Implementing AI
8 posts on this topic — practical guidance from Shawn Livermore on fractional CTO, AI, and technology leadership.
Who Should Own AI in Your Company
Only 24% of organizations assign a single executive to own AI outcomes. Distributed AI ownership looks like accountability — and produces none.
Read post →Why Most SMB AI Projects Fail to Scale
The failure-to-scale rate for SMB AI projects is above 80% in 2026. The cause is almost never the model. It is the data foundation and accountability structure that the model was supposed to operate on.
Read post →Most SMBs Are Using AI. Few Are Implementing It.
The adoption numbers for AI in small and midsized businesses look strong. The implementation depth — where AI actually changes how operations run — is much thinner. Understanding the gap is the first step to closing it.
Read post →The First AI Automation a Small Business Deploys Matters More Than the Tools It Uses
The first AI automation a small business deploys either builds internal confidence or depletes it. Which process you automate first determines whether AI adoption accelerates or stalls.
Read post →The AI Implementation Gap: What Mid-Market Companies Keep Getting Wrong
Anthropic and Blackstone just bet $1.5B that implementation — not model quality — is the AI bottleneck. Here is why mid-market companies consistently fail on this exact point and what the sequence should actually look like.
Read post →Building an AI Business Case for Your Small or Midsized Business
89% of small businesses have adopted some form of AI. The ones seeing meaningful returns built a business case first — before the tool selection, not after.
Read post →AI Implementation Sequencing: What Mid-Market Companies Get Wrong About the Order
Most mid-market companies invest in AI in the wrong order. The highest-ROI use cases are rarely the ones that get funded first. Here is what the correct sequencing looks like.
Read post →AI Automations Without a Developer: What Actually Works in 2026
No-code AI automation tools have matured, but the gap between what they promise and what they reliably deliver is wide, and architecture judgment still matters.
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