Leading AI Adoption in the Space Between Change and Uncertainty

A three-hour interactive workshop for transformation leaders who carry the accountability for AI adoption — without always holding the authority to guarantee it.

Unlike previous change fatigue, AI adoption has no clear endpoint. Leaders are now expected to guide teams in real time, often without full control over outcomes or authority over key decisions related to data, governance, and accountability.

This session focuses on a key principle: effective AI leadership begins with personal reflection. Manisha Mistry and Jennifer Gervès-Keen will start with a live simulation of an AI adoption scenario. Participants will assess their own readiness, develop tools to determine which decisions should remain human-led, and explore how followership can drive influence, even without formal authority.

Research shows that organisations successful with AI are twelve times more likely to have leaders who are personally and actively engaged, rather than distant sponsors. Self-awareness, more than experience or confidence, is the strongest predictor of executive success.

This workshop builds self-awareness and provides practical tools to act on it.

You will leave with a personal playbook developed during the session and a practical followership strategy to implement with your team. This approach encourages collaborative adoption, leveraging your team's existing insights.

• A clear assessment of your current position in AI adoption, and how it is influencing your professional presence
• Practical tools to navigate ambiguity, identifying which tasks require human input and which can be delegated
• A structured followership approach to access and leverage your team’s existing insights
• A personalised playbook, developed during the session, ready for immediate implementation
• A clearer understanding of your readiness to recognise and act on your team’s existing knowledge
• Opportunities to connect with other transformation leaders at a similar stage of AI maturity