Here's a truth most executives don't want to hear: your teams are already using AI. They're drafting emails with ChatGPT, summarizing documents with Claude, and automating small tasks without waiting for permission.
The question isn't whether AI enters your organization. It's whether you'll shape how it's used—or react after something goes wrong.
Start by identifying low-risk, high-value use cases. These typically include internal documentation, meeting summaries, first drafts of communications, and brainstorming support.
Create psychological safety for experimentation. Teams that hide their AI usage can't share learnings or flag concerns. Make it acceptable to say, "I used AI to help with this."
Invest in prompt literacy. The gap between amateur and effective AI usage is largely about knowing how to ask. Basic training pays immediate dividends.
Unreviewed external communications. AI can draft, but humans must review anything going to customers, partners, or regulators.
Sensitive data in consumer AI tools. Until you have enterprise agreements with proper data handling, confidential information shouldn't touch free AI tools.
AI for final decisions on people matters. Performance reviews, hiring decisions, and terminations require human judgment and accountability.
Focus governance on three areas: data classification (what can touch AI systems), output review (what needs human approval), and vendor management (which AI tools are sanctioned).
Skip the 50-page policy document. Create clear, memorable guidelines that people can actually follow. A simple framework used consistently beats a comprehensive policy that's ignored.
The leaders who thrive in the AI era won't be those who moved fastest or slowest. They'll be the ones who created clarity for their teams while the landscape was still shifting.