Part 6 of 7 in the AI Change Framework Series
Implementation delivers results; Sustainment makes them last. This stage invites organizations to shift from project mode to practice mode—from delivering pilots to integrating new ways of working.
Making Results Last
The invitation is to move beyond “Did it work?” toward “How do we keep learning and improving?” AI maturity is not a finish line; it's a living system that evolves with people, data, and strategy.
Guiding questions:
- What worked well enough to scale?
- How do we embed AI into daily operations without losing agility?
- How do we continuously evolve capabilities?
Creating Sustainment Briefs
Objective: Consolidate pilot learning for organizational memory.
For each completed pilot, host a reflection session (1–2 hours). Use prompts:
- “What impact did this create for customers, teams, or efficiency?”
- “What unexpected consequences emerged?”
- “What do we keep, drop, or redesign?”
Output: Sustainment Brief—a concise reflection summary.
Scaling Decisions (2 hours)
Objective: Determine which practices or tools should scale.
Facilitator grid: Value to Business vs Complexity to Adopt
- High value, low complexity → Scale immediately
- High value, high complexity → Invest in enablement
- Low value → Sunset or deprioritize
Agree on 2–3 candidates to move into standard operating procedures.
Governance Renewal
Objective: Refresh decision-making structures for the next cycle.
- Review AI governance policies—do they still fit?
- Update roles: who stewards AI now that it's operational?
- Identify new risk patterns from pilot experience
- Refresh communication channels for transparency
The Quarterly Rhythm
Objective: Track long-term value and evolve strategy.
- Produce a Quarterly AI Impact Report: metrics, stories, lessons, next priorities
- Track both hard data (ROI, efficiency) and soft signals (confidence, engagement)
- Close the loop: feed findings into strategic planning and next-generation pilots
“Sustainment doesn't end the framework—it renews it. Each quarter, the organization cycles back through assessment and design, ensuring AI remains a living, evolving advantage.”
Mastery Checklist
Sustainment has achieved mastery when:
- Successful AI workflows are embedded in standard operations
- Governance policies are refreshed and fit current needs
- Skills and confidence have grown across teams
- A quarterly reporting rhythm connects pilots to strategy
- The organization naturally cycles back to Assessment and Design
Artifacts to Produce
- ☐ Sustainment Briefs for all completed pilots
- ☐ Scaling decisions documented
- ☐ Updated governance guidelines
- ☐ Quarterly AI Impact Report published
- ☐ Next-cycle priorities identified
Previous: Stage 4: Launching AI with Learning Loops
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