The recent announcement by McKinsey & Company that it plans to cut roughly 10% of its workforce has sent ripples through the consulting world, reigniting debate about the future of the industry. This is not about one firm, one round of layoffs, or one business cycle. It signals an irreversible shift in how value is created in consulting.
Having spent a significant part of my career at McKinsey, I saw it grow and flourish in an era when information was scarce. Even basic market intelligence required large teams working for months to gather and synthesize data. The digital age brought a data explosion and democratized access, and McKinsey adapted again by expanding its capabilities into advanced analytics and technology-enabled transformation.
That advantage is now under pressure in the AI age.
The existential threat in the AI age
While the digital age reduced information asymmetry, the AI age goes further. It increasingly equalizes analytical and recommendation capabilities. Firms like McKinsey built a powerful competitive moat by hiring the best analytical minds from top universities—excelling at data synthesis, first-principles problem-solving, and translating insight into recommendations. In the AI age, however, that advantage is becoming commoditized.
This shift is part of a broader transformation of white-collar work. Contrary to early assumptions, AI is impacting knowledge work more than blue-collar roles. I expect that over the next five years, nearly 300 million white-collar jobs will be impacted globally, with around 100 million at risk of becoming obsolete. Work that is highly cognitive and already digitized is particularly susceptible.
Consulting sits squarely within this zone of disruption. As the traditional consulting model faces growing pressure, the premium for future talent will no longer rest on analytical horsepower alone.
The center of gravity has shifted: Consulting is being redefined
The need for consulting services is not disappearing, but the source of value is shifting decisively. Traditionally, firms like McKinsey, BCG, and Bain (MBB) sat at the top of the consulting value chain through high-value strategy work. Over the years, McKinsey has invested significantly in building technology and execution capabilities, but structural challenges remain. In contrast, execution-centric firms like Deloitte, EY, and Accenture, built with a different DNA, were able to more naturally combine advisory with technology and large-scale execution.
The growth numbers speak for themselves. While the MBB firms have reported slower growth, averaging approximately 5% to 6% compound annual growth rate, implementation-led firms such as Accenture, Deloitte, and EY have grown approximately 11% to 12% in recent years (average growth estimated based on revenues from company websites, annual reports, press releases, and analyst reports), reflecting the direction of client spend.
Historically, strategy was viewed as the highest-value activity, and execution was treated as a follow-on—largely organizational and operational in nature. In the digital and AI age, execution is deeply technology-driven, and strategy and execution are no longer sequential but iterative and continuous. From being an enabler, technology has become the primary driver of both strategy and execution.
Clients increasingly want partners who can bridge strategy, technology, and operations, and execute change at scale. Consulting firms, including the Big Four, have responded by reshaping their talent and operating models around large-scale execution and organizational transformation.
The Battle of Relevance in the AI age: Where does McKinsey stand?
The key question now is: Who will emerge as winners in this new consulting landscape? As the center of gravity shifts toward execution depth and the ability to drive continuous change, success will depend on how effectively firms rewire their DNA—building the operating model and talent engine required to implement and scale tech-led transformation.
While strategy remains critical in the AI age, it demands a higher bar. As AI takes over analysis and recommendations, strategic advantage shifts from problem-solving to sense-making—from humans “in the loop” to humans “above the loop.”
My bet is that two types of firms are best positioned to win. First, there are firms like Accenture, Deloitte, and EY, which have built strong execution capabilities and successfully strengthened their technology foundations. Second, there are industry specialists with exceptional domain expertise, where deep contextual understanding becomes the primary source of differentiation.
Where does that leave McKinsey? While its brand, client relationships, global reach, and intellectual capital remain as formidable strengths, the transformation challenge it faces may be far greater than what it advises its clients on. Meeting it will require more than just new capabilities. It requires a structural reset, beginning with a mindset shift—from authority rooted in expertise to leadership grounded in learning and adaptability.
Whether McKinsey retains its position at the top will depend on how effectively it embraces this shift. In the AI age, even the most storied institutions must continuously reinvent themselves—or risk being outpaced by those that do.