What this helps you avoid
Licence theatre, vague pilots, unsafe data use, and automating processes that should be fixed first.
90-day AI adoption roadmap
90-Day AI Adoption Checklist
A practical sequence for moving from AI noise, unused licences and scattered experiments to useful workflows, clear governance and evidence-based next steps.
What you will map
Workflows, stakeholders, data readiness, risk, feasibility, adoption blockers, and ownership.
What the 90 days produce
Ranked use cases, a pilot shortlist, risk notes, kill criteria, and a practical adoption roadmap.
The checklist
The point is not to automate everything in three months. The point is to learn where AI is useful, where it is risky, and what the organisation needs before scaling.
Days 1-30
Diagnose and decide
- Inventory current AI tools, licences, experiments and shadow usage.
- Identify five to ten real workflows where AI is already being used or requested.
- Classify use cases by value, frequency, risk, data sensitivity and feasibility.
- Define unacceptable uses, human review requirements and data handling boundaries.
- Pick one or two low-risk, high-value pilots.
Output
AI adoption baseline, rejected or parked ideas, pilot shortlist and initial risk map.
Days 31-60
Pilot and govern
- Design pilot workflows around actual users, systems and decision points.
- Define success metrics before rollout: time saved, quality, error rate, adoption and cost.
- Confirm privacy, security and data protection constraints.
- Create lightweight usage guidance for staff.
- Test outputs against realistic failure cases.
- Decide whether each pilot should stop, continue or move toward production.
Output
Pilot evidence, governance notes, training needs and implementation decision.
Days 61-90
Operationalise
- Turn successful pilots into repeatable workflows.
- Assign owners for monitoring, prompt and workflow updates, vendor review and escalation.
- Add human-in-the-loop review where errors have business or legal consequences.
- Document model or tool choice, data flows, cost assumptions and known limitations.
- Plan the next-quarter rollout based on evidence, not hype.
Output
Practical roadmap, operating model, next use-case backlog and adoption metrics.
What runs through all 90 days
AI adoption works when business value, human judgement, data protection and technical reality are handled together.
Business value before automation.
Human judgement and accountability stay visible.
Privacy, security and data protection are designed in early.
Regulatory awareness covers Swiss and European expectations, including transparency, risk classification and monitoring.
Measurable outcomes matter more than tool adoption.
Download the checklist
Get the printable version and use it to pressure-test your first 90 days of AI adoption.