Self-Driving Cars and L&D: How We End Up Going The Wrong Way Faster

This session will review key insights from the research literature about the most effective strategies for Learning and Development through the lens of technology innovation theory. We will then evaluate those insights with a practical framework for determining where generative AI can extend, reinforce, and enhance our learning efforts, and where the human-in-the-loop becomes even more necessary to build dynamic, effective, and engaging learning experiences.

During this session, you will learn:

• How to spot “faster in the wrong direction” traps in L&D — recognizing when new technology accelerates existing (but flawed) approaches rather than actually improving learning outcomes
• What the research says about effective L&D strategies — grounded insights from technology innovation theory that separate genuine improvement from novelty for its own sake
• A practical framework for evaluating generative AI in learning design — a way to assess where AI genuinely extends, reinforces, or enhances a learning program versus where it falls short
• When and why human-in-the-loop still matters most — identifying the specific points in the learning experience where human judgment and involvement remain essential to keep programs dynamic, effective, and engaging

JD Peterson
Chief Marketing Officer
Perceptyx

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