Description

In this interactive workshop, we’ll explore how AI can support business research, learning, and problem-solving while also examining the limitations, assumptions, and risks that come with AI-generated information. Participants will practice evaluating outputs, identifying red flags, validating claims, and determining what makes AI-generated research genuinely useful in a real-world business context. 

Throughout the session, we will: 

• Explore a practical framework for assessing whether an AI-generated output is credible, useful, and appropriate for business decision-making. 
• Compare traditional business research methods with AI-assisted research to better understand the strengths, gaps, assumptions, and tradeoffs of each approach. 
• Learn how AI can help entrepreneurs quickly understand unfamiliar concepts, current events, technical topics, regulations, and business terminology — especially when they need a fast starting point for learning. 
• Examine high-profile AI failures and breakdowns to better understand how hallucinations, weak sourcing, bias, flawed assumptions, and automation errors occur. 
• Practice reviewing sample AI outputs to identify unsupported claims, vague sourcing, misleading statistics, overgeneralizations, and hidden assumptions. 
• Learn lateral reading and research validation techniques to fact-check AI-generated information and trace claims back to credible sources. 
• Discuss when AI is an appropriate tool for a business problem — and when another approach may be more effective. 
• Apply these concepts to realistic business examples and a possible photography-industry case study focused on market research and decision-making. 

Rather than treating AI as a replacement for expertise, this session focuses on how entrepreneurs can use AI thoughtfully as a research assistant, brainstorming partner, and learning tool while remaining the decision-maker and “human in the loop.”