How to Build the AI “Second Muscle” in Business Leaders

Why AI Leadership Matters

McKinsey’s December 2025 report Building the AI muscle of your business leaders highlights a critical gap: AI tools are plentiful, but leaders who can translate technology into business value—called domain owners —are scarce. The report argues that true advantage comes from nurturing these hybrid leaders rather than merely buying more tools.

What Is a Domain?

A domain is a relatively independent end‑to‑end business process that is large enough to have significant impact yet small enough to be transformed without heavy reliance on other departments. Typically 5–15 interrelated use cases are needed to deliver real transformation value, and firms expand or deepen domains to scale AI adoption.

Current Leadership Shortage

Analyzing LinkedIn profiles of 3,348 C‑level executives and over 900,000 senior leaders from Fortune 500 companies, McKinsey found that only 17% possess technical skills and merely 5% have held technical roles, reflecting a historic separation between IT and business leadership.

What Excellent Domain Owners Look Like

Citizens Bank – Adam Boyd : Non‑technical background; reduced mortgage loan approval time from >35 days to a few days using AI‑driven credit scoring, personalized marketing, digital applications, and back‑office automation.

Schwab – Neesha Hathi : Former head of a software subsidiary and chief digital officer; leverages technology to redesign customer journeys and operational processes.

Tata Steel – Menno Van der Winden : Former quality and product development lead; used advanced analytics and AI to dramatically improve product quality and output.

These leaders have developed a “second muscle” – a technology capability that augments their traditional business skills.

Four Capabilities of the “Second Muscle”

Customer‑Centric Vision : Identify pain points and waste, then redesign processes with AI rather than simple automation.

AI‑Enabled Roadmap : Co‑create end‑to‑end use‑case sequences with experts, attach clear KPIs, and avoid delegating execution solely to IT.

Technical Delivery Oversight : Understand agile development and data architecture to prioritize, unblock, and iteratively build scalable solutions.

End‑to‑End Change Management : Own solution rollout, value realization, cross‑functional coordination, and organizational adaptation.

Six Practical Ways to Build the “Second Muscle”

Learn Like a Mission : Dedicate 6–10 hours weekly to reading, engaging with tech leaders, attending sprint reviews, and visiting startups.

Focus on Value, Redesign Processes : Target initiatives that deliver >20% incremental value, using AI agents to reshape workflows.

Understand Operational Levers : Combine people, data, and technology; foster cross‑functional collaboration and grasp enterprise architecture.

Get Hands‑On : Participate in design workshops to develop intuition about project progress.

Develop Technical Talent Sense : Recruit, motivate, and train engineers; e.g., Van der Winden mentored over 500 engineers.

Embrace Ambiguity and Phase Delivery : Accept unclear paths during transformation, but ensure each phase yields economic benefit and remains adaptable.

What the C‑Suite Should Do

To cultivate 75–150 AI‑savvy domain owners (assuming 15–30 core domains per large enterprise), senior leaders should take three actions:

Select the Right People and Incentives : Assess current leaders, replace 20–30% if needed, and align performance metrics with AI goals.

Launch Strategic Upskilling Programs : Go beyond traditional courses; combine real projects, consulting partners, “dual‑leadership” (business + tech) models, and capstone experiences.

Reconfigure Operating Model : Embed engineering talent within domain teams, fund initiatives via a “persistent capital” model tied to roadmaps, and align KPIs with transformation outcomes.

Conclusion

McKinsey stresses that a cohort of domain owners who blend deep domain expertise with AI competence creates a hard‑to‑replicate competitive advantage. For Chinese enterprises, the message is clear: AI tools are easy to acquire, but talent is scarce; systematic development of the “second muscle” is essential to thrive in the AI era.