Leadership & AI.
Two curations.

Leaders need first-hand experience of AI’s capabilities and limitations. Responsible experimentation helps them distinguish useful assistance from convincing errors, while keeping people accountable for the result.

A strong entry point for an executive audience with uneven AI experience. Mollick connects the technology with everyday knowledge work and gives the room a shared basis for discussing what to test, where to exercise judgement and what should remain a human responsibility.

The leadership challenge is to redesign work so that technological change strengthens the organisation’s capacity to learn, collaborate and adapt. New tools are only one part of that wider choice.

Gratton broadens the discussion from AI adoption to its consequences for people and the organisation. Her perspective suits leaders who need to think about capability, collaboration and careers together, and avoid reducing transformation to a short-term efficiency exercise.

Digital transformation depends on how people understand change, build trust and coordinate around new ways of working. Leaders need to develop the mindset and organisational conditions that make adoption meaningful.

Neeley connects the AI agenda with the leadership behaviours needed across functions and locations. She offers a useful lens for an international management audience facing different levels of confidence, resistance and readiness, with trust and collaboration central to the discussion.

Test AI in the work people actually do. Examine where it helps, where quality deteriorates and where a person must check the output; use those observations to guide decisions about deployment.

Retained from V1, with a sharper brief. His role in this selection is to connect practical experimentation with explicit human judgement: what should a leadership team test before extending AI use, and what evidence would justify changing a workflow?

AI changes more than individual tasks. Its strategic value depends on the operating model: the data, processes, responsibilities and feedback loops through which a business creates and delivers value.

Added because the revised question concerns organisational decisions. Iansiti helps frame the move from disconnected pilots to a coherent operating model, giving senior leaders a way to discuss ownership, cross-functional dependencies and the architecture needed to scale learning.

Start with the work, then consider the technology. Breaking activities into tasks and skills helps leaders decide what to automate, what to augment and where human contribution should be redesigned.

Added to make the discussion concrete for business and people leaders. Jesuthasan brings a task-and-skills lens to workflow redesign, helping the audience examine how responsibilities, capability needs and opportunities for people change when AI enters an existing process.