Discover and shape AI use cases

• Run discovery workshops with business and technical stakeholders, and separate the AI ideas worth building from the ones that aren't ready.
• Assess feasibility on the merits — data availability, process fit, risk, cost

Design the AI experience (UX)

• Define how people interact with the AI: conversational and agent flows, copilot interaction patterns, how confidence and sources are surfaced, error and fallback states, and expectations around latency and streaming.
• Decide where the AI should be visible, where it should stay in the background, and where a human stays in control.
• Partner with UI/UX designers to turn this into real interface design, and make sure the experience feels trustworthy and usable rather than gimmicky.

Drive value and adoption

• Build the value case up front (effort saved, deflection, cycle-time, quality) and measure realisation after ...