The Imbila AI Adoption Framework
A Step-by-Step Guide to Moving from AI Chaos to Structured Adoption
Most organizations struggle with AI adoption—not because they lack technology, but because they lack a clear framework for moving from experimentation to real business value.
The Reality:
- 86% of organizations are not fully ready for AI (Cisco, 2024)
- 60-70% are stuck in "Stage 1" with scattered experiments
- Most AI projects fail to move beyond pilot stage
This framework shows you exactly where you are, what's holding you back, and how to move forward—based on research from Gartner, McKinsey, Deloitte, and leading institutions worldwide.
Stage 0: Exploring
Just starting your AI journey with little coordination or strategy.
Stage 1: Experimenting
Scattered AI experiments with no clear ROI—"AI Chaos."
← Most companies are hereStage 2: Structured
Governance in place, successful implementations, ready to scale.
Stage 3: Scaling
Mature AI practices delivering clear ROI at scale.
Strategy & Governance
Clear direction and guardrails for AI adoption
- Documented AI strategy
- Executive sponsorship
- Governance policies
Data & Infrastructure
The technical foundation for AI success
- Centralized, quality data
- POPIA compliance
- AI-ready infrastructure
People & Capability
Building the skills and culture for AI
- In-house AI expertise
- Training programs
- Cross-functional collaboration
Execution & Measurement
Delivering results and proving ROI
- Production implementations
- ROI measurement
- Scaling capability
If You're in Stage 0-1: Exploring or Experimenting
- Conduct AI Readiness Assessment
- Develop AI Strategy
- Establish Governance
If You're in Stage 2: Structured Adoption
- Optimize Existing Implementations
- Expand Successful Use Cases
- Build Internal Capability
If You're in Stage 3: Scaling & Optimizing
- Deploy Enterprise Platform
- Establish Centers of Excellence
- Drive Innovation