AI Business Capability Directory
Explore granular definitions, L2 capabilities, and relevant tooling for each functional plane — from strategy and orchestration to security and governance.
AI Product Strategy & Value Orchestration
The ability to design and monetize AI-native systems by aligning core customer needs with causal value mechanisms, rather than just shipping static features.
AI Agent Execution & Orchestration
The capability to design, deploy, and manage autonomous or semi-autonomous AI agents capable of perceiving their environment, reasoning, making decisions, and executing complex, multi-step workflows.
AI Knowledge & Memory Management
The ability to curate, store, and provide low-latency access to the proprietary data and context required to ensure AI systems operate with high factual precision.
Unified AI Security & Threat Defense
The capability to protect AI systems from adversarial attacks and ensure the integrity of AI workflows at runtime.
Agentic Identity & Access Management
The ability to securely govern Non-Human Identities (NHIs) and AI agents by shifting from static, human-centric credentials to dynamic, intent-based access controls.
Agentic Software Engineering (SDLC)
The ability to seamlessly integrate AI agents as active team members within the software development life cycle, shifting human effort toward architecture and orchestration.
AI Data Security & Privacy
The capability to discover, classify, and secure sensitive data (PII, IP, secrets) as it is consumed, processed, or generated by AI models and workflows.
AI Evaluation & Quality Assurance
The capability to systematically measure, benchmark, and continuously validate the quality, accuracy, safety, and reliability of AI model outputs across development, staging, and production environments.
Model Infrastructure & Serving
The capability to select, customise, optimise, and serve foundation models at production scale — encompassing fine-tuning, inference acceleration, and multi-provider orchestration.
AI Governance, Ethics & Compliance
The capability to establish organisational policies, risk frameworks, and audit trails that ensure AI systems are developed and operated in compliance with regulatory requirements (EU AI Act, NIST AI RMF, ISO 42001) and ethical principles.