Consulting’s Talent Model Is Changing Faster Than Its Career Model

Summary: McKinsey is hiring engineers, computer science PhDs and founders without degrees as AI reshapes client work, and AI roles across the seven largest firms have more than tripled as a share of openings. Hiring technologists is the easy part; the real test is whether consulting’s career model, economics and Partner track change with them.

Consulting’s talent model is changing faster than its career model.

For decades, the MBA was the clearest route into elite consulting. McKinsey is now recruiting mathematicians, computer science PhDs, startup founders without degrees and people from technology companies, as AI changes the work it does for clients.

“Our recruiting changed dramatically in the last few years,” Ben Ellencweig, who leads McKinsey’s AI arm QuantumBlack, told Business Insider. QuantumBlack has grown from 47 data scientists working with a Formula 1 team to well above 5,000 AI professionals in a decade.

McKinsey is not alone. EY, once built almost entirely on accountants, now hires engineers and technologists. Bain’s AI workforce has tripled since 2020 and now accounts for around half of its experienced hires, a shift we covered in why expertise is becoming power.

Most commentary stops at the funnel. The funnel is the easy part.

Consulting does not simply need more technologists. It needs to stop treating them as specialist support.

Consulting is hiring fewer people, and more of them are technical

Job postings across Deloitte, PwC, EY, KPMG, McKinsey, BCG and Bain fell by about 24% in the year to May 2026, according to labour-market analysis by Draup reported by Business Insider. Over the same period, AI roles rose from 1.4% to 5% of their openings, roughly one in 20.

The sharper number is forward-deployed engineers. Openings for the role across the seven firms went from zero to 1,404 in a single year. These are engineers who deploy and run production AI systems inside client organisations, and who also do the client-facing work consulting has always done.

McKinsey’s postings for those roles mostly ask for four or five years of engineering experience. This is not a graduate scheme with a coding module. It is experienced technical hiring.

The pattern matches what we saw in the rise of the hybrid professional, where AI-focused roles made up almost 7% of Big Four experienced hires in 2025, more than triple the 2022 share.

Fewer jobs overall, more of them technical. That is not a wider funnel. It is a change in the core unit of consulting work.

The consulting talent model is moving from advice to deployment

The consulting talent model is shifting because clients now want the same team to frame the problem and then build and deploy the answer inside their organisation. The line between strategy and implementation is getting harder to defend.

The AI labs have noticed. OpenAI has set up the OpenAI Deployment Company to embed engineers inside enterprises, and Anthropic has launched a $1.5bn deployment venture backed by Blackstone, Hellman & Friedman and Goldman Sachs. We looked at what that means in a fifth consulting model.

That puts consulting firms in direct competition with the labs for the same engineers. The firm that offers client impact and a real career wins the hire. The firm that offers a support role behind a generalist Partner does not.

Hiring technologists is easier than keeping them

Consulting firms are finding that hiring AI talent is the easy part and keeping it is where they struggle. In our own conversations with candidates and firms this year, four patterns keep coming up.

Senior AI people inside consulting often describe it as plan B. Big tech, the AI labs and corporate AI transformation roles are plan A, and many are interviewing for both.

The pool is thinner than the layoff headlines suggest. The traffic is running from consulting into technology, not the other way.

The scarce profile is not the pure data scientist. It is the engineer with strong mathematics and production-grade code who has worked inside a real IT estate and can hold a room with the business.

And the best engineers care more about who they work with than the brand on the door. A name that opens doors with MBA graduates carries far less weight with someone choosing between a consulting firm and a frontier lab.

Every Partner is required to sell AI in 2026

Consulting firms tell us that every Partner is required to sell AI in 2026.

Read that again.

Every Partner is expected to sell AI. Very few of the people who can actually build it are on a path to Partner. That gap is the whole problem in one line.

It creates odd economics. The generalist Partner owns the client, the pipeline and the revenue credit. The engineer who makes the work real sits in delivery, measured on utilisation. Credit follows the relationship, not the build.

Over time that shapes who stays. The engineer can see the ceiling early. Most Partner decisions are made years before the vote, and someone who is never put in front of the client is never in that conversation.

A two-tier consulting talent model will not hold

A consulting talent model in which technologists build while generalists keep the client and the vote produces a two-tier workforce, and the strongest technical people will not stay in the lower tier.

Consulting has run versions of this before. Expert and distinguished tracks give senior specialists a title without the same economics or influence. At McKinsey, distinguished partners do not vote in managing partner elections. An expert path is not equal if it pays and counts differently.

A firm that hires 1,400 forward-deployed engineers and makes none of them Partner has not changed its model. It has built an expensive contractor bench.Strat-Bridge

The fix is not a separate “tech Partner” badge. It is giving technologists client ownership, revenue credit and a seat in the decisions that shape the firm. That also changes how the partnership itself works, from pay to capital.

The future Partner combines commercial judgement and technical fluency

The future consulting Partner will not be defined by an MBA or a computer science degree, but by combining commercial judgement and client trust with technical fluency and accountability for what gets implemented.

Consulting does not have an AI talent shortage. It has a shortage of people who can make AI matter in the boardroom.

That profile can be built from either end. Some generalists will become fluent enough to shape and own technical delivery; Accenture has already made AI fluency part of its promotion criteria. Some engineers will build the commercial judgement and client trust to originate work.

Partners from both routes will also need to understand the economics of AI delivery, not just the relationship.

Both routes need deliberate development, and that is where the traditional apprenticeship model is under pressure. If AI removes the routine analysis juniors learned on, and engineers are kept away from clients, neither group gets the reps that produce a Partner.

What firms that get the consulting talent model right will do

The winners will treat technologists as future Partners from the day they are hired. They will put engineers in front of clients early, share revenue credit for delivery, and open the partnership vote to people who got there through code rather than case interviews.

Many firms will still get it wrong. They will count technologists as headcount, celebrate the hiring numbers, launch an expert track and wonder why their best engineers keep leaving for the labs. AI may not end the traditional route into consulting. But it is ending its monopoly, and the firms that hold on to it hardest will lose the talent they most need.

Strat-Bridge is a retained executive search firm placing Partner & Director-level leaders into strategy and management consulting firms across Europe.

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Ben Appleton

Ben Appleton is the founder of Strat-Bridge, a specialist executive search partner to the management consulting industry. He works with global consulting firms and senior leaders across the UK, Germany, Switzerland, and beyond — helping them build capability at the Partner and Director level.
Connect with Ben on LinkedIn or email ben@strat-bridge.com.