Full Time

Ai Readiness Starts with Data Discipline Intro

AI Readiness Starts with Data Discipline

Vol. 2, Issue 10 Preparing for AI by strengthening the systems your business already depends on.  A Message from Matt Preparing for AI has quickly become a board-level conversation. But the questions I get are less and less about technology. They're more about confidence. Can we trust our data?...
The 3 AI Mistakes Mid-Market Companies Are Making

3 AI Mistakes Mid-Market Companies Are Making

Why AI Adoption Is Accelerating - But Competitive Advantage Isn't TL;DRAI adoption across mid-market companies is accelerating. But measurable competitive advantage remains rare. Three strategic mistakes are limiting financial impact: Starting with AI tools instead of business outcomes Skipping governance and acceptable use policies Measuring activity instead of financial ROI...
Why AI Fails Without a Data Warehouse

Why AI Fails Without a Data Warehouse

TL:DRMost AI initiatives don't fail because of bad models or tools. They fail because the data underneath them is fragmented, inconsistent, and ungoverned. A data warehouse provides the single source of truth AI needs to deliver accurate, explainable, and trustworthy outcomes. If AI is on your roadmap, the foundation matters...
A practical framework for mid-market executives to deploy AI with governance, measurable ROI, and durable competitive advantage.

AI Is More than a Strategy. It’s a Lever.

A Practical AI Strategy Framework for Mid-Market Companies TL;DRAI is not a strategy. It's a leverage mechanism. For mid-market companies, AI creates value in five ways: Generating output Predicting outcomes Automating processes Optimizing systems Scaling interaction The strategic question isn't whether to adopt AI. It's where AI materially impacts revenue,...