Employees are already pasting work data into personal AI accounts, and bans won’t stop it. The 3-tier shadow AI policy that works, with a template.
The Shadow AI Policy Your IT Team Actually Needs (With Template) Read More »
What an AI readiness assessment for IT teams covers: 24 scored questions, six dimensions, ranked risks, and a 90-day plan. Why scores beat opinions.
The AI Readiness Assessment for IT Teams: What It Covers and Why Scores Beat Opinions Read More »
The AI readiness framework explained: six dimensions, 24 questions, 0 to 4 maturity ladders, equal weights, and a floor rule. How the pieces fit together.
The 6-Dimension AI Readiness Framework, Explained Read More »
An AI readiness checklist for IT teams: 24 questions across data, security, infrastructure, skills, use cases, and governance, with the target for each.
The AI Readiness Checklist: 24 Questions to Answer Before Spending a Dollar Read More »
How an AI readiness score is built: 24 questions, six dimensions, a plain average, four bands, and the floor rule that caps a score when security lags.
What’s Your AI Readiness Score? How the 0–100 Scale Works Read More »
A 90-day AI plan that works: close risk gaps first, build foundations second, then run a pilot that proves value, with an owner for every action.
Your First 90 Days of AI: Risks → Foundations → Pilot Read More »
Microsoft Copilot readiness comes down to five fixes: oversharing, labels and DLP, access reviews, policy and training, and a measured pilot. In order.
Copilot Readiness: The 5 Things to Fix Before Rollout Read More »
Data readiness for AI isn’t perfect data. It’s five questions about the data your first use cases need. An audit worksheet you can finish in a week.
AI rarely creates new security problems. It exposes old ones faster. An AI security readiness scorecard, rollout red flags, and a 90-day plan.
AI Security Readiness: Closing the Gaps AI Exposes Read More »
These guides are written for IT leaders at mid-size organizations, roughly 200 to 5,000 employees, who are being asked whether the company is ready for AI. Each one takes a question from the AI Readiness framework, across data, security, infrastructure, skills, use cases and governance, and shows what good looks like and the practical steps to get there.
One sequence runs through all of them: close the risks first, then build the foundations, then run a measured pilot. Fix oversharing and publish a policy before licensing an assistant for everyone, and capture a baseline before any pilot starts. If your team needs structured skills to do the work, see AI Certifications.
Start with the 24-question checklist or the free AI Readiness Score, then work on your weakest dimension first.
