AI-Native Capability Model
Turn AI ambition into organizational ability.
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7 domains · 28 capabilities · 84 building blocks
28 capabilities · 7 domains
The capability periodic table
Strategy & Value
- AI Strategy & AmbitionThe capability to set a shared direction for how AI should improve business outcomes.
- AI Opportunity DiscoveryThe capability to identify business problems where AI could create measurable value.
- Portfolio & Sourcing DecisionsThe capability to compare AI opportunities and decide what to fund, build, buy, or stop.
- Business Case & Value MeasurementThe capability to measure the business value of AI, including adoption and operating costs.
Work & Processes
- Process Discovery & EvaluationThe capability to understand how work flows, where it fails, and how success is measured.
- AI-Native Process RedesignThe capability to reshape work around business outcomes using human and AI contributions.
- Human-AI Responsibility DesignThe capability to assign work and decision ownership between people and AI systems.
- Outcome-Driven Process ImprovementThe capability to use outcomes and feedback to improve how work is performed with AI.
Knowledge & Context
- Enterprise Knowledge AccessThe capability to make approved organizational knowledge available for reliable AI use.
- Knowledge Ownership & LifecycleThe capability to keep organizational knowledge accurate, traceable, current, and appropriately retained.
- Organizational & Case ContextThe capability to assemble the role, task, and case information needed for a relevant AI response.
- Memory & Historical Outcome RetrievalThe capability to retain approved task state and retrieve relevant outcomes across AI interactions.
Agents & Automation
- Agent Reasoning & PlanningThe capability to turn a bounded goal into reviewable steps and adapt them as evidence changes.
- Authorized Tool UseThe capability to let AI perform authorized actions through controlled business and technical tools.
- Workflow & Agent OrchestrationThe capability to coordinate work across people, AI agents, and tools, including handoffs and task state.
- Exception Handling & Bounded AutonomyThe capability to detect AI task failures, stop unsafe actions, and enable recovery or human escalation.
Engineering & Platforms
- AI Application DevelopmentThe capability to build and maintain AI applications that meet business needs and integrate with existing systems.
- AI Evaluation & Release AssuranceThe capability to verify that AI systems meet task, safety, and operating requirements before and after release.
- AI Observability & Lifecycle OperationsThe capability to monitor, maintain, and safely update AI systems throughout their operating life.
- AI-Assisted Software EngineeringThe capability to apply AI across software delivery while retaining engineering judgment and quality controls.
Governance & Trust
- Agent Identity & Access ControlThe capability to identify AI actors and limit their delegated access to authorized resources and actions.
- AI Data Governance & ProtectionThe capability to control which data AI may process, disclose, retain, or transfer.
- AI Safety & Policy ControlsThe capability to prevent or contain prohibited AI outputs and actions through enforceable safeguards.
- AI Risk, Audit & AccountabilityThe capability to assign AI risk ownership and retain evidence for oversight and consequential decisions.
People & Organization
- AI Literacy & JudgmentThe capability to help people understand AI’s limits, judge its outputs, and recognize when to seek help.
- Builder Enablement & Shared PracticeThe capability to equip AI builders with supported tools, skills, and reusable implementation practices.
- Role Redesign & Change AdoptionThe capability to help teams adopt AI-enabled work through clear roles, support, and feedback.
- AI Enablement & Operating ModelThe capability to organize AI expertise, business ownership, and decision rights across the organization.