What happens when leaders are confident about AI, but the people expected to use it are not ready?
In this episode of Tech Talks Daily, I sat down with Caroline Grant from Slalom Consulting to explore one of the most persistent tensions in enterprise AI adoption right now. Boards and executives are spending more, moving faster, and expecting returns sooner than ever, yet many organizations are struggling to translate that ambition into outcomes that scale.
Caroline brings fresh insight from Slalom's latest research into how leadership, culture, and workforce readiness are shaping what actually happens next.
We unpack a clear shift in ownership for AI transformation, with CTOs and CDOs increasingly leading organizational redesign rather than HR. That change reflects how deeply AI now cuts across technology, operations, and business models, but it also introduces new risks.
Caroline explains why sidelining people teams can create blind spots around skills, incentives, and trust, especially as roles evolve and uncertainty grows inside the workforce. The result is what Slalom describes as a growing AI disconnect between executive optimism and day-to-day reality.
Despite the noise around job losses, the data tells a more nuanced story. Many organizations are creating new AI-related roles at a pace, yet almost all are facing skills gaps that threaten progress. We talk about why reskilling at scale is now unavoidable, how unclear career paths fuel employee distrust, and why focusing only on technical capability misses the human side of adoption.
Caroline also challenges assumptions about skill priorities, warning that deprioritizing empathy, communication, and change leadership could undermine effective human-AI collaboration.
We also dig into ROI expectations, with most UK executives now
expecting returns within two years. Caroline shares why that ambition is achievable, where it breaks down, and why so many organizations remain stuck in pilot mode. From governance and decision rights to culture and leadership behavior, this conversation goes beyond tools and platforms to examine what separates experimentation from fundamental transformation.
As AI becomes a test of leadership as much as technology, how are you closing the gap between vision and execution within your organization, and are you building a workforce that can keep pace with change rather than resist it?
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