INSIGHTSSignal, not hype.
What's actually changing in AI, what it means for the people running a business, and what we're learning as we take organizations through the framework.
What Company Data Should Never Go Into a Public AI Tool, and How Do We Classify the Rest?
Trade secrets, personally identifiable information and regulated data stay out of public AI tools. A four-tier classification ties every kind of company data to a rule for which AI tools may handle it.
What Controls Should We Have in Place Before Letting an AI Agent Access Our Email, CRM, or Financial Systems?
Five controls belong in place before an AI agent gets credentials to your email, CRM or financial systems. Here is what each one does, how much autonomy to grant at the start, and who should own the decision.
Should We Standardize on One AI Platform, or Let Teams Choose Their Own Tools?
Left unmade, the AI platform choice doesn't stay open — it gets made department by department, by default. Here's why AITF ties governance to a single named platform, and what belongs in the contract before you commit.
What Does an AI Readiness Assessment Evaluate, and Why Should Executives Prioritize It?
An AI readiness assessment scores five categories before any strategy work begins — data, leadership usage, vision, policy, and technical skill. Here's what each one measures, and what AITF found when it ran the assessment on itself.
What Is Shadow AI, and Why Is It a Governance Risk for Growing Businesses?
Two-thirds of employees say they've used AI tools they believe violate company policy. Here's why blocking it backfires — and the no-penalty process that gets shadow AI into the open before you write a policy.
What Should We Ask an AI Vendor About Privacy, Retention, Training and Indemnification Before We Sign?
Data handling, security, compliance, access scope, and how fast you can shut it off. Five questions settle most of what gets expensive after a contract is signed — and the order you ask them in matters.