Turning Change Data into Leadership Intelligence
Project Overview
Our global life sciences client’s AI Data and Content Generation program was established to accelerate AI-enabled data and content generation across the end-to-end R&D development lifecycle.
As the program entered full-scale execution, stakeholder excitement was high, but understanding of the program purpose, governance model, delivery approach and expected outcomes was inconsistent across multiple R&D functions, delivery partners and leadership teams. Success depended on one coherent view connecting its vision, value, roadmap and governance with what the transformation would mean for diverse stakeholder groups.
Afiniti used the engagement as a pilot for its AI-Aided Change Workbook and dashboard approach, creating a connected, always-on view of change that helped leaders understand impacts, readiness, engagement needs and adoption priorities at pace.
Our Solution
Afiniti combined its structured change methodology, AI-aided analysis and expert human judgment to rapidly connect program evidence, stakeholder perspectives and delivery information. The AI-Aided Change Workbook provided the data spine, while our consultants interpreted and validated the findings to identify where change was concentrated, where adoption risk was emerging and what action was required.
- AI-aided workbook pilot: Built a governed change workbook to connect stakeholder analysis, impact assessment, communications, learning, readiness, mitigation actions and feedback loops into one evolving source of change insight.
- Accelerated data build: Used AI to consolidate workshop outputs, meeting notes, stakeholder feedback and program artifacts into reviewable workbook content, reducing manual administration and analysis.
- Always-on dashboard view: Translated thousands of data points into a clear- leader-ready dashboard reporting showing who was most affected, where risks were emerging, which interventions should be prioritized and where leadership attention or decisions were needed.
- Human-led interpretation: Kept consultant judgment, challenge and client validation at the center, with the AI-Aided Change Workbook supporting synthesis and structure rather than making change decisions.
The Difference We Made
“This clarity will be instrumental in driving the adoption of AI and new ways of working.”
AIDCG Business Lead
- Accelerated delivery: Reduced the workbook delivery timeline by around 40%, completing the pilot in 7 weeks rather than the 12 weeks expected through traditional approaches.
- Scaled the insight: Connected 4,500+ change data points across 64 stakeholder groups, 32 impacts, 62 communications activities, 38 learning interventions, 36 readiness measures and 14 mitigation actions.
- Improved decision-making: Helped leaders surface adoption risks earlier, prioritize stakeholder interventions and identify high-impact areas of change.
- Created a reusable model: Demonstrated a scalable AI-aided change intelligence approach that could support multiple AI use cases and future deployment across the client.
The result was not simply faster production of change outputs. It was a connected, evidence-based view of the transformation that leaders could understand, challenge and act upon.
Discover more AI in Business Change
Read our Insight article exploring the benefits and limitations of using AI in change management
