Brainstorming with AI

AI-supported brainstorming is a way to gather a wide range of ideas quickly and then select the most promising ones. Tools such as ChatGPT or Gemini help students generate, organise, and refine ideas. They can also reduce anxiety about being judged, giving less confident students more space to contribute and making classroom discussions more dynamic.

In teaching, AI can simulate real innovation practices such as iterative concept development, testing assumptions, and the rapid comparison of alternatives. As in start-ups, consulting, or research and development teams, students work in small groups and ask a tool such as ChatGPT to suggest answers to a specific question, for example: How can small businesses reduce emissions in transport and deliveries? AI generates a range of possible solutions, after which students begin to collaborate. They discuss the ideas, select the most promising ones, group them into categories, and refine those that are too general or unrealistic. As a result, students move quickly from initial ideas to concrete proposals that can be described, justified, and defended.

The method can be adapted to suit the aim of the class. In one version, students first generate ideas independently and then compare them with AI-generated suggestions. In another, the group evaluates and improves the responses produced by the tool.

A comparative variant can also be introduced, with different groups working with different prompts or tools and then analysing the differences in their results. Another useful option is constrained brainstorming, where AI generates ideas within specific criteria, such as budget, time, or regulations, making the proposed solutions more realistic

Course: Innovation Management
Topic: Searching for New Revenue Models
Students work in small teams to develop innovative business models for a digital banking application. Using AI as a creative partner, they move from defining the problem and generating ideas to evaluating solutions and delivering a short final presentation.

Warm-Up (10 min)
Present the challenge: How can digital banks develop new revenue models in the era of artificial intelligence and blockchain technology?

Students discuss trends such as sustainability, data monetisation, and personalisation in pairs or small groups. They then identify three to five barriers or opportunities. Examples should be specific, for instance focusing on the European market, Generation Z users, or green finance.

AI Brainstorming (10 min)
Each group selects one specific challenge and prepares a short prompt for AI, for example:

• Generate at least 10 innovative business models for a digital banking application using
  blockchain technology.

Teams then create a long list of ideas.

Filtering (15 min)
Students analyse and group the generated ideas using a shared board (Padlet, Miro, or a traditional whiteboard). They discuss which ideas have the greatest potential and select the most promising ones using simple criteria such as impact × feasibility or the ICE model

In-depth Analysis (20 min)
Each team selects its strongest idea and develops it further by considering questions such as:

• Who will benefit from this idea, and why now?
• What are the key resources or risks associated with it?
• How could the idea create unique value for both customers and the company?

Students complete a short Innovation Card summarising:

• the problem;
• the proposed solution;
• the value proposition;
• the business model;
• the next steps.

Presentation and Reflection (15 min)
Each group records or delivers a two-minute presentation proposing its solution. Participants then vote for the most creative and feasible idea using Mentimeter or paper voting slips. (Impact, Confidence, Ease).

• At the beginning of a course or project, when the aim is to spark curiosity and overcome the so-called “blank page” problem.
• In large groups, where AI can help balance participation and encourage more reserved students to contribute through writing rather than speaking.

• When students lack basic knowledge, as they may copy AI-generated answers uncritically.
• In tasks where originality and authorship are central to assessment.

• Students may copy AI-generated answers without reflection → encourage critical discussion.
• Maintaining ethical standards, including plagiarism and fabricated data → introduce clear, explicit rules on academic integrity.
• Participants may feel overwhelmed by the rapid flow of ideas → introduce time limits, use visual idea boards, and provide written guidance to make the process more predictable.

Easier → Provide structured prompts and pre-prepared topics. Ask the strongest group to present an example.
More Challenging → Ask students to compare AI-generated ideas with their own and explain the differences in a short reflective note.

• Keep the pace high and set clear time limits.
• Visualise ideas using online tools or sticky notes for grouping and ranking.
• Reward originality. During presentations, recognise unusual combinations of ideas.
• Ask students to generate ideas first and refine them afterwards.

Formative Assessment
Observe how teams discuss and filter AI-generated suggestions. Pay attention to collaboration, reasoning, and students’ ability to justify why certain ideas were accepted while others were rejected. A short reflective activity at the end can help consolidate learning.

Summative Assessment
A short final project (individual or group-based). Students prepare a one-page Innovation Canvas summarising their final idea, feasibility analysis, and proposed next steps.