TL;DR

The consulting model that built the industry's largest firms, scaled delivery teams, multi-year implementations, sustained client dependency, was a deviation, not a destination. AI is now correcting it, commoditizing the analysis layer that underwrote the model and exposing firms with no clear specialization. The firms built correctly for the original model are not fighting the disruption. They are watching the market finally arrive.

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When Olly Purnell and four colleagues set up Q5 in 2009, the business model they chose was, by the standards of the industry they were leaving, commercially eccentric at best.They would not pursue long-duration client relationships. They would not deploy large teams across multi-year implementations. They would not build the kind of embedded account dependency that most consulting firms, at the time, were actively treating as a revenue strategy.

Instead, they would work for 8–12 weeks on specific organizational problems, charge a fixed fee for a fixed scope, and then leave. They would remain available to be called back. They would not arrange to be needed.

"It's a business model," Olly says now, with the mild amusement of someone who has spent sixteen years watching an unconventional thesis prove itself, "which would be laughed out of the Dragon's Den TV show."

He is not wrong that it would have been. Dragon's Den logic prizes recurring revenue, long-term contracts, and the kind of predictable pipeline that comes from clients who cannot easily walk away. Q5 was built on the opposite assumption: that the best clients are the ones who choose to return, not the ones who have no real alternative.

Olly Purnell is Managing Partner and co-founder of Q5, a specialist organizational performance consultancy now operating across eight offices worldwide with over 300 employees and roughly 160 clients a year. He spent the first eight years of his career at what was then Andersen Consulting, present for its transformation into Accenture, its IPO, and its separation from Arthur Andersen, before leaving to build something deliberately smaller in ambition and more precise in focus. He describes Q5 as functioning less like a consulting firm in the conventional sense and more like an architect's practice. Clients arrive with specific structural problems. The firm designs the solution. The work is bounded, expert, and complete. The architect does not stay to run the building.

What Olly built in 2009 on that premise grew at over 20 percent last year.

The firms that would have laughed at his Dragon's Den pitch are not all growing at 20 percent. A number of them, the large generalists, the scaled delivery machines, the firms whose commercial model has depended on deploying significant headcount across long-duration client engagements, are navigating a considerably more difficult conversation. Not because they have made poor decisions or hired the wrong people, but because the economic foundations of the model itself are being eroded from below.

AI has arrived in the consulting market and it has not arrived neutrally. It has landed directly on the layer of work, analysis, benchmarking, research synthesis, reporting, that armies of junior consultants have been deployed to produce for decades. That work is becoming faster, cheaper, and more accessible to everyone simultaneously. For firms that built their commercial model around the human effort required to produce it, that is not a technology upgrade. It is a structural challenge to a revenue model that was never as defensible as it appeared.

Olly does not describe what is happening as disruption in the conventional sense, the sudden arrival of something unprecedented forcing rapid adaptation. He describes it, with the perspective of someone who has been watching the industry for 31 years, as a correction.

"The model of consulting has changed," he says. "And will continue to change."What follows is his account of what it is changing toward, and why the direction it is heading looks less like the future and more like the past.

How Consulting Lost Its Way, But Is Finding It Again.

When Olly Purnell and four colleagues set up Q5 in 2009, the business model they chose was, by the standards of the industry they were leaving, commercially eccentric at best.They would not pursue long-duration client relationships. They would not deploy large teams across multi-year implementations. They would not build the kind of embedded account dependency that most consulting firms, at the time, were actively treating as a revenue strategy. Instead, they would work for eight to twelve weeks on specific organizational problems, charge a fixed fee for a fixed scope, and then leave. They would remain available to be called back. They would not arrange to be needed.

"It's a business model," Olly says now, with the mild amusement of someone who has spent sixteen years watching an unconventional thesis prove itself, "which would be laughed out of the Dragon's Den TV show."

He is not wrong that it would have been. Dragon's Den logic prizes recurring revenue, long-term contracts, and the kind of predictable pipeline that comes from clients who cannot easily walk away. Q5 was built on the opposite assumption: that the best clients are the ones who choose to return, not the ones who have no real alternative.

Olly Purnell is Managing Partner and co-founder of Q5, a specialist organisational performance consultancy now operating across eight offices worldwide with over 300 employees and roughly 160 clients a year. He spent the first eight years of his career at what was then Andersen Consulting, present for its transformation into Accenture, its IPO, and its separation from Arthur Andersen, before leaving to build something deliberately smaller in ambition and more precise in focus. He describes Q5 as functioning less like a consulting firm in the conventional sense and more like an architect's practice. Clients arrive with specific structural problems. The firm designs the solution. The work is bounded, expert, and complete. The architect does not stay to run the building

What Olly built in 2009 on that premise grew at over 20 percent last year.

The firms that would have laughed at his Dragon's Den pitch are not all growing at 20 percent. A number of them, the large generalists, the scaled delivery machines, the firms whose commercial model has depended on deploying significant headcount across long-duration client engagements, are navigating a considerably more difficult conversation. Not because they have made poor decisions or hired the wrong people, but because the economic foundations of the model itself are being eroded from below.

AI has arrived in the consulting market and it has not arrived neutrally. It has landed directly on the layer of work, analysis, benchmarking, research synthesis, reporting, that armies of junior consultants have been deployed to produce for decades. That work is becoming faster, cheaper, and more accessible to everyone simultaneously. For firms that built their commercial model around the human effort required to produce it, that is not a technology upgrade. It is a structural challenge to a revenue model that was never as defensible as it appeared.

Olly does not describe what is happening as disruption in the conventional sense, the sudden arrival of something unprecedented forcing rapid adaptation. He describes it, with the perspective of someone who has been watching the industry for 31 years, as a correction.

"The model of consulting has changed," he says. "And will continue to change."

What follows is his account of what it is changing toward, and why the direction it is heading looks less like the future and more like the past.

How AI Found the Weakest Part of the Consulting Model

The disruption Olly describes is not arriving evenly across consulting. It is landing first, and hardest, on a specific layer: the layer the scaled delivery model was built around.

AI has made research faster. It has made benchmarking cheaper. It has made the production of structured analysis, synthesized market data, and professionally formatted recommendations more accessible than at any point in the industry's history. The output that once required a team of junior analysts working at sustained intensity can now be approximated in a fraction of the time, at a fraction of the cost, by anyone with access to the tools. And the tools are accessible to everyone.

"AI has enabled the analysis, benchmarking, reporting to be done almost instantly," Olly says, "and to be done to a high degree of sophistication, depth and breadth."

For firms that have spent thirty years building their junior layers around precisely this work, and building their commercial model around the human effort required to produce it, that is not a feature of the new landscape. It is a direct erosion of the economic foundation. The revenue that came from deploying significant headcount to produce analytical output is not disappearing slowly. It is going rapidly. Olly does not qualify this.

"Unfortunately for firms that have been reliant on having armies of young people doing that type of work," he says, "those opportunities are now diminishing and going very rapidly. AI has commoditised that."

The word commoditised is precise and worth staying with. Commoditisation does not mean the work ceases to exist or ceases to have value. It means the work can no longer command the premium it once could, because the barrier to producing it, the human time, effort, and access that once made it genuinely scarce, has collapsed. When every firm can produce broadly similar analytical output at broadly similar speed using broadly similar tools, the output stops being a source of differentiation. It becomes a baseline. And baselines are not where consulting margins live.

This would be a significant enough problem on its own. What makes it more acute is that it arrives simultaneously with a second pressure, one that existed before AI but has been made suddenly visible by it.

Olly has been using Claude and ChatGPT to audit the positioning of consulting firms across the market. He is not doing this to gather competitive intelligence in the conventional sense. He is doing it because AI offers a kind of neutral, comprehensive audit that professional courtesy and industry familiarity tend to obscure. What he has found is striking. Firm after firm, not small obscure practices, but firms he and his peers would recognise immediately, presents a portfolio of services so broad and so undifferentiated that no clear answer emerges to the question of what, precisely, the firm stands for.

"I'm surprised at how many firms that you and I, and I'm not going to name them now, don't really stand for anything other than just a generalist portfolio of services," he says.

A generalist portfolio of services was a defensible strategic position when the value of consulting lay partly in breadth, in the ability to deploy expertise across many domains, to offer clients a single relationship covering multiple needs, to grow revenue through the expansion of an account across service lines. That logic has not completely dissolved. But its weakness has been exposed in a specific way by AI. When the analytical output underpinning a broad portfolio becomes commoditised, the breadth of the portfolio stops being an asset and starts being a liability, because the firm is now a generalist in a market that is beginning to ask what each firm specifically knows.

The firms Olly sees thriving, and Q5's own trajectory is the evidence he cites most directly, are not immune to AI's disruption. They are simply disrupted in a different place.

AI improves the speed and quality of their delivery. It gives them tools to serve clients more precisely and more efficiently. It does not remove the foundation of their value, because that foundation was never the analytical output AI is now replacing. It was the expertise, the judgment, and the organizational knowledge accumulated through years of working on the same specific class of problem.

"If you're a specialist firm," he says, "I think now is quite an exciting time to be focused on that niche that you're expert in."

The contrast between that sentence and his assessment of the generalist position is not accidental. It reflects a specific view about which parts of the consulting value chain AI is strengthening and which it is undermining, a view that, if correct, means the strategic decisions facing consulting leaders right now are considerably more fundamental than a productivity conversation about AI tooling would suggest.The question is not how to use AI to do the current model faster. It is whether the current model is worth doing at all.

The Future of Consulting Looks Like Its Past

There is a thought experiment Olly returns to when he wants to make his argument as plainly as possible, and it begins not in the present but roughly a century in the past."When McKinsey set up in the 1920s," he says, "I think it was James McKinsey who set the company up around 1926, when they set that business up, I imagine that an organisation would go to James McKinsey and say, 'We've got this problem,' and he and his team would address it in a matter of weeks, probably."

He pauses. "I cannot believe that a hundred years ago companies were going to James McKinsey and saying, 'We want to spend three or four years with your team in situ, sitting alongside ours.'"

The conceit is deliberately unprovable. Olly acknowledges as much. But it contains a hypothesis that sits at the centre of everything he has built at Q5 and everything he believes is now happening across the industry. The long-duration, high-headcount, dependency-sustaining model of consulting is not the original model. It is a deviation from it, one that developed gradually as scaled delivery became profitable, as clients became accustomed to having external teams embedded in their operations, and as the commercial logic of sustaining those relationships grew more compelling than the intellectual logic of completing them.

What AI is now doing, Olly argues, is not inventing a new model for consulting. It is correcting the deviation. Pushing the industry back toward what it was designed to be."I think where we're moving to probably goes back to what the consulting world was a hundred years ago," he says. "Where there's a very specific question. It could be a strategic question that they want some expert advice on. Or it could be one of process or system change that they want some very specific expert advice in. And I think the model of being specialist and being able to provide that advice, and that tooling, and that capability, that probably wouldn't take more than two or three months from start to finish."

The architect's practice is where this becomes concrete. Q5 has operated on this model since 2009, not by accident, but because Olly and his co-founders believed that the version of consulting they were leaving was commercially convenient but professionally incoherent. An architect brought in to design a building does not remain on retainer for the lifetime of the structure. The value they bring is the design: the structural blueprint, the precise specification, the expert judgment about what will stand and what will not. Once the design is complete and the project successfully delivered, the engagement is complete. If the client has a new project, they return. If not, they do not. The relationship continues on the basis of demonstrated expertise rather than embedded dependency.Olly is willing to extend the analogy further, and does so with the cheerful thoroughness of someone who has been making this case for sixteen years.

"If you're having your loft converted, and an architect comes to you and says, 'Just pay me by the hour,'" he says, "you'd be thinking, 'All I want is the structural blueprint. I just want the blueprint. And maybe if you could do the weightings for the reinforced steel joists.' I'm really flogging this analogy here, but so for the work that we do, if a company is coming to us and saying, 'We need to drive out some efficiencies,' we know the effort that is required to do it. We know the tooling that we've got. We know exactly what we're doing and how we're doing it, in the same way that an architect knows how to convert a loft or do a kitchen extension."

The commercial structure that follows from this logic is Q5's mantra, stated simply enough that it carries the weight of a principle rather than a tagline: fixed fee for a fixed scope of work. The client knows what they are buying. The firm knows what it is delivering. The price reflects the outcome, not the hours. If the scope changes, because the client acquires another business mid-engagement, or because the problem turns out to be materially larger than either party initially understood, the fee is renegotiated. But the transaction is, at its core, an exchange of defined expertise for a defined result. Not an open-ended arrangement that benefits commercially from remaining open-ended.This model, Olly is quick to acknowledge, is not for every firm or every type of work.

There are categories of consulting engagement, large-scale technology implementations, complex regulatory programs, multi-year organizational transformations, that genuinely require sustained external presence. He does not argue otherwise. What he argues is that the proportion of consulting work that genuinely required it was always smaller than the proportion of consulting revenue organized around it. The rest was dependency by habit, not dependency by necessity. And the difference between those two things is becoming impossible to ignore.

"I think the model will go back to what it should be," he says, "which is expert specialist advisory, that will be called in on a project-by-project basis."

The word should carries more weight in that sentence than it might initially appear. Olly is not only describing an economic adjustment forced by AI. He is describing a return to intellectual integrity, to a version of consulting in which the value delivered is expert judgment on a specific problem, not the perpetuation of a client relationship that has outlasted the original reason for its existence. The correction is commercial. It is also, in his telling, moral.

For the consulting leaders now watching the scaled delivery model come under pressure, that framing offers something the productivity conversation about AI does not: a direction that is not simply reactive, but oriented. The question is not only what to cut or what to automate. It is what consulting was actually for, and whether the firm being built today is organised around that answer.

Why Specialism Has to Be Built, Not Claimed.

Agreeing that specialism is the right strategic direction is considerably easier than achieving it.

Most consulting leaders, if asked directly, would describe their firm as having a distinct area of expertise. Most firm websites assert a particular focus. Most partner conversations include some version of the claim that the firm does not try to be all things to all people. And yet, when Olly uses AI to audit what those firms actually communicate, the language of their positioning, the breadth of their service portfolios, the specificity of the problems they claim to solve, the picture is markedly different from the one the firms would draw of themselves.

"I've been using ChatGPT and Claude recently to look at some of the big four firms, to look at some boutique firms, to get the perspective of what they actually stand for," he says. "And I'm surprised at how many are generalists. I'm surprised at how many firms don't really stand for anything other than just a generalist portfolio of services."

The AI audit is instructive precisely because it removes the benefit of personal familiarity. A consulting leader who has been in the market for thirty years carries accumulated impressions of every significant firm, relationships, reputations, specific engagements. That familiarity can obscure a harder question: stripped of everything you personally know about this firm, what does it actually communicate about what it is uniquely equipped to do? If the answer, reviewed neutrally, is a list of services available from most of its competitors, the firm's positioning problem is more serious than its leadership may have acknowledged.

Olly does not suggest that brand alone solves this. The firms with sufficiently powerful global reputations, McKinsey being the clearest example, can transcend some of the pressure bearing down on the generalist model because the brand itself carries a form of differentiation that competitors cannot quickly replicate. But for the vast majority of firms operating below that threshold of global recognition, brand reputation is downstream of what the firm actually stands for. And standing for something requires a decision that most firms have been deferring.

"You have to be really well known and famous for a particular type of service and offering right now," he says. "And if you haven't got that in your strap line, if you haven't got that on your website, I think you're going to struggle."

For Q5, the decision was made at founding and has been maintained since. The firm focuses on organisational performance and organisational health, the structural and human foundations that determine whether a business can actually execute its strategy. Operating models, spans and layers, workflows, the design of functions and teams during periods of significant change. It is not a narrow niche. It is a precisely defined one. And the precision matters, because it tells clients specifically what they are buying and tells the market specifically what Q5 is worth calling.

Building and sustaining that kind of recognized authority requires something beyond good work on individual engagements. It requires the consistent communication of a specific point of view, through the people in the firm, through the language used to describe the work, through the reputation that accumulates when the same firm keeps showing up at the same category of problem and keeps getting it right. Olly describes his ambition for Q5's senior team in terms that sit somewhere between intellectual responsibility and commercial discipline: he wants all of them to consider themselves organisational performance influencers, people who are building the resonance of the Q5 brand not just by delivering excellent work for clients, but by articulating what that work means in the broader market.

The growth model that follows from this is less straightforward than account expansion, but more durable. Influence, reach, and contribution, the three words Olly returns to repeatedly when describing how Q5 intends to grow. Influence means being recognized as the leading voice in the specific domain the firm occupies. Reach means extending that recognition into new geographies and new client sectors. Contribution means converting that recognition into profitable, high-quality engagements that deepen the firm's expertise while sustaining its commercial momentum.

"We have to become more famous," he says. And then, with characteristic frankness about the competitive implication: "If there are leaders of generalist firms that think, 'We're going to win and remain all things to all people,' then I'd be fascinated to know how."

That challenge is not rhetorical. It is an invitation to the strategic conversation most generalist firms have been avoiding, the one that requires choosing, definitively, what the firm is genuinely expert in, and accepting that the answer excludes a significant portion of the work it currently pursues.

The firms that make that choice deliberately will build something defensible. The ones that continue to defer it, hoping that breadth of capability offsets the absence of a clear position, are making the bet that the market will not force the question.The market, increasingly, is forcing it.

The Future of Expertise Still Needs Young Talent

The question of talent arrives differently once the value of junior consulting work is no longer assumed.

For decades, the argument for bringing young people into consulting was partly developmental and partly economic. They learned by doing the research, building the analysis, preparing the decks, sitting inside the machinery of larger engagements until they began to understand how organizations moved. The work trained them. It also monetised them. If AI now compresses or removes a large portion of that analytical layer, the temptation for some firms is obvious: hire fewer juniors, keep the senior expertise, and let technology absorb the work that used to justify the bottom of the pyramid.

Olly’s reaction to that logic is unusually blunt.

“We truly believe in investing in future talent,” he says. “I find it incredibly irksome and irritating to hear business leaders saying they’re not going to invest in young talent.”

The strength of the response is not sentimental. It sits directly inside his broader argument about the future of consulting. If the industry is moving back toward expert specialist advisory, then firms still need a way to create future experts. They cannot simply preserve the senior layer and assume the next generation of judgment will appear fully formed. AI may reduce the value of some entry-level tasks, but it does not remove the need for people to learn how work happens, how clients think, how ambiguity feels, and how advice earns trust inside a room.

At Q5, that belief has taken a form that is more deliberate than a graduate scheme. The firm has been running a Youth Panel for nine years, bringing in 16- to 18-year-olds for paid work across the year rather than a short burst of work experience. It started before generative AI became a mainstream business issue, but the logic has become sharper since. These are not symbolic placements. They apply, answer questions about why they are interested in business and consulting, and are selected into a program that Olly describes with evident seriousness.

“In our business, our Youth Panel, we’ve had hundreds of 16- to 18-year-olds come into our business,” he says. “We had 987 people apply for this year’s Youth Panel, which we can only take 15 people on.”

The numbers matter because they change the texture of the initiative. This is not a charitable gesture at the edge of the firm. It is a way of exposing the organization to people whose experience of technology, media, retail, work, and consumption is already different from that of the senior team. Olly talks about the possibility of an advisory board made up not of “the great and the good,” but of people in their twenties who have grown up with different tools, different habits, and a different sense of how life is organized around digital systems.

That inversion is important. Traditional advisory boards tend to confer seniority back onto the business. Q5’s logic points the other way: the people closest to emerging patterns may not yet have the authority to name them, but they may understand them earlier than the people who do.

This is where the Youth Panel connects back to specialism rather than drifting into culture. A specialist firm cannot afford to become expert only in yesterday’s version of its field. Its authority depends on accumulated judgment, but also on freshness of perception. Senior consultants may understand how deals are cut, how leaders behave under pressure, and what makes an operating model fail in practice. Younger people may understand, with less effort and less translation, how AI tools are actually being used, how digital behaviour is changing, and what will feel natural to the workforce that clients are trying to understand.

Olly describes this as a genuinely multi-generational model.

“There’s a lot that firms that want to succeed in the future will need to have,” he says, “which is this sort of multi-generational understanding of how people at different stages of their careers, at different stages of their professional arc, are using AI and doing their work.”

The point is not that youth replaces experience. It is that specialist judgment becomes stronger when experience is forced into contact with new forms of fluency. The senior person knows how organizations absorb change. The younger person may know, instinctively, which tools are already changing the way work is done. Neither form of intelligence is sufficient on its own. Together, they create a firm that can advise on the future without becoming detached from it.

Q5 has extended the same logic into its Futures Taskforce, a paid program for university students who work on business questions set by clients. Again, the structure is selective and intentional. The firm looks for strong academic capability, but Olly is careful to emphasize breadth of background as well as quality. The participants work on real conundrums, not abstract exercises. The firm gets access to a different kind of thinking; the students get a serious encounter with the kind of problems consulting exists to solve.

That exchange sits uneasily with the emerging argument that consulting no longer needs a “bottom tier” of talent. Olly does not dispute that skills are changing. Q5 now looks for people who can handle both the artistic and the analytical sides of the work, people comfortable with words, pitching, ambiguity, numbers, and data. Everyone joining the firm is expected to spend time in the analytics hub. The future consultant, in his account, is more ambidextrous than the traditional archetype allowed.

But that only strengthens the case for investing early. If the next generation needs to combine data literacy with human judgment, AI fluency with client empathy, and analytical sharpness with the ability to tell a coherent story, the development curve does not get shorter. It becomes more complex.

Near the end of the conversation, when Sarah asks what will separate winners from losers, Olly returns to three things: embracing AI, choosing what to specialize in, and continuing to invest in talent for tomorrow. The third sits alongside the first two, not beneath them. A firm cannot credibly claim to be building for the future while withdrawing from the people who will have to inhabit it.

“I wouldn’t have got a job at Q5,” he says, reflecting on the quality of the young people coming through the Youth Panel, Futures Taskforce, internships, and research analyst roles. “The quality of the thinking, the seriousness that they bring into the business, they’re a real credit to their generation.”

For an industry anxious about what AI removes, this is a useful complication. The junior layer may no longer be valuable for the same reasons it once was. It may not be commercially defensible to build leverage around armies of analysts producing work that tools can now accelerate or approximate. But the conclusion does not have to be that young talent matters less. It may be that the reason for investing in it has changed.

The future specialist firm will not need juniors because it requires more hands to produce more analysis. It will need them because expertise has to be renewed from somewhere. And in a market where the conditions of work are changing faster than senior experience alone can absorb, the people closest to the new tools may not be peripheral to advisory value. They may be one of the ways it stays alive.

The Firms That Survive Know What They Stand For

The same question that now sits beneath AI once sat beneath Covid: what do you do when people want certainty and none is available?

Olly remembers the early months of 2020 in precisely those terms. Clients were pulling work. Force majeure letters were arriving. Around 40 people were suddenly on the bench. Other consulting firms were moving quickly to reduce headcount. No one knew whether the disruption would last weeks, months, or years. The normal leadership currency, confidence, forecasts, the appearance of control, had very little to trade on.“We couldn’t give certainty,” he says. “But we agreed that we had to give clarity as to the steps we were going to follow.”

That distinction mattered. Certainty would have been false. Clarity was still available. Q5 could not tell its people when the market would return, or how long clients would continue to pause work, or whether the firm’s revenue would recover quickly enough. But it could decide what it would protect first. The answer was the psychological safety of its employees, and the decision that followed was deliberately conservative in one sense and deeply entrepreneurial in another: buy time.

The senior people in the business agreed not to take income for six months. Initially, Olly says, they had talked about twelve. They were “long in tooth enough,” as he puts it, to survive without monthly income for some time. Then the firm went to its employees and asked whether they would be willing to take a temporary reduction in salary, with the promise that if the business came through the next six to nine months, they would be reimbursed.

The response stayed with him.

“I’m not joking when I say this,” he says. “We had 99% uptake on that. We’re talking about one or two people who, for various perfectly logical reasons, couldn’t do that. I was absolutely gobsmacked at the willingness of people to do that.”

What makes the episode relevant is not that it produces a neat moral about culture. It is that the firm’s behaviour under pressure was consistent with the model Olly describes elsewhere. Q5 did not treat its people as disposable capacity to be released when utilization fell. It treated them as the accumulated capability on which the business depended. That distinction is easy to state in stable markets and much harder to sustain when revenue is suddenly uncertain.

The commercial outcome, in retrospect, was striking. By June and July 2020, clients began returning to projects they had previously deferred. With holidays, offices, travel, and much of public life suspended, work became one of the few meaningful things companies could still do. Q5 was inundated. Olly recalls revenues moving from roughly £21 million in 2020 to around £32 million or £33 million by the end of the first Covid year, and then to about £48 million or £49 million the year after.

He is careful not to overclaim the uniqueness of that spike. Many consulting firms experienced versions of it. What he takes from the period is not a victory story, but the durability created by the way the firm had behaved before the rebound arrived.

“At that time it was giving clarity, giving a story as to what we’re going to do that really, in the long term, paid dividends,” he says, “because it created that cultural cohesiveness.”

The phrase “giving a story” is easy to misunderstand. It does not mean narrative management in the cosmetic sense. It means giving people a coherent account of what the business is doing, what it is protecting, and how it is making decisions when the facts remain incomplete. In the absence of certainty, people listen more carefully to the logic of the choices being made. The story either holds or it does not.

That is why the Covid episode belongs inside the argument about AI and the future of consulting. The parallel is not exact, but the leadership condition is familiar. AI is creating another environment in which people are asking for certainty that leaders cannot honestly provide. What will happen to junior roles? Which tasks will disappear? Which services will remain valuable? What will the firm look like in three years? Which skills will compound, and which will quietly lose relevance?

No serious leader can answer all of that cleanly. But the absence of certainty does not remove the obligation to be clear.

For Olly, clarity begins with the same fundamentals that run through the rest of his argument: know what the firm is for, know what capability it depends on, and protect the human system that allows that capability to keep renewing itself. The model cannot be purely economic, because the value of the specialist firm is not held only in its contracts or its tools. It sits in judgment, trust, confidence, cultural memory, and the willingness of people to move together when the market changes shape.

Covid revealed that at speed. AI is revealing it more slowly, but perhaps more permanently.

The consulting firms that find this uncomfortable are not necessarily badly run. Many were built rationally for a market that rewarded scale, breadth, leverage, and long-duration delivery. They grew by supplying capacity clients needed and by institutionalizing the kind of dependency clients were often willing to buy. For a long time, that looked like the natural evolution of the industry.

Olly’s argument is that it was not the destination. It was the detour.

AI is now making that detour harder to sustain. It is not removing the need for consulting. It is removing some of the economic cover that allowed firms to confuse delivery volume with advisory value, breadth with differentiation, and analytical production with expertise. What remains is not smaller in ambition, but more demanding in character: the ability to be called for a specific reason, to bring judgment that cannot be easily replicated, to price around defined value, and to leave the client stronger rather than more dependent.

That is why Q5’s model, once commercially eccentric enough to be laughed out of Dragon’s Den, now reads less like an anomaly and more like an early signal. Fixed scope. Specialist advisory. Multi-generational talent. A firm built to be chosen again, not needed indefinitely.

Near the end of the conversation, Olly is careful not to turn Q5’s experience into a universal formula. Other firms may need to respond differently. Some categories of work will still require scale. Some large firms will adapt with seriousness and speed. But his challenge to the generalist model remains deliberately unresolved.

“If there are leaders of generalist firms that think, ‘We’re going to win and remain all things to all people,’ then I’d be fascinated to know how.”

It is a fair place to leave the argument, because it does not pretend the future of consulting is settled. It only makes the burden of proof visible. The firms built on scale now have to explain why scale remains defensible when the work beneath it is being commoditized. The firms built on breadth have to explain what they are famous for when clients can see through generic portfolios more easily than before. And the firms built on expertise have to prove that their specialism is real enough, deep enough, and alive enough to matter.

The industry is not being pushed into something entirely new. It is being pulled back toward an older question, one that may now matter more than it has in decades.When the manpower advantage fades, what is the firm truly worth calling for?

Practical Takeaways: Building Advisory Value When Manpower Stops Being the Advantage

AI is not simply making consulting faster. In Olly Purnell’s view, it is exposing which parts of the consulting model were truly advisory and which depended on scaled delivery, client dependency, and junior analytical labor. For consulting leaders, the practical question is no longer how to protect the old leverage model. It is how to build a firm that clients call for a specific reason, trust for expert judgment, and do not need indefinitely.

1. What is the core consulting model shift leaders need to understand?

The shift is from scaled delivery to specialist advisory. Olly argues that consulting is moving back toward bounded, expert problem-solving rather than long-duration embeds built around client dependency. The leadership rule is clear: if the firm is valuable mainly because clients cannot operate without its continued presence, the model is exposed. If clients return because the firm brings precise judgment to specific problems, the model is more defensible.

2. Why does AI challenge scaled delivery more than specialist advisory?

AI attacks the work that supported much of the scaled delivery model: research, benchmarking, synthesis, reporting, and structured analysis. Olly describes this layer as rapidly commoditized, which means firms can no longer rely on large junior teams to justify premium fees for analytical output. The leverage implication is sharp: when tools can approximate the analysis, margin must come from judgment, specialization, and client trust, not from human effort alone.

3. What early signal shows that a consulting firm’s positioning is becoming vulnerable?

A vulnerable firm struggles to say what it is specifically known for. Olly points to consulting firms whose websites and service portfolios read as broad, generalist, and hard to distinguish. The early warning signal is not weak capability; it is unclear market meaning. If a neutral buyer cannot identify what the firm is famous for, the firm risks competing on availability, breadth, and price rather than differentiated expertise.

4. Which roles or functions are most exposed by the shift away from manpower-based leverage?

The most exposed roles are those tied to analytical production, scaled program delivery, and partner economics built on large teams. Olly does not dismiss the quality of those people, but he distinguishes deliverers from advisors. The organizational consequence is significant: partners must rethink leverage, junior talent must develop broader skills, and client teams should expect less value from external capacity alone. The premium shifts toward people who can combine analysis with judgment.

5. What risks emerge when firms continue to build revenue around client dependency?

Client dependency can look attractive because it creates recurring revenue, but it weakens both sides. Olly argues that having consultants “on tap” for years is unhealthy when it turns external support into part of the client’s operating model. The risk is strategic laziness: clients fail to build internal capability, while firms confuse duration with value. If revenue depends on staying embedded, leaders should question whether the work is still advisory.

6. What should clients now expect from consulting relationships?

Clients should expect clearer scope, sharper expertise, and less tolerance for open-ended dependency. Olly compares the future model to an architect’s practice: the advisor designs, solves, delivers, and leaves. The decision rule for buyers is practical: if the problem can be defined, the scope should be defined too. If a firm cannot explain what it will deliver, why it is qualified, and when the work ends, the client carries avoidable risk.

7. How should delivery models change when analysis becomes commoditized?

Delivery models should move toward fixed scope, fixed fee, defined expertise, and shorter problem-led engagements where possible. Olly presents Q5’s model as one built around specific organizational problems rather than open-ended account expansion. The operating implication is that firms need better scoping discipline and stronger confidence in their own methods. If the scope changes materially, renegotiate it; do not let ambiguity become the commercial engine.

8. What strategic options do generalist consulting firms still have?

Generalist firms need to choose how they will remain defensible: build a truly famous brand, specialize more clearly, or prove that scale still creates value clients cannot get elsewhere. Olly is skeptical that most firms can win by remaining all things to all people. The trade-off is unavoidable. Specialization excludes some opportunities, but lack of specialization exposes the firm to commoditization, especially when AI makes broad analytical output easier to replicate.

9. What leadership decision separates firms adapting to AI from firms only reacting to it?

The key leadership decision is whether to automate the existing model or redesign the firm around what remains valuable after automation. Olly frames AI as a correction, not just a tool. If leaders use AI only to make current delivery faster, they may preserve a model whose economics are already weakening. If they use it to sharpen specialization, judgment, and client outcomes, AI becomes leverage rather than erosion.

10. What metrics should leaders use to judge whether their advisory model is becoming more defensible?

Leaders should track whether clients return by choice, whether the firm is known for a specific problem, whether engagements are bounded, and whether talent development renews expertise. Olly points to Q5’s growth, fixed-scope model, Youth Panel, Futures Taskforce, and specialist positioning as indicators of resilience. The scoreboard should not be utilization alone. A defensible advisory model measures clarity of demand, quality of contribution, repeat trust, and future capability.

The structural implication is that consulting advantage is moving away from manpower and toward meaning. Firms now have to prove what they are worth calling for when analysis is faster, cheaper, and more widely available. The strongest firms will not simply deliver more efficiently. They will make sharper choices about expertise, talent, scope, and the kind of client dependency they refuse to build.

If you want to hear the full conversation behind this analysis with Olly, you can find the episode in the podcast section.

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