Enterprise AI Playbook

Five field guides on operationalizing AI in the enterprise. Each part ships as an architecture infographic, a deep-dive PDF you can hand to your team, and a readiness checklist — written from twenty-plus years of Fortune 500 platform work, in the same vendor-neutral spirit as the rest of this site.

By Tom Ward, Enterprise Architect — Cloud & AI

• Part 1 of 5 PDF

  Operationalizing LLMs as Enterprise Tools

  A six-layer operating model for taking large language models from promising pilot to governed, production-grade enterprise capability — demand, models, grounding, guardrails, delivery, and LLMOps, with governance as the spine.

  Read part 1
• Part 2 of 5 PDF

  Aligning AI Initiatives with Business Readiness

  A readiness model for matching AI ambition to organizational capacity across five dimensions — strategic fit, data foundation, platform & skills, process fit, and risk & governance — multiplied by the change capacity nobody budgets for. Readiness Gap = Ambition − Capacity.

  Read part 2
• Part 3 of 5 PDF

  Establishing Ethical, Accountable AI Governance

  How to turn AI principles into platform-enforced controls across five pillars — accountability chain, principles made testable, model risk management, controls as code, and evidence & audit — anchored to the NIST AI RMF and mapped to the EU AI Act and ISO/IEC 42001 so regulators recognize the vocabulary.

  Read part 3
• Part 4 of 5 PDF

  Leading Agentic AI-Driven Workflow Change

  What changes when AI stops suggesting and starts acting. A five-rung autonomy ladder (Assist → Draft → Propose → Supervise → Autonomous) and the five design decisions — delegation, permissions, human checkpoints, reversibility, trust — that must sharpen at each rung, over a human control plane that scales with autonomy.

  Read part 4
• Part 5 of 5 PDF

  Assessing the AI Stack from Infrastructure to Interface

  The finale, and the map back through the series: a five-layer reference architecture — compute & networking, data platform, model layer, orchestration, experience — scored on a four-level maturity scale, with security, cost, observability, and portability assessed at every layer. Know what you have, then decide what to build.

  Read part 5