Most leaders are still thinking about AI as something people use.

A person asks a question. The system produces an answer. Someone reads it, checks it, edits it, copies it into another tool, ignores it, or decides what to do next.

That has been the dominant pattern of AI adoption so far, and it has shaped the way organizations think about risk. The human is still the point at which something happens.

Agentic AI changes that.

Most leaders tracking AI adoption are measuring the wrong thing.

They're watching who's using it, how often, which tools. Useful data. But adoption is not capability, and the gap between the two is where organizational AI strategy can fall apart.

The Stanford AI Index 2026, published this week, puts a name to what good actually looks like: centaur evaluations - assessments that measure not the AI system in isolation, but the human-AI team. The insight is straightforward and consequential. If most real-world AI use involves people supervising, steering and integrating model outputs, then that's what you should be measuring. The unit of capability isn't the tool. It's the collaboration.

AI washing has been making headlines. Recent debate around Block and Jack Dorsey is one example of how quickly external narratives can move ahead of what is actually visible from the outside. Whether or not any individual case proves the point, the wider leadership risk is real.

It is easy to look at this and see it as a Big Tech problem. The scale may be different. The scrutiny may be different. But the underlying dynamic is not. This can happen in any organization. And when the narrative outruns reality trust is usually the first thing to go.

Your people are not waiting for you to figure out your AI strategy before forming opinions about it.

They're reading the headlines. They're watching other companies announce layoffs alongside AI investment. They're talking to each other. And if you haven't told them how you're thinking about AI - what it means for the work, for their roles, for what you value - they're filling that gap with whatever's loudest in the environment right now.

Right now, what's loudest is fear.

Nearly every leader I speak to shares a particular anxiety about AI adoption. That they're behind the curve. That others have nailed something they haven't.

If nearly everyone feels this way, most can't actually be behind. But that isn't the interesting part.

In previous technology waves, there was a visible adoption curve - you could pinpoint if you were early, late, or somewhere in the middle (or have a consultant tell you). The destination was knowable. You could, eventually, arrive.

AI doesn't work like that.

Does this sound familiar? You receive a draft document from someone on your team. It’s well structured and covers the key points. But something feels off. The tone is generic. Important details are buried in long paragraphs that say less than they seem to.

You find yourself working backwards to work out what this person is actually trying to tell you, and which details they believed were important.

You’re mentally ‘de-AI-ing’ the communication to extract the core message.

There's something critical to successful AI pilots that often gets overlooked: clarity about who owns what.

Who makes sense of the results? Who helps others learn from it? Who is accountable for what happens next? Identifying a champion is a good start, but it doesn't answer those questions.

People come back from holidays with energy for change. They have stepped away from the daily grind long enough to see what has been frustrating them. They are more open to doing things differently.

I think this is a powerful moment for leaders who know how to harness it.

There is likely more AI capability in your organization than you realize.

People are already using tools, experimenting, finding what works, and solving real problems. The question leaders face is not whether AI is happening, but how scattered individual wins turn into actual organizational capability.

Your team is all over the place with AI. They’re scattered across curiosity, caution, avoidance, and quiet experimentation.

This variation feels messy, but it contains real strategic signal.

Building AI capability isn't like rolling out a new CRM or similar business technologies. AI is a fundamentally different animal - multipurpose tools that anyone can access, capabilities evolving at a dizzying rate, use cases that blur personal and professional, and a moving landscape of what's even possible. Each person is on their own AI journey that intersects with your organizational strategy but isn't contained by it.

Your team is using AI. Probably a lot of it. ChatGPT for emails, Claude for analysis, various tools for various tasks, real productivity gains happening. But are those gains adding up to strategic capability? Or could you still be stuck at the random acts of productivity stage of adoption?

How casual employee use of Chat GPT and other tools at work creates both significant risks and untapped opportunities that require strategic attention.

Shadow AI refers to employees using personal AI accounts for work tasks without official approval or oversight. The applications are typically straightforward - drafting emails, summarizing documents, basic research - but the scale and business implications are substantial.

When I started out in B2B media over 20 years ago, I was recruited to the ‘dark side’. I clearly recall a literal line on the office floor that marked the editorial department’s territory, past which the advertising sales team were never to cross…

Media has always had a historic separation of ‘church and state’, with advertising often perceived as a necessary evil for revenue generation. Interruptive online ad formats added to its woes, eventually raising audience annoyance, and decreasing impact for brands in equal measures. And poorly executed ‘advertorials’ earned early commercial content a somewhat tarnished reputation amongst journalists and readers alike.

I am about to reveal an uncomfortable truth. Over the very many years I’ve worked in content marketing, I have frequently heralded the increasing maturity of the discipline. As innovation and creativity has exploded in the space, smart technology has superpowered our ability to reach and engage audiences at a staggering scale. The number of industry award categories dedicated to success in the field is testament to the fact that it has earned its rightful place in the upper echelons of marketing prowess. And for good reason; focusing on providing value through education, entertainment or inspiration is both worthy and worth it (thanks L’Oreal). So, we can now rest assured that, unlike many forms of advertising, content earns us real engagement and loyalty from our previously ambivalent target audiences.

Right?

Sorry, wrong. Because here’s the truth; they still don’t really trust you. You’re a brand, and they know it.

‘It is not the strongest of the species that survives, nor the most intelligent. It is the one most adaptable to change’

This quote, often wrongly attributed to Charles Darwin (albeit inspired by Origin of Species), was coined by business professor Leon C. Megginson in the 1960s. Has it ever been more apt for the business world today?

The turbulence of the last few years, months and even the last week is putting this adage to the test for the digital marketing industry at pace. Tough decisions around resourcing have had to be made, as almost everyone has been scrambling to fight fires and retain clients. At the same time, we also know that out of crisis can come innovation; we have already seen some clear winners emerge over this time.

At the weekend, I was speaking with a very talented son of a friend who graduated with a first degree in Creative Writing last year. Having recently entered the marketing agency world, he was after some career advice. It struck me what a radically different environment he was faced with at the beginning of his work journey compared to me and my contemporaries. The conversation was animated; from office culture to creativity to - of course - AI. It got me thinking about the huge paradigm shift that many agencies will need to tackle in 2024 regarding pricing models and principles.