The traditional consulting model is facing once-in-a-generation turbulence, according to Nick Pye. The Mangrove Consulting managing partner argues that the old pyramid of a few partners on top, supported by juniors, may be made obsolete by AI.
In the past year, the world’s biggest global consulting firms have quietly reduced graduate intakes. Some studies suggest that more than half of graduate roles now require AI skills, while McKinsey & Company tests new recruits on their AI capabilities. Whether junior consultants should learn how to use these tools is a given – what is more pertinent is what a consultant role will look like next decade.
The industry has long-operated on a simple economic principle: a small number of highly-paid partners at the top, supported by a vast base of graduates doing the analytical heavy lifting. But as artificial intelligence reshapes what clients actually need from consultants, this ‘pyramid’ is becoming increasingly difficult to justify.
The economics that built the pyramid
Understanding why requires looking at what made the pyramid work in the first place. Partners sell work and maintain relationships. Mid-level consultants manage projects. Underpinning that, a broad base of graduates conduct research, build financial models, and create the analysis that is leveraged by senior employees. The problem is that this structure increasingly suits consulting firms rather than the needs of their clients.
Big consultancies achieved healthy margins by billing premium rates for hours mostly performed by the least experienced team members. That’s not to say that this was not a premium service: this analytical work was both time-intensive and valuable. Clients needed people to gather data, run scenarios, and synthesise findings, and the only way to do this at scale was to employ consultants with huge cohorts of bright graduates capable of managing the legwork.
AI can address these needs for a fraction of the time and cost. It therefore becomes considerably harder to justify rooms of employees spending months on spreadsheets and decks when technology can deliver a comparable output in the time it takes to make a cup of tea. And the economics will only deteriorate further as the technology becomes more sophisticated and clients, facing tighter budgets, increasingly look to AI solutions.
What clients actually want
This technological shift coincides with a quieter change: clients increasingly own and understand their own data. What was once held by a few trusted external advisers is now being democratised within organisations. Multinationals now have the technological systems to in-source capabilities, gaining greater control and saving millions in the process.
This means that client expectations have evolved from decks and processes as key deliverables, to decisions and outcomes. The analytical components that once justified large teams and commanding fees are precisely where AI excels. What remains valuable, and what justifies premium fees, is the strategic insight that comes from experience making complex decisions and driving performance – clients want senior judgement, not junior analysis. Hiring more junior members is counterproductive in this respect.
The shape of things to come
So if the pyramid’s days are numbered, what replaces it? Amongst mid- to large-sized organisations, the most discussed model is the “diamond” – wider in the middle and top, thinner at the base, with fewer entry-level analysts, but lots of manager-level orchestration. It’s the least radical future, the one many partners imagine because it’s least disruptive to the multi-level model.
But there’s an alternative: genuinely flipping the pyramid. Teams of more senior and mid-level consultants with minimal junior support, tackling specific challenges and supported by central systems. Less hierarchy, smaller teams, more focus on outcomes and performance.
AI can process data faster than any graduate, but it cannot replicate the judgement developed from years of navigating transformations or understanding of a complex organisation’s cultural landscape. This places a premium on genuine experience and sector expertise.
Boutique consultancies have operated variations of this model for years, competing on quality of thinking and speed of delivery, rather than breadth of resources. What’s changed is that AI now makes this approach economically viable at scales previously impossible. When senior consultants can leverage technology for meaty analytical components that once required teams, they can serve clients more effectively with far fewer people.
The future likely sits somewhere between the two. Different consulting needs will require different structures; some junior talent will remain necessary in certain areas, whilst AI predominates in others. But the direction of travel is clear.
The graduate question
This creates a challenge: if junior roles contract whilst demand for senior expertise increases, where do future expert consultants come from?
The traditional pyramid functioned as a training system where graduates built fundamentals before developing into senior practitioners. That pathway may be closing. The alternative is that consulting increasingly recruits people who’ve already developed sector expertise elsewhere. Instead of training generalists who later specialise, firms may hire mid-career professionals who’ve spent years in specific industries. The career path inverts: specialise first, then move into consulting.
If major firms stop functioning as early-career training grounds, future executives may develop within industries for longer before moving into leadership roles. Where they cut their teeth matters, and consulting may no longer be that place.
For clients, this transition represents a more honest exchange. Premium rates purchase genuine expertise focused on performance rather than subsidising the training of junior staff. It’s uncomfortable for an industry built on a different model, but it finally aligns the economics with what clients have actually needed all along: experienced judgement, not analytical production.
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