AI is threatening the giants of consulting

It all started with a chicken shop deal. When Mr Mark Bunker read about the founders of a UK fast-food chain walking away with a small fortune after a private equity deal, he felt something close to envy. “It can’t be that difficult,” he recalls thinking.

But Mr Bunker was a Deloitte senior advisory partner, not a chef. Launching a new advisory firm capable of competing with the huge incumbents was widely considered impossible. Scale was everything in consulting.

Yet the landscape was shifting. Artificial intelligence was beginning to erode the advantages that had protected the major players for decades and rumours were circulating of Big Four partners leaving to launch AI-native advisory firms backed by private capital.

So Mr Bunker joined them. Over lunch at the House of Commons with an old friend from Imperial College London, he sketched out a plan to set up Queen’s Tower Advisory, named after a university landmark, which would utilise AI agents to bolster human workers.

He went on to recruit a senior EY partner as chair.

Queen’s Tower is just one of a growing crop of advisory firms launched in the UK in recent years with ambitions to challenge the consulting establishment.

AI has suddenly made smaller firms scalable and private equity firms or other backers are increasingly willing to finance them.

A business model, disrupted

For decades, consulting has been dominated by a handful of giant firms, ranging from the elite strategy houses of McKinsey, Bain and Boston Consulting Group (BCG) to the consulting arms of the Big Four – Deloitte, EY, KPMG and PwC – and the technology implementation behemoths such as Accenture. Each boasts armies of junior consultants able to work on large projects across multiple geographies.

AI is beginning to dismantle that hegemony for the first time, opening the door to well-funded challengers. The technology robs the incumbents of their main advantage: scale. With certain jobs increasingly performed by AI agents, small firms can take on projects of a size that used to be impossible.

The Management Consultancies Association (MCA) estimates that smaller firms are seeing growth rates of up to 50 per cent as AI helps them compete with larger rivals.

AI has brought down the “barrier to entry”, says Mr Bunker. “Your platform might have 20 people, but... with the amplification factor of AI, you’re suddenly at 100 people, 150 people, very quickly. Now that created a dent in the marketplace very quickly.”

He aims to build teams made up of 20 per cent humans, 80 per cent AI agents. 

This shift has collided with a surge of private equity interest in growing professional services firms. Europe’s largest private capital group has given more than €500 million (S$743 million) to build out tax advisory firm WTS, which aims to hire 100 partners within five years and directly compete with the Big Four.

Previously, most new consultancies faced years of slow organic growth before they could hope for capital from an initial public offering to help them achieve the scale needed to challenge incumbents.

Together, private capital and AI have created a “huge inflection point” for the industry, says a former Big Four executive who helped oversee their firm’s response to the first generation of large language models.

When you add fast-changing demands by clients and lower budgets, “it’s an infamous perfect storm”, says Ms Fiona Czerniawska, chief executive of Source Global Research. “Historically, each of these things has happened but never once before at the same time.”

The bigger firms are now under pressure to redraw their workforce strategies and in some cases have begun shedding thousands of jobs.

The Big Four have cut UK graduate recruitment, while PwC’s global headcount fell by 5,600 in 2025, though the firms generally attribute such moves to economic conditions and routine restructuring.

Ms Sayeh Ghanbari, EY’s head of consulting for UK and Ireland, says the industry has already accepted that parts of its traditional business model will disappear.

“Certain aspects of the work will be disrupted, either because clients will do it themselves or because the work just isn’t relevant any more,” she says.

The big firms will themselves shape-shift, she predicts, a strategy they have used many times. “Where certain services will fall off, other services will be created.” 

Few industries are debating AI’s implications more intensely than consulting, whose core work of research, summarising data and producing neatly designed PowerPoint presentations is highly automatable.

Professor Richard Susskind, co-author of The Future Of The Professions, says consultants are more vulnerable than other mainstream professions in part because the work of junior staff “can now be taken on, with mild supervision, by increasingly capable AI systems”.

The sector now has two new competitors, he adds: “The AI-empowered client and disruptive start-ups. Both challenge the conventional model.”

Investors fear that firms reliant on vast offshore centres performing routine cognitive tasks may be particularly exposed.

Accenture, one of the few listed consultancies and with almost 800,000 employees, has seen its share price fall more than 50 per cent since its peak in late 2021, reducing its market value from more than US$260 billion (S$332.8 billion) to about US$108 billion.

The larger consultancies are quickly realising the scale of the challenge ahead.

“I want this organisation – us – to still exist... That’s how disruptive I believe AI will be,” says Ms Lisa Fernihough, head of advisory at KPMG UK. “If we don’t change, change will happen to us.”

For Mr Bunker, founding Queen’s Tower meant abandoning the comforts of partnership life and confronting start-up realities – whether “cleaning the bathrooms or writing reports”, as he puts it.

The disrupters acknowledge the trend they embody is still in its infancy.

“We’re in the foothills of the shift but the pace of it is starting to build,” says Ms Marissa Thomas, the former chief operating officer of PwC UK, who has helped launch start-up Unity Advisory.

They believe their gamble will pay off because AI is attacking the foundations of the traditional consulting model on three fronts: its historical reliance on generalist consultants, its billing model and its pyramid staffing structure.

The larger firms have traditionally employed generalist consultants, who are prized for their analytical ability rather than sector expertise and deployed across industries.

But much of that work overlaps with tasks that generative AI performs well. Clients increasingly use AI tools to generate an initial diagnosis before turning to consultants for deeper expertise, says Mr Bunker.

His clients come with a “cursory or headline view” of a problem, and only need a “deep expert to go that layer down”.

“The firms that succeed in this AI world will be the ones that are highly specialised rather than the more generalist type of service,” says Mr Tom Shave, the president of Europe and Asia-Pacific operations at tax advisory firm Ryan.

In his telling, firms with deep specialisms will get more client work. The major firms will have to build up teams with deep industry and domain expertise and reduce the number of generalists they house – an effort begun years ago in some countries – while start-ups are founded along those lines. MCA figures show its member firms recruited 25 per cent more experienced people in 2025.

What happens to billables?

AI also threatens one of professional services’ foundational economic models: billing by time. When a bot can review thousands of contracts in minutes and draft complex documents in seconds, the relationship between hours worked and value delivered begins to break down.

Increasingly, clients are demanding pricing linked to outcomes rather than labour inputs. McKinsey spent more than two years overhauling how it pays its partners in order to adapt to the move away from its old billable hours model. Roughly a third of its work is now tied to performance-based fees, according to a person familiar with the firm.

“AI is really challenging the (billable hour) model that a lot of the firms have been built on,” says Mr Shave, who does not ask his employees to fill in time sheets.

For firms built around audit practices, the transition is particularly difficult.

Independence rules and longstanding cultural norms make fees based on certain targets being successfully hit more complicated for the Big Four than for firms that do only consulting work, Mr Shave says. “Success-based billing is anathema to large and professional services firms like the Big Four.” 

Mr Bunker’s firm uses a mixture of success-based fees and subscription fees for loaning his AI agents to clients.

Ms Fernihough says KPMG also expects pricing models to evolve towards subscriptions and success-based fees, even if that depresses revenues in the short term.

But she is betting on consulting becoming both faster and cheaper so that clients will “have the additional funding and... the capacity to do more”, and revenues will ultimately grow.

The shift away from hourly billing is also undermining the traditional pyramid structure, in which a firm employs thousands of junior-level employees and thins out the ranks with an “up or out” promotion culture. 

For decades, firms relied on large cohorts of junior employees whose billable hours generated profits for a smaller number of partners at the top. AI reduces the need for those labour-intensive delivery models.

“Without time sheets, that entire resourcing model loses its logic,” says Mr Shave. “We all have much leaner models because we don’t need armies of people to deliver the work (any more).”

Some firms are betting on an “obelisk” structure instead, with fewer layers and less reliance on junior staff, while others predict an “hourglass” — pinched in the middle as AI automates mid-level routine tasks.

Not all executives agree that AI will obliterate the pyramid structure. Big Four executives in the UK are aware of their firms’ status as major graduate employers and talk privately about their responsibility to take on large numbers of young people and train the next generation of accountants and consultants.

Ms Kate Smaje, McKinsey’s global AI lead, says her company is “not turning the taps off” on graduate recruiting. The MCA says graduate and apprentice recruitment is currently up across the sector.

But without the billable hour and with smaller rivals able to charge far lower prices, the economics of this will be difficult to sustain.

Who emerges the top dog?

The incumbents are adamant that they will retain their position at the top of the food chain.

Companies wrestling with geopolitical fragmentation, supply-chain disruption and AI adoption still need external expertise, they argue – BCG claims 40 per cent of its revenues come from its AI- and tech-focused business.

“People will still need consultants,” says Ms Smaje. “The nature of what is consulting... of course has to change.”

In addition, the Big Four previously rode out the disruption caused by the rise of the Indian consulting giants Infosys and Tata Consultancy Services in the early 2000s, Ms Czerniawska notes.

The big companies retain one overwhelming advantage: money. They have invested billions of dollars in AI. It comes with problems – a rash of hacks on LLMs with poor cybersecurity, and embarrassing public AI hallucinations – but it will pay off, they claim.

Their global networks also allow them to pool expertise across jurisdictions and industries. Often, getting member firms to work together on a global project is intensely political and riven with differences in strategy, but KPMG’s Ms Fernihough says the urgency of AI has improved cooperation: “We are working... better than I’ve ever seen, on this topic.”

McKinsey has taken a different approach, forming alliances with technology companies rather than spending capital on building everything internally.

Ms Smaje describes teams that are so AI-literate they have entirely eschewed the “50-page deck that thuds on the (table)”.

Such alliances have become fundamental to the way large consulting firms win business, according to Source Global Research, which found in a survey of major consulting clients that they wanted access to the expertise of specialist technology providers. 

The problem is, the big tech companies understand this too. OpenAI and Anthropic are already making moves to corner the increasingly lucrative market of selling AI tools to businesses, potentially bypassing the consultants.

OpenAI has launched a new consulting and services business, backed by US$4 billion in private equity cash, and has forged an alliance with major consultancies, prompting criticisms that the consultants are “letting the fox into the hen house”.

The biggest money to be won is from multinational clients that need to adapt at scale and in a variety of complex, interacting ways. The major firms argue they will capture that high-value work because they are built to be multidisciplinary and have the wherewithal to grow new arms rapidly. 

“The issues are complex, they’re rarely niche,” says EY’s Ms Ghanbari. “The industry has space for niche players, but it will depend on client matters and what the issue at hand is... Our role is for clients (with) complex matters... where that multidisciplinary approach is required.”

Still, the incumbents face accusations of moving too slowly. Rolling out AI tools across organisations with hundreds of thousands of employees can take months, by which point newer models may already have overtaken them.

Part of the problem is convincing top talent to stay instead of defecting to a smaller, lithe opponent. It is an issue that Big Four executives are paying close attention to.

Ms Fernihough admits the bureaucracy can be near-crippling for AI projects that need to move fast. KPMG created an internal “air-gapped” initiative, known as Project Watts, to bypass normal approval processes and experiment directly with clients. The result, she says, is that tools that once took months to build can now be developed in weeks.

Some time to adapt

The Big Four and other large consultancies do have some time to adapt, as the new generation of start-ups attempts to build up market share.

The scale of change could be “considerable” but it may take years for any effects to show, says Ms Czerniawska, who says there is “very little evidence” of AI disrupting whole swaths of the sector just yet.

The former Big Four executive adds that many clients retain “deep loyalties” to the long-established brands.

In the short term, the danger may be greatest for mid-tier firms that have neither the Big Four’s capital to invest aggressively in AI infrastructure, nor the agility of boutique firms. Squeezed between both ends of the market, they risk being stranded in the middle.

“The big firms can always retreat and retrench into something that looks more lean and focused,” says management professor Laura Empson of Bayes Business School, London. “But the medium-tier firms, if they end up doing too much of that, they may end up getting too malnourished.”

But challengers say that if they expand into the right geographies and attract enough senior talent, they could quickly eat up a larger share of the pie. Ms Thomas of Unity Advisory promises that they will soon peel market share away from the incumbents.

More start-ups will almost certainly appear, adds Mr Bunker of Queen’s Tower Advisory, as more veteran consultants smell the lucre. But he is determined it will not become a “Wild West of start-ups”, with new entrants instead rigorously disciplined by the demands of the financial backers that made their bid for glory possible.

The question for founders like him is whether they can resist being folded back into the establishment they are trying to disrupt by selling out to the incumbents.

After years of the “sheer relentless slog” of building a consultancy, founders often tire, Prof Empson notes, “and the bigger firms will be waiting in the wings to absorb them”. FINANCIAL TIMES