Incorporating AI tools like ChatGPT in education shifts the focus from generating answers to critically evaluating and refining them. Students must learn to ask specific questions and identify gaps in AI-generated outputs, enhancing their critical thinking and innovation skills.
I teach an undergraduate class where my students work as consultants to help real clients develop and test new business ideas.
Traditionally, this process involves teaching and guiding them how to build and test a business model from scratch.
But now, with tools like ChatGPT, the game has changed.
Students no longer need to start from a blank slate. With the right prompt, ChatGPT can generate an answer almost instantly.
However, the first answer is rarely the best one. The real work lies in refining it, and the quality of the final answer depends on their ability to ask more granular questions.
Example: A Business Model for a Sustainable Travel App
Let’s say the task is to develop a business model for an eco-friendly travel app.
A student might ask ChatGPT:
"What are possible customer segments and value propositions for an eco-friendly travel app?"
ChatGPT might generate this response:
- Customer Segments:
- Eco-conscious travelers.
- Corporate clients seeking carbon-neutral business travel.
- Local tour operators promoting sustainable tourism.
- Value Propositions:
- Reduce carbon footprint with green-certified travel options.
- Access exclusive eco-friendly accommodations.
- Tailored sustainable travel itineraries.
This is a good start. But it is not enough.
The Power of Granular Questions
At this point, students need to critique and improve the output. They could ask:
- “What assumptions are behind these customer segments?”
- “What are specific challenges corporate clients face when adopting eco-friendly travel solutions?”
- “What specific certifications or partnerships would make these value propositions credible?”
For question #2, ChatGPT might refine the response by adding insights about cost barriers, compliance requirements, or limited availability of options.
A New Role for Educators
This shift from developing answers to critiquing and refining means I need to change how I teach.
Instead of spending time scaffolding knowledge step by step, my role is to:
- Teach students how to evaluate the AI’s output critically.
- Guide them to ask more specific, impactful questions.
- Help them identify gaps or assumptions in the AI’s suggestions.
It’s no longer just about building. It’s about improving what’s built.
What This Means for Learning Innovation
With AI tools, students (and business owners) have incredible opportunities to accelerate their work. But speed alone doesn’t lead to quality. Asking the right questions, critiquing answers, and iterating are skills that matter now more than ever.
This shift isn’t just for students—it is for anyone using AI in their work.
How would you approach teaching or working with AI to support your innovation journey?