Practical Insights on
Enterprise GenAI
Grounded in real-world engagements. No vendor talking points. No AI hype cycle commentary.
Why Most GenAI Pilots Fail to Scale (And How to Fix That)
The pattern is familiar: an enthusiastic pilot, strong demo results, then a slow fade as the project tries to move from proof-of-concept to actual deployment. Here's why it happens and what the organizations that succeed do differently.
Read MoreThe Shadow AI Problem: What Your People Are Already Doing With AI
Before you build a governance framework, you need to understand what's already happening. In most organizations, the answer is more than leadership realizes — and some of it creates real risk.
Read MoreAgentic AI: What It Actually Means for Enterprise Organizations
Agentic AI is getting a lot of attention. Some of it is genuine signal. Some of it is vendor noise. Here's a grounded look at what AI agents can actually do today, and what's still ahead.
Read MoreFractional CAIO: What It Is, When It Makes Sense, and When It Doesn't
The Fractional Chief AI Officer model is growing. For some organizations, it's exactly the right fit. For others, it's not the right move yet. Here's how to think about it.
Read MoreAI Governance That Actually Works: Lessons from Real Deployments
Good AI governance isn't about building a bureaucracy. It's about creating the right amount of structure so your organization can move with confidence. Here's what that looks like in practice.
Read MoreVendor-Agnostic AI Strategy: How to Navigate the Noise
Every major cloud vendor is telling you their platform is the right starting point for AI. Here's how to evaluate those claims independently — and make decisions that serve your organization, not their roadmap.
Read MoreWant to Discuss Any of These Topics?
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