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 go-live.
Own UAT and drive adoption — the solution only counts if people use i...