Giving employees access to AI tools does not mean they will use them effectively, responsibly, or consistently. Even a successful course can have limited impact if employees return to work without changing their habits.

For Northeastern University’s Custom Learning team, behavior change means more than increased AI usage. It means employees can recognize where AI is appropriate, apply it to their work, evaluate what it produces, and make better decisions about when to use it, when to question it, and when not to use it at all.

During our recent AI in Action event, From AI Panic to AI Progress, one leader asked:

“What is the best way to get 1,000 employees thinking about and using AI in some form every day?”

This next installment in the AI in Action series takes that question one step further: How do you help employees use AI regularly while also using it effectively?

Northeastern University’s Zach Blattner, director of partner products and programs and Berkeley Almand-Hunter, technical director for partner programs, will explain how experiential, role-relevant learning helps employees move from learning about AI to applying it confidently in their everyday work. They will examine the conditions that turn learning into lasting behavior, including hands-on practice, immediate relevance, responsible-use guidance, manager reinforcement, and opportunities for continued application.

From Learning to Behavior Change

Effective AI learning should change more than what employees know. It should change how they work:

• Recognizing tasks and workflows where AI could add value
• Choosing when AI is appropriate and when it is not
• Applying AI to role-specific work
• Evaluating outputs instead of accepting them automatically
• Refining approaches based on results
• Sharing and reinforcing better practices across teams

What You’ll Learn

• Why tool access and course completion are not the same as workforce capability
• How experiential learning helps employees transfer new skills into real work
• What builds confidence without encouraging overreliance on AI
• How relevance, practice, feedback, and repetition contribute to behavior change
• What leaders and managers can do to reinforce effective AI practices
• How to measure changes in application, judgment, workflows, and performance

Who Should Attend

Designed for executives, HR and learning leaders, transformation and innovation teams, department leaders, and others responsible for building workforce AI capability.

Move beyond counting licenses, course completions, or isolated experiments. Join the next AI in Action conversation to learn how organizations can help employees use AI well and turn learning into lasting workplace behavior.