The Modern Enterprise Architect's Handbook
A practical operating guide for turning enterprise strategy into coherent architecture, investable transition states, governance, and evidence.
- Enterprise architecture
- AI governance
- Transformation
Topic guide
AI governance for systems that can act.
Field guides and evidence-led briefs for leaders moving from AI experimentation to systems with data access, delegated authority, and real-world consequences.
16 field guides and insight briefs
Decision context
Govern the action, not only the model.
Useful AI governance connects each consequential workflow to accountable authority, enforceable limits, human oversight, evidence, and a measurable reason to operate. These articles examine the architecture and decisions that make those controls real.
Explore AI governance advisoryGraph RAG Is for Connected Evidence
A field guide to deciding when graph-enhanced retrieval is worth the extra machinery and how to pilot it safely.
- Graph RAG
- Connected evidence
- AI governance
AI is growing a spine
The spine metaphor explains the shift from AI systems that generate answers to agentic systems that carry intention into consequential action.
- Agentic AI
- AI governance
Harness Engineering: Designing the System Around the Model
The article argues that the durable enterprise advantage in agentic AI sits in the harness around the foundation model rather than in the model alone.
- Harness engineering
- Agentic AI
RAG Was Built For Answers. Agents Need Context Architecture.
Retrieval-augmented generation still serves search-shaped work, but agents need governed context across tools, permissions, workflows, memory, and state.
- Context architecture
- Agentic AI
Harvard Business Review Just Caught AI Lying to Every Executive in America
The article uses HBR and medical-query research to argue that LLMs should not be treated as strategists or oracles.
- AI strategy
- AI risk
Your AI Agent Remembers Every Secret It Sees
AI coding agents can leak secrets when shell output containing credentials enters the conversation context sent to a model.
- Agentic AI
- Secrets management
Overcome the 95% Failure Rate and Launch GenAI Pilots that Deliver
Why GenAI pilots fail when designed for demos instead of operations, and how to connect use cases to workflows, controls, evidence, and measurable value.
- GenAI
- AI implementation
Canada's AI Strategy: Building Infrastructure While Strengthening Governance
Canada's AI policy moment shifts from stalled legislation toward parallel investment in compute infrastructure, adoption, and stronger governance.
- Canada
- AI governance
When AI Systems Start Whispering in Code...
What machine-to-machine communication, autonomy, and public-sector adoption reveal about governing AI systems that interact beyond direct human supervision.
- AI news
- AI risk
The AI Power Struggle and the Future of Intelligence
This opinion piece argues that frontier AI development is increasingly concentrated among a small number of corporate and government actors.
- Open AI development
- AI governance
Alibaba Unleashes Qwen2.5-Max, and the AI Arms Race Just Went Supernova
An opinion analysis of Qwen2.5-Max and what rapid model competition reveals about AI capability, market concentration, governance, and strategic dependence.
- AI models
- AI risk
Advancing AI with Accountability and Fairness
How to turn AI accountability and fairness from statements of intent into operating controls, accountable ownership, reviewable evidence, and decisions.
- Responsible AI
- AI governance
Human-AI Teaming in the Age of Collaborative Intelligence
How collaborative intelligence changes AI from passive automation into an active partner, and what human oversight, role design, and accountability require.
- Human-AI teaming
- Collaborative intelligence
Responsible AI Implementation in Enterprise and Public Sector
A practical approach to responsible AI in enterprise and public-sector settings, connecting governance principles to controls, accountable owners, and evidence.
- Responsible AI
- Governance
Maximizing Cybersecurity with AI: A Comprehensive Guide to Applications, Strategy, Ethics, and the Future
This broad guide surveys AI's role in cybersecurity across defensive applications, strategy, ethics, human factors, and future outlook.
- AI security
- Responsible AI
Start a conversation
Turn ai governance evidence into a decision.
Bring the active choice, constraints, and available evidence. A short conversation can establish what must be decided and what still needs validation.