The accelerating adoption of AI across organizations is reshaping not just how work is done, but what leadership must look like in an AI‑augmented environment. A recent McKinsey & Company thought paper, Building Leaders in the Age of AI, highlights how emerging AI capabilities may alter the types of skills and leadership capabilities of future executive leaders.
We build on this McKinsey piece to help translate how many leadership realities introduced by AI raise important considerations for Chief Risk Officers (CROs) as they evaluate whether their organization’s succession planning itself may now be a material enterprise risk if AI’s impacts are not integrated into their organization’s leadership development strategy.
Why This Matters Now for CROs
AI has become a core lever in nearly every part of the enterprise—from operational decision support to strategic forecasting. Yet McKinsey’s core message remains unequivocal: AI cannot lead.
For CROs, this creates a dual challenge:
- Leadership competence in a world with AI is becoming a risk driver.
As organizations automate decision processes, the residual and non‑automatable decisions become more consequential—and are concentrated in the hands of human leaders. - Succession plans designed before AI may no longer be fit for purpose.
Many current leadership pipelines emphasize the capabilities needed for the pre‑AI era. McKinsey’s findings suggest that the leaders of the next decade need different, more human‑centered strengths.
This means that a leadership model that hasn’t been updated for the AI era may itself create risk exposure for an organization, particularly around strategic misjudgment, ethical blind spots, cultural deterioration, or failure to challenge AI‑generated outputs.
Where AI Creates Pressure on Leadership (and Risk)
McKinsey highlights three uniquely human leadership responsibilities: setting aspirations, exercising judgment, and designing for nonlinear outcomes. For CROs, these aren’t just leadership competencies—they are skills important for executives who own and manage risks.
1. Setting Aspirations and Mobilizing People
AI can analyze patterns, but it cannot motivate people to embrace a vision, build trust, or shift culture.
Risk implication: As organization further embed AI in its operations, they will want to be reminded that AI is less able to inspire, mobilize, or create psychological safety and it may under‑anticipate risks, not embrace dissent, or fail to align around risk priorities.
2. Exercising Judgment Anchored in Values
AI can outline options, but it cannot accept accountability. Human leaders remain responsible for prioritizing competing risks, resolving value conflicts, and making decisions under ambiguity.
Risk implication: Succession candidates who over rely on AI augmentation may lack judgment, humility, or ethical grounding leading to high‑stakes AI‑augmented decisions without sufficient skepticism or values‑based rigor. That leads to new risks.
3. Designing for Nonlinear Outcomes
AI builds its projections from existing patterns; humans imagine alternatives that have never been seen. The future of risk—climate, cyber, geopolitical, AI ethics—requires nonlinear thinking.
Risk implication: If potential leaders default to AI‑linear thinking, they may miss emerging risks entirely in a world that is changing dramatically at a rapid pace. Creativity is an important human leadership trait that will be hard to replace with AI.
Why Traditional Succession Planning May Be a Risk Exposure
Many succession systems still prioritize tenure-based progression, technical expertise, operational performance, and credential-based filters. But McKinsey argues that the traits needed in the AI age—resilience, curiosity, creativity, judgment, and collaboration—are deeply human and not captured well by traditional selection processes.
This gap represents an enterprise risk:
- Organizations may promote leaders who are excellent operators but poor “AI‑era decision makers.”
- Leadership pipelines may overlook talent capable of guiding AI‑augmented teams.
- Ethical and strategic risks increase if successors cannot distinguish between AI-generated outputs and human responsibility.
- Boards may believe they have succession risk covered when, in fact, the competencies needed have fundamentally changed.
A Clear Call to Action for CROs
CRO Question to the C‑Suite: Does our succession plan identify and develop leaders who can responsibly lead in an AI‑augmented environment—or are we preparing leaders for a world that no longer exists?
As CROs help lead the focus on risks linked to leadership development and succession planning, here are some key takeaways to consider:
| CRO Actions | Risk Considerations |
|---|---|
| Redefine leadership risk | Ensure AI integration in succession planning given AI increases the consequences of weak leadership. Poorly equipped future leaders become a top‑tier enterprise risk. |
| Evaluate succession plans through a risk lens | Ask whether your leadership pipeline reflects the actual competencies required to lead in an AI-augmented environment. |
| Partner with HR to modernize assessment methods | Move toward scenario-based interviews, values testing, and AI‑augmented simulations. |
| Elevate human-centric skills as risk controls | Remind decision makers of the importance of judgment, ethics, creativity, and resilience as core components of the organization’s leadership succession planning. |
| Position AI fluency as essential—but insufficient | Emphasize how leaders must understand AI deeply, yet remain grounded in the humanity AI cannot replicate. |
Final Thought
AI is transforming workflows. But only human leaders can transform organizations.
For CROs, the message from McKinsey is clear: if your leadership model isn’t evolving at the pace of AI, your succession plan may be your next major enterprise risk.
Read the McKinsey thought piece:
Bob Sternfels, Borge Brende, and Daniel Pacthod, “Building Leaders in the Age of AI,” McKinsey & Company, January 2026.
- Types:
