Why AI Demands a New Breed of Leaders

Artificial intelligence is fundamentally transforming how organizations operate, but this transformation extends far beyond technical implementation. Modern AI systems are increasingly taking on roles that previously would have been filled by human workers. People working alongside these AI systems often need reskilling, upskilling, and training in behavioral traits such as critical thinking. To successfully manage this blend of AI tools and humans working together in new ways, leaders need to understand complex human and organizational factors, such as agility and cultural change, personality dynamics, and emotional intelligence.

Yet most organizations continue to treat the implementation of AI as a primarily technical challenge — and current technology leadership roles reflect this mindset. According to Foundry’s 2024 State of the CIO survey, 85% of IT leaders say that CIOs are increasingly becoming changemakers in their organizations, but only 28% call leading transformation their top priority. In another recent survey, 91% of large-company data leaders said “cultural challenges/change management” are impeding organizational efforts to become data-driven. Only 9% pointed to technology challenges.

But instead of focusing on the aspects of cultural and organizational change that are relevant to AI, much of the time and effort of IT and data leaders is spent on operational functions, long seen as the bread and butter of these roles. This operational focus seems to be increasing: Sixty-one percent of CIOs in the Foundry survey reported having less time available for strategic responsibilities over the past year than in previous years.

Although AI-enabled transformation clearly has enormous human and organizational implications, HR leaders have, for the most part, not stepped up to deal with such changes either.

When leaders fail to think through the strategic and organizational consequences of their AI plans, the results can be catastrophic. Zillow’s failed attempt to use AI-generated property valuations as the basis for its own homebuying division not only cost the company $300 million in losses but also saw its stock price fall by more than 20% as investors lost confidence in its ability to navigate the AI transformation. In another example, California State University had a clear strategic vision but failed to account for the human element.