OneRange

Download the AI Rollout Plan workbook

The workbook version of the OneRange AI rollout plan: fill-in worksheets your team completes together, covering readiness, use-case selection, pilot design, enablement, and measurement.

Guiding principles behind the plan

  • Train for judgment, not just tools — Tools change every quarter. The durable skill is knowing when to trust an AI answer, when to push back, and when to bring a human expert in.
  • Embed learning in real workflows — AI capability is built doing real work with AI in the loop, not by completing self-serve videos. Tie every training hour to a task someone actually owns.
  • Measure outcomes, not completions — Course completion rates do not predict business impact. Measure proficiency uplift, time-to-competency, and hours reclaimed per role.
  • Governance before scale — Acceptable-use policy, data classification, and approved tools must be in place before you push adoption org-wide. Otherwise shadow AI becomes your default.
  • Champions over mandates — One trained, motivated peer per ~25 employees moves the needle more than any executive memo. Invest in a champions network early.
  • Plan for a 6–12 month capability cycle — Generative AI capabilities reset roughly twice a year. Bake continuous reassessment into the operating rhythm — not a one-time rollout.

Phase 1: Assess (Weeks 1–3)

Baseline where you are before deciding where to go.

Most rollouts fail because they skip baselining. You cannot show ROI on a starting point you never measured.

Inventory the AI tools already in use (including shadow AI), the policies on the books, and any training delivered so far.

Measure current proficiency across the five core AI skills by team — not just leadership self-report.

  • Worksheet: Current state inventory — List the AI tools, policies, and training already in play. Include the unsanctioned ones.
  • Worksheet: AI Readiness baseline by team — Score each team (1=Beginner, 2=Intermediate, 3=Advanced, 4=Expert) across the five core AI skills. Use a short diagnostic — not self-rating — for honest numbers.
  • Worksheet: Top 10 candidate use cases — Brainstorm 10+ candidate use cases with line-of-business leaders. Score impact × feasibility (1–5 each). Prioritize the top quadrant for pilots.

Phase 2: Align (Weeks 2–4)

Set the governance and ownership that makes scale safe.

Acceptable-use, data classification, and a named accountable executive must exist before you push tools to the whole org.

Pair every AI initiative with a business sponsor — not just IT or L&D. If a P&L owner does not care, the rollout will stall.

Decide what is centralized (policy, procurement, security review) vs. federated (use-case selection, training delivery) up front.

  • Worksheet: AI acceptable-use policy checklist
  • Worksheet: Data classification → approved tools matrix
  • Worksheet: Steering committee RACI

Phase 3: Pilot (Weeks 4–10)

Prove value in 2–3 real workflows before scaling.

Pick 2–3 pilots across different functions. One pilot is too narrow; five is too diffuse to learn from.

Each pilot must have a named business sponsor, a real workflow (not a science project), and a measurable success metric.

Stand up a champions network in parallel — 1 trained peer per ~25 employees — so when you scale, you are not the only support channel.

  • Worksheet: Pilot charter — Complete one per pilot. Limit pilots to 6–8 weeks before a go/no-go decision.
  • Worksheet: Champions network — Recruit 1 champion per ~25 employees. Give them ~2 hours/week, a private channel, and direct line to the AI program lead.
  • Worksheet: Training plan per role — Sequence training as Foundational → Role-specific → Advanced. Plan for ~6–12 hours of structured time per employee in the first 90 days.

Phase 4: Scale (Weeks 10–24)

Roll out org-wide with embedded learning and manager enablement.

Scale by department in waves, not all at once. Each wave needs a champion, manager enablement, and a feedback loop.

Managers are the single biggest lever. If your managers cannot review AI-assisted work or coach AI use, adoption will plateau.

Move from one-off training to embedded learning — short, contextual, in the flow of work — backed by office hours and an internal community.

  • Worksheet: Rollout calendar by department
  • Worksheet: Enablement stack
  • Worksheet: KPI dashboard — Track these monthly. Report to the steering committee quarterly.

Phase 5: Embed (Ongoing)

Make AI capability a permanent part of how the company operates.

Treat AI capability the way you treat security or compliance: a permanent function with an owner, a budget, and a review cadence.

Reassess proficiency every 6 months. Models, tools, and best practices shift faster than annual training cycles can handle.

Bake AI competencies into hiring rubrics, performance reviews, and promotion criteria. Otherwise it stays a side project.

  • Worksheet: Quarterly review
  • Worksheet: Career-path criteria including AI competencies
  • Worksheet: Vendor & model review cadence

Appendices included in the workbook

  • Sample AI Acceptable Use Policy (1 page)
  • Sample 30-60-90 communications plan
  • Glossary
  • Credits & further reading

The full five-phase rollout playbook — readiness assessment, use-case selection, pilot design, enablement, and measurement, with owners and success criteria for each phase — is on this page, and the workbook turns it into worksheets your team fills in together.