What is the first priority in month one?
Narrow workflow candidates and define success criteria clearly across KPI, quality, and cost.
2026 AI Adoption Strategy Framework
A 30/60/90-day strategy framework for 2026 AI rollout goals, KPIs, and execution priorities.
Updated: 2/25/2026
Key bullet summary
- Adoption success depends more on workflow redesign and ownership boundaries than model choice alone.
- Clear early metrics accelerate expansion decisions after PoC.
- Include security, permissions, and audit logging from day one to avoid late-stage rollout risk.
30/60/90-day adoption roadmap
| Phase | Duration | Core goal | Recommended KPI |
|---|---|---|---|
| Alignment phase | Days 0-30 | Select target workflows and define data/security guardrails | 3 priority workflows fixed, 100% risk checklist coverage |
| Experiment phase | Days 31-60 | Run workflow PoC and measure quality/cost | 20% cycle-time reduction, baseline error-rate established |
| Scale phase | Days 61-90 | Integrate into operations and lock ownership model | Higher monthly automation volume, 95%+ SLA compliance |
Clear conclusion
AI adoption is an operating design project, not just tool setup. Fix KPI and ownership boundaries together in 30/60/90-day cycles for sustainable scale.
Data Basis
- The 30/60/90 roadmap is structured from public operating case patterns and KPI practice.
- Security, access control, and audit requirements are included from the initial phase.
- Adoption performance is tracked across cycle time, error rate, and SLA compliance.
Sources
Execution priorities and KPIs should be reviewed regularly for each organization context.
AI Adoption Guide FAQ
Why do teams get stuck after PoC?
Permissions, governance, and incident processes are often defined too late, creating expansion bottlenecks.
Which metrics work best for executive reporting?
Show cycle-time reduction, automation rate, quality error trend, and operating cost movement together.
Next execution steps
Cross-check rollout plans with comparison, cost, and trend data.