The problem this solves
AI initiatives rarely fail on technology; they fail on adoption. The pattern: leadership announces the AI push, a pilot group experiments enthusiastically, and six months later most of the team works exactly as before, because nobody assessed who had the skills, the time, or the incentive to change. Meanwhile anxiety fills the communication vacuum, and the people whose workflows AI would change most were consulted least.
How we work
We assess readiness at three levels. Individual: current AI literacy across roles, from daily power users to people who have never touched a prompt, mapped without embarrassment or blame. Team: how work is structured today, and whether existing processes have room for AI-assisted steps or would need redesign. Organizational: incentives, time budgets, and whether anyone is actually resourced to support adoption after the launch enthusiasm fades.
Method is interviews and a structured skills survey, plus a review of how earlier tool rollouts went in your company, because past adoption behaviour predicts future adoption behaviour better than stated enthusiasm does.
The output is a readiness map by team and role, a skills gap analysis, and a concrete adoption risk assessment: who will run ahead, who will need structured support, and where the initiative is most likely to stall. It feeds directly into training strategy and change execution work.
Deliverables
- AI literacy baseline across roles and teams
- Workflow absorption assessment showing where AI fits current ways of working
- Adoption risk map identifying likely champions and likely stall points
- Skills gap analysis with role-specific development needs
- Readiness findings report with prioritized enablement recommendations