You can't build what you can't see. Before investing in AI, you need to know where your organization stands today—and where it needs to be.
Executive Summary
- Capability gaps block AI success — Technology without capability leads to failure
- Five capability domains — Strategy, Data, Technology, Talent, and Governance
- Assessment before investment — Understand gaps before committing resources
- Prioritize by business impact — Not all gaps are equally important
- Build vs. buy vs. partner — Different gaps require different solutions
- Ongoing assessment — AI capabilities need continuous development
The Five AI Capability Domains
Strategy Capability
AI vision, use case prioritization, investment planning, executive sponsorship (/insights/ai-strategy-framework-guide)
Data Capability
Data quality, infrastructure, governance, accessibility (/insights/ai-data-classification-categorizing-data)
Technology Capability
ML platforms, deployment infrastructure, integration, monitoring (/insights/ai-monitoring-101)
Talent Capability
Technical skills, business skills, governance skills, broad AI literacy (/insights/ai-training-needs-assessment)
Governance Capability
Policies, risk management, approval processes, ethics (/insights/ai-governance-101-guide)
Capability Gap Assessment Matrix
| Domain | Current (1-5) | Target (1-5) | Gap | Priority |
|---|---|---|---|---|
| Strategy | [Score] | [Score] | [Delta] | [H/M/L] |
| Data | [Score] | [Score] | [Delta] | [H/M/L] |
| Technology | [Score] | [Score] | [Delta] | [H/M/L] |
| Talent | [Score] | [Score] | [Delta] | [H/M/L] |
| Governance | [Score] | [Score] | [Delta] | [H/M/L] |
Scoring: 1=Ad-hoc, 2=Initial, 3=Defined, 4=Managed, 5=Optimized (/insights/ai-maturity-framework-5-levels)
Risk Register: Capability Gap Risks
| Gap Area | Risk Description | Likelihood | Impact | Risk Level | Mitigation |
|---|---|---|---|---|---|
| Talent shortage | Cannot execute AI initiatives | High | High | Critical | Hire, train, partner |
| Data quality | Unreliable AI outputs | Medium | High | High | Data quality program |
| No governance | Compliance issues | Medium | High | High | Governance framework |
| Technology gaps | Cannot scale pilots | Medium | Medium | Medium | Platform investment |
| Strategy gaps | AI doesn't deliver value | Medium | Medium | Medium | Strategy development |
Development Planning Framework
Step 1: Prioritize Gaps
- Business impact
- Urgency
- Dependencies
- Effort required
Step 2: Select Approach
| Approach | Best For | Timeline |
|---|---|---|
| Build | Core differentiating capabilities | 6-18 months |
| Buy | Table-stakes, speed critical | 1-3 months |
| Partner | Specialized expertise | 1-6 months |
| Hire | Critical ongoing needs | 3-12 months |
| Train | Upgrade existing staff | 1-6 months |
Step 3: Create Roadmap
For each gap: target level, approach, actions, owner, timeline, success metrics
Checklist for AI Capability Gap Assessment
- All five capability domains assessed
- Current state scored objectively
- Target state defined based on strategy
- Gaps calculated and prioritized
- Risks identified (/insights/ai-risk-assessment-framework-templates)
- Development approach selected
- Roadmap created with owners
- Success metrics defined
- Regular reassessment scheduled
Frequently Asked Questions
Ready to Assess Your AI Capabilities?
Book an AI Readiness Audit for an objective assessment and prioritized development roadmap.
[Contact Pertama Partners →]
References
- MIT Sloan. (2024). "AI Capability Maturity Framework."
- McKinsey & Company. (2024). "Building AI Capabilities."
- Gartner. (2024). "AI Skill Gap Assessment Guide."
- Deloitte. (2024). "AI Readiness Assessment Framework."
Frequently Asked Questions
Annually at minimum. More frequently during rapid AI expansion or after major initiatives.
References
- AI Capability Maturity Framework.. MIT Sloan (2024)
- Building AI Capabilities.. McKinsey & Company (2024)
- AI Skill Gap Assessment Guide.. Gartner (2024)
- AI Readiness Assessment Framework.. Deloitte (2024)
