Cross-Cutting Enabler
Operational Readiness
Platform, process, and people readiness for production-grade AI.
Operational Readiness is the combined readiness of platform (MLOps, infrastructure), process (delivery, incident, change), and people (skills, roles, culture) to run AI in production safely and sustainably. It is a cross-cutting concern that must be assessed in Calibrate, designed in Model, and proven before the Produce-to-Evaluate gate.
Core articles
- M1.4The AI Technology Landscape
- M1.4Machine Learning Fundamentals for Decision Makers
- M1.4Deep Learning and Neural Networks Demystified
- M1.4Generative AI and Large Language Models
- M1.4Data as the Foundation of AI
- M1.4AI Infrastructure and Cloud Architecture
- M1.4MLOps: From Model to Production
- M1.4AI Integration Patterns for the Enterprise
- M1.4Emerging Technologies and the AI Horizon
- M1.4Technology Decision Framework for Transformation Leaders
- M1.4Agentic AI Architecture Patterns and the Autonomy Spectrum
- M1.4Tool Use and Function Calling in Autonomous AI Systems
- M1.5Model Governance and Lifecycle Management
- M3.3Technology Architecture as Strategic Capability
- M3.3Enterprise AI Platform Strategy
- M3.3Data Architecture for Enterprise AI
- M3.3Multi-Model Orchestration and AI System Design
- M3.3AI Security Architecture
- M3.3Scalability and Performance Architecture
- M3.3AI Infrastructure Economics and FinOps