AI Isn't the Answer. It's the Start of the Question.

93% of leaders say their organisations aren’t ready for AI.

But what’s really holding them back?

In this episode of the No Bull Ideacast, I’m joined by James Easterbrook, partner at Moorhouse Consulting, to unpack the results of a major new study into AI readiness — and what it actually takes to drive transformation at scale.

Together, we explore:

• Why organisations are stuck in ‘AI theatre’ while real value goes untapped
• The behavioural and structural barriers to adoption
• What’s behind the disconnect between exec ambition and delivery reality
• Why AI isn’t a tool. It’s a strategy.

🔍 The data is fascinating.

The conversations that followed? Even more so.

We talk readiness (just 7% feel confident). Responsibility. Trust. Fear. Hope. And the kind of leadership required to break the inertia loop.

🎧 If you’re in strategy, consulting, data, digital, or any leadership role navigating AI — this one’s a must-listen.

Because it’s not about the tech.

It’s about what you choose to do with it.

For more insights and to stay up to date with all the latest information from BH&P, visit our website, or follow us on LinkedIn.

BH&P is a B Corporation, certified in September 2023, and on a mission to create meaningful growth for brands with purpose. From scale-up to Enterprise, we're here to help.

Transcript

AI, Inertia and the 7% That Are Ready

Season 4, Episode 4 of the No Bull Ideacast

“What we’ve seen is this sort of popular and public explosion of very simple-to-use, very applicable AI tools. And I think the pace - how quickly that’s gone up the curve and into people’s minds - is what makes it particularly interesting. It’s going to be unknown. It’s going to require us to gird our loins and cope with things we haven’t seen before.”

- James Easterbrook

Becky: Hello and welcome to The No Bull Ideacast. I’m Becky Holland.

Let’s talk about AI. Again.

Because while the headlines are full of hype, most organisations are quietly stuck.

Only 7% of business leaders feel genuinely ready to harness AI. The rest? Not quite sure where to start. Nervous about the risks. Struggling to turn potential into progress. And often focusing more on the tech than the actual impact.

My guest today is James Easterbrook, Partner at Moorhouse Consulting. We’ve been working together on a major piece of research exploring exactly that: the data and AI readiness gap, and what to do about it.

The strategy and insight behind this project was something the team at BH&P helped shape from the ground up, digging into not just what leaders say about AI, but how they feel about it. And what’s really holding them back from meaningful action.

I’m so excited to share what we found out.

We talk about fear, inertia, and invisible blockers. Why AI needs to be more than a tool - it has to be a strategic lens. And along the way, we get into behavioural science, loss aversion, and the cultural shifts that need to happen if AI is going to drive real, positive transformation.

If you’re tired of surface-level AI talk and want to get under the skin of what’s really going on - this episode is for you.

Becky: Good morning James, and welcome to the show.

James: Morning Becky, thanks very much. Really happy to be talking about this incredibly exciting topic.

Becky: Exciting, but a bit complicated - and a bit of a rabbit hole, I think, for a lot of people. But before we get into all of that, can you tell us a little bit about your journey?

James: Sure. I actually started out in advertising. My first job was in France, working as part of my degree for a publishing agency. It was very much focused on the creation of content for marketing purposes - that was the crux of what they were doing.

Then through a couple of hop-skips-and-jumps, I ended up back in the UK, working in more traditional ad agencies. I really enjoyed that - exciting, fast-paced, doing crazy things - but I found that a lot of the clients I was working with would say things like, “I know it’s not what we pay you for, but we’re having a customer strategy day,” or, “We’re reviewing our customer experience - could you join and share your thoughts?”

And I started to realise that I was enjoying that stuff way more than I was just cranking out ads.

So I ended up moving to PwC, and was there for two and a half years. Then I moved - about eight and a half years ago now, to Moorhouse.

Becky: Let’s jump into the research. Obviously, this is something we worked on together, so it’s quite exciting to see how it’s shaped up. But I want to start with the big picture. When we launched this research, we were really curious about why AI wasn’t delivering on its promise inside large organisations.

What do you think surprised you the most once we started to get the data in?

James: I think it’s easy to assume agency when you look at large organisations-or even small to medium-sized ones. It can be easy to think everybody else has got it nailed. That they all understand these things, they’ve got it figured out, and they’re just waiting to see what comes next.

But one of the biggest surprises for me was the sheer degree of fear, inertia, and the lack of grip people had. Everyone knows AI is a huge opportunity. Everyone knows it’s a challenge they have to address. But people are really struggling to know where to start.

The scale of that uncertainty was striking. I think it was 7% who said they felt well prepared to tackle AI. That’s a tiny proportion.

But when you sit with it, the shock fades a bit. Because when you really think about what’s involved-the scale of change, and what people need to get their heads around to unlock real value-it is incredibly complex.

And of course, AI isn’t one thing. There’s not a single, homogeneous ‘AI’ out there. So when people start to unpack it and figure out what it means for their role, their team, their department-that’s when the realisation hits.

Becky: I completely agree.

And I think when you hold a mirror up to organisations, it’s easy for people to talk about the things they’re doing with AI - a system they’ve implemented, how they’re using Copilot, all the various bits and pieces.

But using AI to help with individual tasks is not the same as embracing what AI could do more fundamentally. It’s not the same as understanding how it works in the real world, how it could reshape the business model.

Did the research results match what you’re seeing on the ground in the work you do?

James: Yes, in one sense, because it reinforced the kinds of questions people are asking us every day.

We get a lot of “Where do I begin?”, “What are the use cases?”, “How could this help me?” type questions.

That absolutely came through in the research. People know it’s out there. They know it’s important. But they don’t feel sure where to start.

And we are still very early in the journey.

I know it feels like AI’s been around forever, it’s the topic of every LinkedIn post, every boardroom conversation. But in reality, we’re just getting started.

If you think about industries like finance or insurance - actuarial science, for instance - they’ve been using machine learning and AI for years. It’s already part of the way they assess risk, develop products.

But what’s changed is this public explosion of easy-to-use, accessible tools. That pace, the way AI has shot up the curve and into people’s minds, is what’s made it feel so disruptive.

And that’s reflected in the research.

The questions are no longer just coming from IT teams or data teams. Now, it’s brand, HR, operations. It’s much broader across the organisation.

Becky: Was there a moment during the interviews or when the survey results were being played backthat really made you sit up and go: “Yes. That’s the thing I was looking for”?

James: There was a moment in one of the interviews where someone asked a really good question: “Is AI a tool, or is it fundamental to the strategy of the organisation?”

And for me, that was such a useful distillation of the core challenge.

Is this something that should sit with the tech team, be developed and pushed out to the rest of the business? Or is it something that underpins everything the organisation does?

The answer isn’t the same for everyone. It depends on the business. But that distinction - tool versus strategic foundation - is a moment of clarity.

Because if you treat it just as a tool, that’s going to limit you. You’re not going to take full advantage.

Becky: You mentioned that only 7% of organisations feel truly ready for AI. Which obviously means 93% don’t.

Why do you think that is?

James: I think it’s a number of reasons.

The first, and this came out particularly in the interviews, is a fundamental uncertainty around how to connect AI with value.

People are unsure what success looks like. Not in a vague way, but very specifically: What would a valuable AI deployment actually do for us?

What would it change? What would it free up? What would it unlock?

And then, there’s the scale of coordination that’s required.

To do this well, you need alignment between data, tech, process, people, customer experience, risk…

That’s not a small thing. Especially inside large organisations with complex structures and legacy systems.

Becky: It’s like they’ve bought a Formula 1 car and don’t know how to drive it-let alone how to integrate it into the team.

James: Yes, exactly.

And without that alignment, or without a test-and-learn culture, it’s hard to know where to begin.

There’s also the issue of confidence. People don’t want to be wrong. And AI feels like a high-risk space. If you get it wrong, it’s not just embarrassing - it could be costly, reputationally or financially.

But again, that’s where experimentation becomes so important. Creating safe spaces to test, to learn, to scale what works and discard what doesn’t.

James: I think one of the biggest factors we uncovered is fear. For many people, AI still feels impenetrable. There’s just so much to get your head around. So many unknowns. The tech is moving fast, and if you’re not deeply embedded in it already, it can feel impossible to catch up.

So even if leaders want to explore the potential, they often freeze. It’s that paralysis of not knowing where to begin.

Then there’s investment. We’re in incredibly volatile and economically challenging times. And any kind of big step forward, adopting new tools, running pilots, making system-wide changes costs something. Whether that’s money, headspace, or just time you don’t feel you have.

People are asking: How am I going to find the bandwidth to do this properly? That’s a major blocker. And for me, those two things - fear and lack of resource - are the biggest drivers of inertia.

There’s also the human concern: What does this mean for my job? For my team? That emotional factor is huge. People are worried. And when you combine that uncertainty with the difficulty of building a business case - especially when outcomes are hard to quantify - it’s no wonder organisations are hesitating.

The technology moves so fast that even being out of the loop for a couple of weeks can make a big difference. It’s incredibly difficult to feel like you’re on solid ground.

Becky: So let’s talk about skills. What’s missing?

James: Of course, there are some fundamental hard skills. You need to have your data in good order. You need the ability to clean it, structure it, use it. And yes, technical fluency in the tools is important.

But what we’re really noticing is a gap on the softer side. Resilience, for one - the ability to keep pace with change and not be overwhelmed by it. And also curiosity - being able to look at something and say, Where might this fit in our workflow? How could this help us solve a problem or deliver more value to clients?

At a practical level, people’s first experience of AI often lets them down. They’ll use Copilot or another LLM, type in a question, get a generic or unhelpful answer, and walk away disappointed. That’s not a tech failure - that’s a prompt engineering issue.

Prompt design is a skill. The ability to think clearly about what you’re asking, how you’re asking it, and how to iterate - that makes all the difference. There’s a visible gap between someone who understands that, and someone who doesn’t.

James: There’s also something important around innovation literacy. Too often, people think innovation is someone else’s job. But the truth is, everyone needs to be part of that now. AI doesn’t live in a silo.

This project is a good example. We built an LLM using all the survey responses, interview transcripts, and consultant feedback. Everything lived in one place. It meant we could analyse and pull out patterns incredibly quickly.

And yes, we used prompt engineering ourselves - not just in the research, but in the creative execution. The final campaign route involved a lot of AI input. But that only worked because we combined it with human insight.

That’s the critical point: tech plus human beats tech or human alone. Every time.

You see it with our own consultants. They’re spending more time now on critical thinking, on value-adding work - because the research, the synthesis, the foundations - those are now being accelerated by AI.

James: One other thing we saw in the interviews was polarisation. Some leaders were clearly excited - they saw AI as an adventure, something that could unlock more. But others were dragging their feet. There wasn’t much middle ground.

And I think that comes down to context. Some organisations just have too many basic problems they need to fix before they can think about AI. Others have a solid enough base that they can experiment and build.

In some cases, it’s financial headroom. If you’ve got it, you innovate. If you don’t, you hesitate.

Becky: I think that leads quite nicely into what I wanted to talk about next - what behavioural science tells us about transformation failure.

It reminds me of something we talk about a lot at BH&P - the idea of loss aversion. People fear losing what they’ve already got much more than they value a possible gain. And that came through quite strongly in the research.

What do you think are some of those invisible blockers that hold transformation back?

James: Loss aversion is definitely one of the biggest ones. If people feel like AI is going to “do them out of a living” - if it’s seen as something that’s going to take away their job, not help them do it better - then of course they’re going to resist it. That’s a completely natural human response.

There’s also a big issue around confidence. A lot of people just don’t feel equipped. They don’t believe they have the skills, the knowledge, or the mandate to engage with AI meaningfully. So even if they’re curious, they hold back.

And then you’ve got the fear of getting it wrong. Especially in larger organisations with centralised control structures. We spoke to a number of businesses where regional or business unit teams wanted to experiment, but they didn’t have permission. The head office controlled all AI decisions. Or they were told to “wait” for the official rollout. That sort of top-down grip completely stifles momentum.

In some cases, we heard about organisations outright banning the use of AI tools. Whether it was because of concerns over data security, cyber risks, or compliance - fair enough - but it means people were afraid even to explore what’s possible.

Becky: So it becomes this question of permission - do I have the remit to try this?

James: Exactly. Am I allowed to test this? Do I need sign-off from IT or Legal or Risk?

And interestingly, fear can also work the other way. We spoke to people who said they were exploring AI precisely because they were scared. Scared of being left behind. Scared they’d miss a major wave of change.

I felt it myself. This isn’t a trend that’s going away. It’s something that’s going to fundamentally reshape how we work. And that urgency - when channelled positively - can be a driver. It motivates people to experiment, to play, to get stuck in.

Becky: I’ve seen examples where companies are already building AI expectations into governance. For instance, if you’re putting in a business case asking for headcount, you have to explain why it can’t be done with AI first.

James: Exactly. That’s happening now. And those are the kinds of signals that will shift organisational culture. These might be slightly more advanced organisations, but others will follow in months.

It’s why this research felt important. We wanted to create something actionable. Something that gave people the tools - not just the theory - to start moving.

Becky: And it had a behavioural lens baked in, right?

James: Absolutely. We didn’t want to just present the facts. Everyone presents the facts. Every day there’s a new report about AI, some new tool, some stat.

What we wanted to do was create something practical. We used to joke we were writing the Lonely Planet guide to getting value from AI.

It was about breaking down the problem - eating the elephant, bit by bit. Four types of AI. How to build use cases. A framework for ideation, adoption, and scaling. Tangible examples that people could borrow, test, and adapt.

James: When they are in lockstep with the business and they understand what the business and its customers are trying to achieve - and they’re reacting, and also being proactive about what’s possible and what could change - I think that two-way relationship is where it’s best. For me, success is that we’re able to add AI into that mix and maintain that two-way street: “Here’s what I’m trying to achieve for my customers, can you help me?” and equally, “Here’s a new thing that we know is possible - can this help you?” That, I think, is a critical sort of flow.

James: I think at a different level, for me it’s impossible to build a picture that will stand up to the change we’ll see week by week, day by day, hour by hour in this space. So it’s about identifying areas of advantage that you can drive. Can I make that process quicker? Can I provide a little bit more value for the customer? Can I take a little bit of cost out over here? Can I enhance this team so that it can add different value? That’s the way I think you can determine value - rather than saying, “Here’s a picture of the organisation in 10 years’ time - have we got there or not?” Because I just think it’s too varied, too variable. You’re unlikely to get it right.

Becky: It comes back to something we talked about right at the start - that AI should be there to help you achieve your vision, your mission, your strategy. So actually, measuring success in terms of AI isn’t about whether you’ve got Copilot enabled, or what percentage of your work is done by toolkits. 

The question is: if this is our goal - whether that’s being the most sustainable beer company on the planet, or transforming how people travel across Europe - then are we achieving what we said we’d do in our roadmap? And how have we used AI to help us get there? If it’s not helping, don’t do it. You’ve got to remove that noise from the system.

James: Yeah, definitely - I totally agree. The build on it is being able to look back and say: where did the use of AI not just allow us to enhance what we do or make it cheaper and easier, but help us realise that something completely different could be done? Where there was a new piece of insight about what people want?

Becky: I saw an interesting stat the other day: for a lot of online businesses, particularly in the eCommerce space, their attention through search - their marketing and outreach performance - has gone down significantly. They’re seeing fewer referrals and less traffic. But their sales are up. That’s really interesting, right? It suggests that the morass of inquiries they were getting before through search were unqualified - people weren’t buying. Now, people are using LLMs like ChatGPT. And when they do come through, they’re more likely to be the right customer. They’re more informed. They’re navigating more quickly to what they want.

James: And we’ve got to read that as a good thing - that people are getting more insight that allows them to make better decisions. Whether that’s the supplier or the customer.

Becky: We did a lot of research - and we’ve talked about it at length - but what’s something you’re still chewing on from the research? Is there anything that challenged your assumptions, or that you’d like to explore more?

James: That’s a really good question. As ever, when you go into a piece of research, you have a question and you want an answer - which we got. We understood the barriers. We saw where people were excited. We got a sense of how far through the journey they felt they were. But - as you’d hope - it also raised more questions.

James: For me, one of the areas I’d now like to spend more time on is understanding not just how to optimise customer journeys or improve value at the frontline - but the impact on strategy. Strategic decision-making. That’s a Pandora’s box I’d like to open now, and it definitely came out for me as a key stimulus from the report.

Becky: OK, so final word. What word or phrase would you use to describe where we go next with AI? Just one word.

James: Excitement.

James: And that excitement is tinged with a bit of fear and a bit of optimism. I think that’s a fair summary. It reflects the client conversations we’re having. It’s going to be unknown. It’s going to require us to gird our loins and behave in new ways. But it also brings so much opportunity. So many new ways to do really positive things. So yes - excitement, with a little trepidation, is my word of choice.

Becky: Thank you so much, James. I’ve absolutely loved having you on the show. We will talk again soon - thank you for joining me.

James: Thanks very much, Becky. It’s been fascinating.

Becky: Thank you again, James, for being so open and generous with all the thinking behind this research. Super, super interesting. And we’ve got plenty more coming this season - from nature-based finance to fast-moving consumer brands, from B2B behaviour change to public sector innovation… and yes, there is beer coming.

Becky: Every episode is an exploration of inside-out impact. Don’t forget to subscribe wherever you get your podcasts. Google BH&P. Message me on LinkedIn. You can get transcripts, downloads, behind-the-scenes insights - lots and lots of fantastic content.

Becky: And if you’re working inside a complex organisation and wondering how to move from insight to action - that’s what we do at BH&P. Our Impact Thinking framework helps organisations turn strategy into creative systems that genuinely work.

Becky: Thank you so much for listening - and I’ll see you next time.