How to Design AI That Earns Trust and Drives Adoption

As AI moves from answering questions to taking actions, organisations find themselves at a critical inflection point. The promise of agentic AI — systems that break work into steps, use tools, adapt to outcomes, and operate across business-critical environments — is compelling. But so is the anxiety it produces. When AI acts autonomously, the stakes of opacity rise dramatically.

This roundtable brings together practitioners to tackle the trust gap head-on. Drawing on four decades of IT evolution and four years of hands-on AI deployment, the discussion will explore why trust — not technology — is now the primary barrier to meaningful adoption, and what can practically be done about it.

Participants will examine how explainability, human-in-the-loop design, tightly controlled automation rules, and reversible actions can transform agentic AI from a perceived black box into a system people are willing to rely on.

Whether you are deploying AI in enterprise workflows, this session will offer concrete frameworks for making AI’s reasoning visible, its failures recoverable, and its value undeniable.