impact.
By the end of 2025, most marketing teams had a clearer view of where AI actually fits into their workflows. Some use cases moved forward. Others stalled once they hit the limits of fragmented data, inconsistent definitions, or unclear ownership.
That reset is shaping how teams approach AI in 2026. Rather than broad experimentation, the focus shifts to a smaller number of use cases where impact can be proven and scaled.
As Lee McCance explains, “I don’t see AI projects as failing. I see them as learning opportunities. The smart companies will take those learnings into next year and be much more focused on where AI can actually change the business.”
That focus is already changing how marketers think about analytics. AI is no longer just speeding up reporting, it’s starting to influence decisions as they happen. And in 2026, the competitive advantage goes to the companies that invested early in data foundations that support AI agents.
"AI will synthesize cross-channel interactions and recommend the next best action for marketing and sales, turning attribution from a rearview mirror into a steering wheel."
Diana Gonzalez, Senior Product Growth Manager at RevPartners
“Attribution in 2026 will move beyond reporting and into real-time decision-making. AI will synthesize cross-channel interactions and recommend the next best action for marketing and sales, turning attribution from a rearview mirror into a steering wheel. Marketers will finally be equipped to act on insights, not just analyze them,” says Diana Gonzalez, Senior Product Growth Manager at RevPartners.
The rapid pace of model development has made long-term vendor lock-in unrealistic. As Marko Matejcic, Adverity's Product Leader for Intelligence and Data Products notes, “On Monday the best LLM is ChatGPT, on Tuesday it’s Grok, and on Wednesday it’s Gemini. You simply cannot make long-term decisions without composability.”
“On Monday the best LLM is ChatGPT, on Tuesday it’s Grok, and on Wednesday it’s Gemini. You simply cannot make long-term decisions without composability.”
Marko Matejcic, Product Leader for Intelligence and Data Products, Adverity
Composable architectures such as interchangeable models, flexible pipelines, and tools that plug into different environments will become the only way to stay adaptive as AI evolves.
“MCP lets you connect agents and models to real business data without rebuilding integrations every time. The data layer stays governed, authorized, and traceable, even as the AI tools change,” says Marko.
At the same time, marketers themselves need deeper AI literacy. AI can automate tasks, but interpreting its outputs, validating context, and making decisions remain human work.
"You want to be T-shaped. Be genuinely expert in one area, but really open-minded about adjacent platforms, technologies, and alternatives. Otherwise your skills age very quickly."
Lee McCance, CPO, Adverity
Lee explains, “The people who invested over the last two years in becoming more AI-native are in a great position. The people who didn’t are going to struggle. And that’s not just marketing, that’s everywhere. You want to be T-shaped. Be genuinely expert in one area, but really open-minded about adjacent platforms, technologies, and alternatives. Otherwise your skills age very quickly.”
Tools are accessible. Skills are what separates the teams who move fast from those who fall behind.
Trust threads through every major challenge coming in 2026: trust in data, in tech, and in content.
Harriet Durnford Smith, CMO and COO at Adverity stresses the tech adoption issue which will be key, “There’s still a reticence to adopt AI because marketers think it’s stealing their jobs. Next year the narrative has to shift. AI’s primary function is to automate, not replace. The human role becomes strategy, creativity, and judgment. Things AI still can’t do well on its own. Marketers will become the orchestrators of their AI tools.”
"AI’s primary function is to automate, not replace. The human role becomes strategy, creativity, and judgment."
Harriet Durnford Smith, COO, Adverity
Trust in data also becomes non-negotiable. AI will increasingly be asked to justify its outputs, and companies need traceability to answer questions from leadership, and from customers.
“Advertisers are understanding that not all data of an equal quality, with advertisers trusting their first party data more but still understanding its limitations and looking at ways to plug the gaps and validate the data points. This erosion of trust in data sources will continue, but with it the consequent reduction in confidence in the outputs from advertising measurement tools, compounded by black box solutions and limited auditing,” says Sarah Mansfield, former VP of Global Media at Unilever and now founder of Barcarolle consultancy.
As Lee warns, “We’re not far from the first very public AI failure. When it happens, the companies with strong governance and traceability will be fine. The ones that took shortcuts will find it very expensive to fix.”
"We’re not far from the first very public AI failure."
Lee McCance, CPO, Adverity
“You need to be able to trace downstream actions, whether they’re done by humans or by AI, all the way back to the source data. Otherwise you can’t trust the decisions being made,” he adds.
And on the content side, marketers face tightening quality standards. Search engines have already begun penalising low-effort AI content, while simultaneously sending more traffic from AI assistants.
AI agents already exist, but 2026 is the year they become mainstream. Agentic browsers like Google’s expected Gemini-powered Chrome will let non-technical users automate multi-step workflows visually. Meanwhile, MCP/API-based agents will quietly power back-end automation at scale.
Marko explains the shift: “Agentic browsers will bring automation to non-technical users. Once people see what’s possible in the UI, they’ll want the same workflows built as faster, more reliable agents through MCP.”
But a second trend emerges: an internet of agents. As agents generate and respond to content, large parts of the open web may become machine-to-machine noise.
“We’ll see the emergence of paid, sponsored media placements within AI chatbots, as platforms begin to capitalize on the commercial potential of these tools,” says Sarah Mansfield.
“We’ll see the emergence of paid, sponsored media placements within AI chatbots."
Sarah Mansfield, former VP of Global Media at Unilever and now founder of Barcarolle consultancy
Lee puts it bluntly: “You could end up with bots marketing to bots, with no humans involved. Performance metrics will look great, but they won’t help businesses grow.”
Harriet expects to see a twofold effect here, the first being that “Marketers must evolve their measurement systems to track brand influence and AI authority, proving that their content is trusted and cited by the AI systems themselves, even if the user never clicks through to the website.”
"People and relationships will become more important as technology strips away the low-hanging fruit of tasks that can be automated”
Barry LaBov, author, and founder of LABOV marketing agency
The second of Harriet’s predictions is that this dynamic may push marketers back toward channels where human engagement is guaranteed: events, experiential, offline media, and direct relationships. Barry LaBov, author, and founder of LABOV marketing agency, agrees on this point, pointing out that “people and relationships will become more important as technology strips away the low-hanging fruit of tasks that can be automated”.
The AI arms race among Google, Meta, Amazon, OpenAI, and others will define which channels dominate and how measurement evolves. It may further concentrate spend into fewer platforms, or it may fracture the landscape entirely.
But one message from Adverity’s leadership was unequivocal: Whatever direction AI takes, data remains the backbone of marketing.
"Marketing budgets will see a deeper focus on data hygiene, quality, and lineage."
Harriet Durnford Smith, COO, Adverity
As Harriet emphasizes: “Marketing budgets will see a deeper focus on data hygiene, quality, and lineage. Teams will need to prove the provenance of the data their models rely on to ensure outputs are accurate, fair, and compliant. If the foundational first-party data is biased, incomplete, or corrupted, the AI's personalized campaigns will fail, wasting spend and eroding customer trust.”
"In 2026, AI won’t be the competitive edge - data quality will."
Diana Gonzalez, Senior Product Growth Manager at RevPartners
Diana Gonzalez builds on this sentiment, stating that “In 2026, AI won’t be the competitive edge - data quality will. Marketing teams with clean, enriched, continuously updated data will unlock AI’s full potential, while those with fragmented CRMs and inconsistent processes will fall further behind. The winners will be the ones who treat data architecture as a core marketing asset”.
No model, channel, or agent can compensate for missing or unreliable data.
To translate these predictions into action, marketers should prioritize three things:
- Strengthen your data foundations.
Your AI outputs will never exceed the quality of the data feeding them.- Build data and AI literacy across your team.
Skills and adoption determine whether AI accelerates or derails your workflows.- Choose flexible, composable tools.
The market will shift fast in 2026. Your stack needs to shift with it.
As AI evolves, the teams that succeed will be the ones with strong data foundations, adaptable systems, and the skills to turn insight into action. In 2026, across predictions from both Adverity’s leadership team and our expert podcast guests, one theme is clear: progress next year will be defined less by speed and more by disciplined execution of AI deliberately, responsibly, and at scale.
About Diana Gonzalez
Diana Gonzalez is Senior Product Growth Manager at RevPartners, where she focuses on data-driven go-to-market strategy across sales and marketing. She brings over a decade of experience in RevOps, go-to-market strategy, and marketing automation. A certified Pavilion member, she has been recognized for designing sales enablement programs that have driven measurable gains in productivity, retention, and revenue. At Riverside, she led cross-functional strategy across business development, sales, and customer success. Diana holds an MBA from Universidad Pontificia Bolivariana and a degree in International Business from Universidad de Medellín.
About Sarah Mansfield
Sarah Mansfield is an industry-leading media consultant and founder of Barcarolle Ltd, with over two decades of expertise across media, retail, and digital marketing. At Unilever, she served as VP of Global Media, leading media operations, programmatic platforms, and a €5 billion budget, before launching her consultancy after 12 impactful years. A recognized thought leader, Sarah holds key roles at ISBA, MMA EMEA, and I‑Com. Her work has earned accolades such as Drum’s Digital Trading Leader Award and a Cosmopolitan Female Icon honor.
About Barry Labov
Barry Labov is a two-time Ernst & Young Entrepreneur of the Year, celebrated author, and the founder of LABOV, a marketing agency trusted by brands like Harley-Davidson, Audi, and The Macallan. His book, The Power of Differentiation, explores how companies can escape the commodity trap by uncovering and amplifying what makes them truly unique. He’s also the host of the Difference Makers podcast, where he speaks with leaders across industries about how differentiation drives lasting business success.
About Marko Matejcic
Marko Matejcic is Adverity's Product Leader for Intelligence and Data Products, recognized as IAB Europe’s Digital Strategy Person of the Year 2022 and the Cannes Lions 2021 winner in the Data Technology category. With almost two decades of experience in data, AI, and media technology, he has led both media and product strategy within WPP. His work has also earned honours from the Festival of Media Global and Euro Effie awards.
About Lee McCance
Lee McCance, Chief Product Officer at Adverity, brings 20+ years of product leadership from roles at GroupM, Essence, and McAfee. He’s now spearheading Adverity’s expansion into AI-powered, customer-centric data analytics solutions.
About Harriet Durnford-Smith
Harriet Durnford-Smith is the Chief Operating Officer at Adverity, where she leads business transformation over simple operational alignment. Having built her career as a high-impact CMO and marketing leader, Harriet specializes in evolving marketing and growth functions into strategic business partners and revenue engines. With a proven track record in B2B scale-up technology, she now applies that same commercial rigor to the entire enterprise.