AI Has the Answers. Do You Have the Questions?

Generative AI can draft literature reviews in seconds and synthesise qualitative transcripts on demand. But in high-stakes DBA research, speed is not necessarily the bottleneck—cognitive control is. When you treat AI as an answer engine, who is actually directing your inquiry?

Join Jana Thiel, Associate Professor at EDHEC Business School and expert in entrepreneurship, entrepreneurial strategy and deep-tech entrepreneurship, and Professor Martin Wetzels, Full Professor of Marketing at EDHEC usiness School  and Academic Director of the Executive PhD in Business Management, for a session on using GenAI in research. 

In this webinar, we explore how you can harness the power of GenAI without surrendering critical thinking or scholarly ownership. We break down the Human-AI research relationship into three core stages:

•  Input: Who's in the Driver's Seat?
  How much of your problem definition and research scope should you feed into a model before it silently chooses your research question for you? How can you structure project context and prompting without ceding direction?

•  Process: What Is Reality?
  Context window limits, attention decay, and silent filtering can cause models to drop critical evidence while still crafting a smooth, convincing story. How do you structure your AI workflows—especially with complex qualitative data—so the tool doesn't make sampling choices behind your back?

•  Output: Asserting Judgment
  As AI agents operate with higher autonomy and multi-step execution, testing model outputs, auditing evidence trails, and retaining rigorous oversight over final research claims becomes key. How do you design robust human-in-the-loop verification protocols?

This session is particularly relevant for executives, doctoral candidates, and professionals seeking to incorporate GenAI into rigorous research and evidence-based decision-making.