Major consulting firms are undergoing their largest-ever workforce transformation as artificial intelligence fundamentally reshapes the industry. Firms like McKinsey, Boston Consulting Group (BCG), PwC, Deloitte, EY, and KPMG are aggressively hiring technologists, retraining existing staff, and redefining what it means to be a consultant in the AI era.
The shift is dramatic and data-driven. Accenture added nearly 40,000 AI and data professionals in just two years, now representing roughly 10% of its global workforce. EY brought on 61,000 technologists since 2023. At McKinsey, “AI engineer” has become the fastest-growing non-entry-level role, followed by data scientist and software engineer, according to workforce intelligence company Revelio Labs. BCG, which hired 1,000 employees last year, has ramped up technologist recruitment since launching its tech and AI arm, BCG X, in late 2022.
The nature of consulting work itself is transforming. Traditional advisory projects centered on slide decks and strategic recommendations are being replaced by multi-year AI-driven transformation initiatives that require building, implementing, and maintaining sophisticated tools. “Going to a client and purely proposing an army of consultants doesn’t really work anymore,” explained Gert De Geyter, former AI lead at Deloitte US who left in July to join AI startup Teragonia.
Firms are seeking hybrid talent — professionals who can bridge the gap between technical expertise and business consulting. Alex Singla, a senior partner at McKinsey who co-leads QuantumBlack (the firm’s AI arm), described the ideal candidate as a “5Xer — they’re deep in one thing, but can do three or four different things well.” McKinsey’s AI initiatives now account for 40% of the firm’s total work, with QuantumBlack’s 1,700-person team driving these efforts.
Upskilling existing workforces has become imperative. PwC’s AI Lead Saurabh Sarbaliya noted that “the demand for people who can make AI work in the enterprise is only going to grow — but there just aren’t enough experts. So you have to focus on upskilling your existing workforce.” EY held a two-week learning event teaching employees to build AI agents, and nearly 100,000 employees — roughly a quarter of its workforce — have earned digital “AI badges” for completing courses on AI engineering, applied AI, and compliance.
Despite the technical shift, soft skills remain crucial. Leaders emphasized that communication, collaboration, and emotional intelligence are becoming more valuable as AI handles quantitative tasks. “What we really hire for is voracious learners, people who are curious about the world,” said Kate Smaje, McKinsey’s global leader of technology and AI.
Key Quotes
Going to a client and purely proposing an army of consultants doesn’t really work anymore.
Gert De Geyter, former AI lead at Deloitte US, explained how the traditional consulting model is becoming obsolete. This statement captures the fundamental shift from advisory work to hands-on technical implementation that’s driving the industry’s talent transformation.
We’re essentially building a tech company inside a consulting firm. Our job has always been to help companies transform. But tech has become so critical to transformation that we needed to have a grip on it ourselves.
Sylvain Duranton, Global Leader of BCG X, described Boston Consulting Group’s strategic pivot. This quote illustrates how even elite strategy firms recognize they must develop deep technical capabilities to remain relevant in the AI era.
What we want to be able to do is find those people that actually have a propensity to either be this great McKinsey consultant, and or a great technologist, and then groom them to be both.
Alex Singla, senior partner at McKinsey who co-leads QuantumBlack, outlined the firm’s hiring philosophy. This reflects the industry-wide search for hybrid talent who can bridge business strategy and technical implementation — a skill set in critically short supply.
The demand for people who can make AI work in the enterprise is only going to grow — but there just aren’t enough experts. So you have to focus on upskilling your existing workforce.
Saurabh Sarbaliya, PwC’s AI Lead, highlighted the talent shortage driving massive upskilling initiatives. This explains why firms are investing heavily in training existing employees rather than relying solely on external hiring to meet AI talent needs.
Our Take
This workforce transformation reveals a critical inflection point: AI has moved from boardroom buzzword to operational reality. When McKinsey reports that 40% of its work now involves AI initiatives, and Accenture dedicates 10% of its entire global workforce to AI and data roles, these aren’t speculative bets — they’re responses to client demand for tangible AI implementation.
The emphasis on “5Xers” and hybrid talent is particularly telling. It suggests that successful AI deployment requires more than technical prowess — it demands professionals who understand business context, can communicate with non-technical stakeholders, and navigate organizational change. This may actually create opportunities for consultants willing to upskill, rather than simply displacing them with engineers.
However, the industry faces a strategic risk: if most employees remain at a “nascent” technical literacy level, as one Deloitte engineer warned, firms may struggle to deliver on ambitious AI transformation promises, potentially damaging client relationships and the consulting industry’s credibility in the AI space.
Why This Matters
This transformation represents a fundamental restructuring of the $300+ billion global consulting industry, signaling how deeply AI is penetrating enterprise operations. When the world’s most prestigious consulting firms — traditionally bastions of MBA generalists — prioritize hiring software engineers and data scientists, it reflects a broader shift in how businesses approach digital transformation.
The implications extend far beyond consulting. If companies need consultants who can build and implement AI systems rather than just advise on strategy, it suggests that AI adoption has moved from experimental to operational. This creates both opportunities and challenges: demand for AI-skilled workers will intensify across industries, potentially widening the talent gap and driving up compensation for technical roles.
For current and aspiring professionals, the message is clear: technical literacy is becoming non-negotiable, even in traditionally non-technical fields. The consulting industry’s pivot also validates AI as a sustained trend rather than hype — firms are making multi-billion dollar bets on AI-driven transformation work lasting years, not months. This workforce overhaul may preview similar changes coming to law, finance, healthcare, and other professional services sectors.