How McKinsey Plans to Survive AI (and Reinvent Consulting)
McKinsey is navigating a pivotal moment: technology that promises to automate much of what consultants traditionally sold is already reshaping the economics of advisory work. As generative AI commoditizes analysis and insight, the firm faces a fundamental question — what will clients actually pay for when they can do so much themselves? Meanwhile, the firm is still reckoning with reputational damage from high-profile missteps in client selection and oversight. Can a century-old partnership model reinvent itself fast enough to stay relevant in an agentic, outcomes-driven future?
Ключевые выводы
McKinsey already employs 20,000 AI agents alongside 40,000 humans and expects to reach one agent per person within 18 months — a threshold originally projected for 2030.
The firm is migrating from fee-for-service advisory to outcomes-based partnerships, with roughly a third of revenues now tied to underwriting client results rather than delivering reports.
AI will commoditize much of what McKinsey historically charged for, forcing the firm to climb the value chain toward questions like «how do we double market cap» that require judgment, aspiration-setting, and discontinuous creative leaps.
The firm invested $1 billion to overhaul compliance and client vetting after missteps in opioid work and South Africa, bringing in leadership from Apple and Walmart to impose public-company-grade standards on a private partnership.
McKinsey overhauled talent selection to prioritize resilience, teamwork, and learning aptitude over perfect grades, discovering through internal data that candidates who had experienced setbacks were more likely to succeed long-term.
Вкратце
McKinsey is betting its future on a radical shift from selling advice to underwriting outcomes, building a hybrid workforce of humans and AI agents, and moving upmarket to tackle problems so complex that even superhuman tools can't solve them alone.
The Agentic Workforce Is Already Here
McKinsey now deploys 20,000 AI agents and expects one per human within 18 months.
The Client Tension: CFO vs. CIO
CEOs face internal conflict between technology spending and measurable enterprise value from AI.
“Do I listen to my CFO or my CIO? My CFO is in my ear that we're spending a lot of money on technology, but we're not yet seeing enterprise-level value from this. CIO's saying, are you crazy? This is one of those moments. And if we're not in the lead, we're going to get disrupted.”
Why AI Transformation Takes Longer Than Expected
Half or more of the challenge is organizational redesign, not technology.
Sternfels reports that CEOs worldwide are torn between enthusiasm for AI's potential and frustration with the pace of value realization. While technology leaders push for aggressive adoption to avoid disruption, finance chiefs question the return on massive AI investments. McKinsey's research points to a surprising culprit: organizational structure.
The firm finds that successful AI implementation requires fundamental rewiring — flatter hierarchies that eliminate middle management layers, consolidated workflows that break down departmental silos (like collapsing four or five mortgage process departments into one), and new operating models that can actually capture productivity gains. Banks, for example, have traditionally organized around process steps — origination, credit scoring, servicing — but AI-enabled workflows make those boundaries obsolete.
This organizational half of the equation is proving harder and slower than the technology half. Companies that focus only on deploying models without reimagining structure are the ones whose CFOs and CIOs remain at odds. Those that tackle both in parallel are beginning to see the enterprise-level value that justifies the investment.
What AI Can't Do (and What McKinsey Will Sell)
From Advisory to Outcomes: The Business Model Shift
McKinsey is moving away from fee-for-service advice toward underwriting client results.
Overhauling Talent Selection for Resilience
Internal data revealed McKinsey screened out the wrong candidates for 20 years.
The Discovery McKinsey analyzed 20 years of hiring data to identify skills predictive of partnership success. The firm discovered systematic bias: it over-indexed on perfect academic records and under-indexed on resilience, teamwork, and learning aptitude.
Resilience Over Perfection Candidates who had experienced setbacks and recovered proved more likely to succeed long-term than those with unblemished transcripts. The firm now actively screens for resilience in the application process.
Teamwork & Human Skills Real-world collaboration experience — team sports, retail jobs, group projects — became a priority. McKinsey is fundamentally about helping clients change, which requires human-to-human engagement skills.
Learning Aptitude in Novel Environments The firm now assesses how candidates perform in situations with zero pattern recognition — environments where no one has an advantage and pure learning ability matters most.
Opening 500 Pathways to Thousands McKinsey historically drew from only 500 elite academic and professional tracks worldwide. The new framework diversified sourcing to capture talent the old system systematically excluded.
Reckoning with Opioids and South Africa
High-profile missteps forced a $1 billion investment in compliance and client vetting.
Sternfels acknowledges that McKinsey's work advising opioid manufacturers and partnerships in South Africa were failures that demanded humility and structural change. The firm's traditional model gave individual partners broad autonomy to commit the enterprise, with minimal central oversight — a structure that scaled poorly as the firm grew and regulatory scrutiny intensified.
In response, McKinsey invested roughly $1 billion to bring in compliance and audit leaders from Apple and Walmart, building a client selection framework that evaluates country risk, topic sensitivity, institutional integrity, individual actors, and operating environment before engagement. Partners no longer commit the firm alone; they work alongside risk professionals. Sternfels framed the goal not as remediation but as setting the standard for professionalism in consulting.
At the same time, the firm pushed back on criticism it considered unfair — particularly attacks on its work with hard-to-abate sectors on climate transition. Sternfels argued that solving climate change without engaging high-emission industries is «naive,» and that McKinsey would not retreat from difficult work simply to avoid controversy. The dual posture — humble accountability for genuine failures, courage to defend legitimate but controversial choices — reflects the firm's attempt to navigate heightened institutional scrutiny without abandoning its mission.
What CEOs Are Obsessed With Right Now
The 10-Year Aspiration
Sternfels wants McKinsey known as an impact partner, not an advice shop.
The 10-Year Aspiration
In a decade, Sternfels hopes McKinsey is still the world's leadership factory — but no longer remembered for smart slide decks that may or may not get implemented. Instead, he envisions clients saying: «We designed a business case together. These guys underwrote the same outcomes I took to the board, and we kept at it until we got to someplace I didn't think I could get to.» The shift from advisor to impact partner is the existential bet.
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