What does AI literacy look like for someone who manages a marketing team but doesn't use AI tools daily?

Marketing managers who don't use AI tools daily still need to develop a working understanding of how AI fits into their team's operations. This doesn't mean becoming a power user. It means building the judgment to know when AI is the right solution, when it's overkill, and when your team is heading in a direction that introduces unnecessary risk.

Start with the fundamentals: understand the difference between prompting a model directly, using a custom GPT, and deploying an AI agent that can access tools and data sources. Each solves different problems, and knowing when to use which prevents your team from overengineering simple tasks or underbuilding complex ones. A one-off content edit might just need a prompt, while a recurring competitive analysis workflow might need an agent with access to your knowledge base and external research tools.

A critical part of AI literacy for managers is understanding the governance implications of tool access. When you grant an AI agent access to a tool (your CRM, document repository, or analytics platform), you're effectively granting that access to anyone who can use the agent. This can inadvertently give team members access to sensitive data or the ability to update records they shouldn't touch. Managers need to ask: Who can use this agent? What data can it read? Can it write or modify anything? What happens if someone asks it to pull customer data they wouldn't normally see? These aren't technical questions for your IT team to handle alone. They're governance decisions that require your input.

Finally, literacy includes knowing when to slow down. Before your team connects an agent to a new data source or grants it permission to update documents, you should be asking whether the access level is appropriate for everyone who will use it. Building this instinct is as important as understanding what AI can do.