Your core outcome is a clearly defined Use AI strategy and a concrete rollout plan that reaches every practice, not a set of one-off activities.
Within the first two weeks of engagement, the capabilities, the rollout plan, and the roadmap are identified. From there the agenda is implemented against OKRs the candidate helps define alongside leadership, and monitored continuously so adoption compounds rather than stalls. Success is scale: a repeatable enablement model, built once with a flagship practice, then rolled out and adapted across the full portfolio.
You will lead the Use AI Agenda for Practices by owning end-to-end delivery of the Use AI agenda across the practice portfolio. You will also develop the strategy and translate it into a clear rollout plan and roadmap, then into tangible, measurable outcome. You will identify capabilities, rollout plan, and roadmap within the first two weeks of engagement, then implement against OKRs defined with leadership and monitor them continuously.
You will also build and facilitate learning experiences by facilitating sessions across practices, refreshing modules quickly based on field signal. You will also run activations and sprints end to end, prep materials, deliver live labs, drive micro-reinforcement, host office hours and clinics, and provide targeted 1:1 support to convert learning into daily use.
You will be required to produce practice-ready assets by drafting role-based playbooks, prompt packs, job aids, and safe-use guides that fit practice tools and workflow. You will also maintain curated libraries of top workflows, prompts, and Agents through user interviews and field observation; keep content current and organized for reuse
You will help execute releases and campaigns. You will ship timely pre-work, crisp follow-ups, and field-ready assets in support of practice rollouts and campaign and attend and contribute to the weekly sync; keep stakeholders informed on the request pipeline and progress.
You will measure and report outcomes by defining and tracking the target AI proficiency OKR for each practice, report progress toward the target, and flag gaps early so they can be close and reviewing outcomes against the defined OKRs weekly, so the rollout plan is adjusted on real field signal rather than assumption.
