Implementing AI
6 posts on this topic — practical guidance from Shawn Livermore on fractional CTO, AI, and technology leadership.
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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