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How McKinsey Plans to Survive AI (and Reinvent Consulting)
Harvard Business Review
Overview
McKinsey's Global Managing Director, Bob Sternfels, discusses the firm's evolution over its 100-year history, emphasizing co-creation with clients and a significant investment in proprietary intellectual property. He highlights how AI is reshaping the consulting industry, necessitating internal adaptation and a shift towards outcome-based models. Sternfels also addresses the evolving skill requirements for consultants, focusing on resilience, teamwork, and adaptability, and touches upon the firm's efforts to learn from past mistakes and uphold professional standards. The discussion concludes with insights into current CEO priorities, including leveraging AI, building resilience, and rethinking organizational structures for future success.
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Chapters
- McKinsey's approach is characterized by co-creation with clients, helping them achieve goals they couldn't reach alone.
- The firm invests heavily in proprietary intellectual property, with over $1 billion annually in innovation, research, and new ideas.
- McKinsey's model combines novel, in-house thinking (e.g., global balance sheet analysis) with bringing global innovations to local clients.
- The firm's legacy is a blend of generating original ideas and disseminating best practices from around the world.
Understanding McKinsey's historical approach provides context for its current strategies and its role in shaping business practices.
The McKinsey Global Institute's analysis of the global balance sheet is cited as an example of novel, in-house thinking.
- AI presents a unique opportunity for clients to reimagine their businesses, driving both productivity gains and top-line growth.
- Clients face a dilemma between investing in cutting-edge AI (CIO perspective) and being cautious about ROI (CFO perspective).
- Successful AI implementation requires significant organizational change, including flatter structures and breaking down departmental silos, not just technology adoption.
- McKinsey is integrating AI internally, rapidly increasing its use of 'agents' alongside human consultants, aiming for a human-agentic workforce.
This chapter explains how AI is fundamentally changing the consulting landscape and the nature of business operations, requiring strategic adaptation.
McKinsey is now employing 20,000 AI agents alongside 40,000 humans, a number that has grown dramatically in a short period.
- McKinsey is moving away from a traditional fee-for-service advisory model.
- The future model is increasingly outcomes-based, where McKinsey underwrites the results of joint business cases with clients.
- This shift aligns McKinsey's interests more closely with client success and long-term impact.
- Clients will pay for McKinsey's ability to tackle more complex, interconnected problems that they cannot solve themselves.
This transition signifies a deeper commitment to client success and a fundamental change in how consulting value is delivered and measured.
Approximately one-third of McKinsey's current revenue comes from underwriting outcomes, a model they aim to expand.
- McKinsey is re-evaluating hiring criteria, moving beyond traditional credentials to focus on resilience, teamwork, and learning aptitude.
- Resilience, demonstrated by overcoming setbacks, is a key indicator of partner potential.
- Strong human-to-human interaction skills, developed through diverse experiences, are crucial for client engagement and change management.
- Future consultants will need skills that complement AI, such as leadership (setting aspirations), judgment, and discontinuous, creative thinking, potentially drawing from liberal arts backgrounds.
Understanding these evolving skill requirements is vital for aspiring consultants and for organizations seeking to develop talent in a rapidly changing environment.
McKinsey now screens for resilience by looking at how applicants handle setbacks and recover, rather than just focusing on perfect academic records.
- McKinsey has undergone significant 'soul searching' following public controversies, leading to a focus on learning from mistakes and being more courageous when necessary.
- Key learnings include the need for higher diligence in client selection and robust risk assessment frameworks.
- The firm has invested heavily in modernizing compliance and risk management processes, bringing in external expertise.
- McKinsey aims to set industry standards for professionalism, acknowledging that this is an ongoing journey requiring continuous improvement and external feedback.
This section addresses how McKinsey is learning from its past, implementing changes to ensure ethical conduct and maintain client trust.
A new, robust assessment framework now evaluates clients across multiple dimensions (country, topic, institution, individuals, operating environment) before engagement.
- CEOs are focused on transforming enterprises through technology, building institutional resilience against continuous shocks, and rethinking organizational models.
- Building resilience involves balancing 'offense' (bold bets) with 'defense' (buffers) to navigate an unpredictable world.
- Current organizational structures, often matrixed, are frequently seen as bottlenecks, prompting a search for more effective future models.
- Key leadership skills in a post-AI world include setting aspirations, exercising judgment, and fostering discontinuous, creative thinking.
This chapter outlines the critical challenges and strategic priorities facing leaders today, particularly in adapting to technological disruption and global uncertainty.
The concept of institutional resilience is likened to a sports team needing to play both offense and defense simultaneously.
Key takeaways
- McKinsey is evolving from a traditional advisory firm to an 'impact partner' that underwrites client outcomes.
- AI is not just a tool for clients but a catalyst for McKinsey's internal transformation, integrating AI agents into its workforce.
- Successful AI adoption by clients hinges on significant organizational change, not just technological implementation.
- Consultant selection is shifting towards valuing resilience, collaboration, and adaptability over purely academic achievement.
- McKinsey is actively learning from past controversies by enhancing client diligence, compliance, and risk management.
- In an era of continuous shocks, building institutional resilience and fostering adaptive organizational models are paramount for leaders.
- Leadership in the AI era will increasingly depend on setting aspirations, exercising judgment, and driving creative, non-linear thinking.
Key terms
Co-creationProprietary IPMcKinsey Global InstituteArtificial Intelligence (AI)Organizational ChangeHuman-Agentic WorkforceOutcomes-Based ModelResilienceAptitude to LearnDiscontinuous LeapsInstitutional ResilienceImpact Partner
Test your understanding
- How is McKinsey's business model evolving in response to AI and changing client needs?
- What are the key organizational challenges companies face when implementing AI, according to McKinsey?
- Why is McKinsey shifting its focus in hiring and developing consultants towards resilience and adaptability?
- What steps has McKinsey taken to address past controversies and improve its professional standards?
- How do leaders need to adapt their approach to management and organizational design in the current environment of continuous shocks and technological change?