For decades, the consulting industry sold two things: access to benchmarked intelligence, and access to bright, relentlessly hardworking talent. Clients paid premium rates to know what their competitors were doing and to borrow the brainpower to figure out how to respond. That model made McKinsey, it made Deloitte, and it made the Big Four into institutions.
And then, almost without warning, an AI language model could do the first part for free. According to Gartner, by 2026 more than 80% of enterprises will have used generative AI APIs or deployed AI-enabled applications, a shift that has arrived faster than most organisations had planned for. The result for consulting is equally dramatic: the barrier to strategic insight has collapsed. Clients can now interrogate a market, benchmark themselves against industry standards, and generate a credible transformation roadmap before their first scoping call with a consultant.
The question the industry must confront honestly is: what, exactly, are we still being paid for? The answer, I’d argue, has always been the same. We just never had to make the case for it until now.
When the client starts marking your homework
Something interesting has started happening in client engagements. Clients are using AI to fact-check their consultants in real time. This is not entirely a bad thing. In a recent meeting, a client was running their own AI queries to cross-reference the recommendations we were making and was getting different answers. The problem, when we dug into it, was that they were prompting for job architecture outputs when the real problem they were solving was operating model design. Same area, but a fundamentally different question.
Once we helped them reframe the prompt, they got the results they’d been expecting from us all along. And in doing so, we earned something more valuable than credibility on a single deliverable: we earned trust in our judgment.
This is the new frontier of consulting competence. It is not enough to produce accurate insight. Consultants must now actively help clients understand which questions to ask of their own AI tools and why the nuance between two seemingly similar questions can yield completely different outcomes.
Strategy was never the hard part
Here is an uncomfortable truth: strategy has never been the hard part. It only felt that way because the data required to formulate it was expensive and slow to acquire. I use a simple metaphor with clients. A dietitian can tell you not to eat the biscuit. The insight is sound, and the logic is flawless. AI can now produce that insight at scale, instantaneously, for virtually any challenge your organisation faces. But the ability to not eat the biscuit, day after day, when the pressure is on, and priorities are competing, and the team is exhausted, that is an execution problem no language model has solved.
What clients are increasingly asking for is not the strategy deck. They expect that as a baseline. What they are asking for is someone to sit alongside them through execution, call out when they’ve dropped the ball, diagnose why they’re not doing what they committed to do, and hold the strategic thread steady when global macroeconomic chaos makes it tempting to abandon course.
The consulting firms still operating on a deliver-the-deck-and-step-away model are, frankly, giving their clients half a service.
Where execution breaks down
Ask any senior leader why their transformation programme didn’t deliver the expected value, and you will rarely hear them say the strategy was wrong. More often than not, execution broke down at one of three predictable failure points.
The first is a lack of accountability. When strategic initiatives are framed as collective responsibilities, “we need to do X”, they tend not to get done. Ownership must be specific, named, dated, and budgeted. Without that, the urgent will always displace the important, and organisations will continue firefighting their way through quarters while their strategic objectives gather dust.
The second is the disconnection of initiative from outcome. Most organisations can tell you what projects are underway. Far fewer can articulate, with precision, how each of those projects maps onto the three fundamental strategic levers available to them: revenue growth, operational efficiency, and stakeholder engagement. If your team cannot explain why their initiative matters to at least one of those three objectives, it won’t get done.
The third is the underestimation of the behavioural dimension. Technology implementations stall not because the system is wrong, but because the people operating it are afraid of what it means for their role, their status, their sense of competence.
What ‘Scars on Your Back’ means
At Change Logic, we often talk about having scars on our backs. It is worth explaining what that means and why it matters more now than it did five years ago.
There is no AI tool, no consulting framework, and no university curriculum that can fully prepare you for the experience of watching a transformation programme go sideways in real time. Or discovering that a critical data set is unreliable only after you’ve built your operating model around it, or navigating the moment when a senior sponsor loses confidence. These experiences leave marks and knowledge that cannot be acquired any other way.
The value of that experience is not that it makes you pessimistic about what can go wrong. It is what makes you hypervigilant, able to read the early signals of execution risk, to name what is happening before the client can fully see it, and to prepare them for what is coming rather than simply reacting to it after the fact.
What an execution-first model requires
An execution-first model is not traditional consulting with more project management bolted on. It means being able to trace every initiative back to a concrete strategic objective, with a start date, an end date, and a named owner. It means staying in the engagement long enough to see whether the change stuck. Employees and staff at our clients are fluid and moving all the time. Change Logic stays committed to the change process rather than the individual awareness, to help clients make this part of their institutional knowledge and they way they do things. And it means having experience across enough functions and industries to hold the connective logic of a complex system together when things get hard.
The disruption AI has brought to consulting is real, and firms that underestimate it will pay a significant price. But disruption is not the same as obsolescence. What the market is asking for, clearly and persistently, is consultants who have done the work, understand the obstacles, and are willing to stay in the room long enough to see the change through.
- Michaela Voller, Executive for People Solutions Division at Change Logic
