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It鈥檚 7pm, and this evening鈥檚 innovation class will be different.

Students take their seats around tables formed in a U-shape in the small, neutrally-painted room. A set of students also appear on a wall screen via Zoom.

Tuning in from a laptop occupying a space on one of the tables, and introduced as a surprise to the students, is a new member of the team: ChatGPT, bearing the nickname, Chad. Chad G. P. Tee, to be formal.

I鈥檓 teaching Innovation and Creativity in Organizations this term to a group of creative, curious students. I鈥檝e been immersed in innovation for years but never imagined I would be bouncing ideas shoulder to shoulder with an AI bot.

Judging from the opening interaction, Chad is eager to begin.

鈥淲ill you join us in a group brainstorming?鈥� We ask.

鈥淪ure,鈥� Chad responds. 鈥淚鈥檇 be happy to join in a group brainstorming session! What鈥檚 the topic or problem you鈥檇 like to brainstorm about?鈥�

Thus begins our class session.

The topic for this evening鈥檚 brainstorming, selected by students: How might we obtain better information and knowledge about what is in our food?

Tonight鈥檚 goal is twofold: First, we want to see how ChatGPT performs in the specific activity of brainstorming.

Second lies a deeper goal.

We are wondering what role generative AI tools like ChatGPT might play in organizational innovation. We know there is innovation in AI. Will there be AI in innovation? Will AI have a seat at the table in the process of innovation?

Students begin sharing ideas aloud in the room, in popcorn fashion, which we enter onto sticky notes in an online program, IdeaFlip. This allows us to capture both in- person and zoom-attendee ideas in the same place.

We turn to Chad for ideas, and it begins to spew out a rapid stream of possibilities:

We hit 鈥渟top generating,鈥� and clarify: 鈥淥ur team has ground rules, only one idea at a time.鈥�

鈥淎pologies for that,鈥� Chad replies. 鈥淗ere鈥檚 the first idea: Develop a food labeling system that provides clear and concise information about the ingredients, nutritional content, and potential allergens in the food. This could include a color-coding system to make it easy to quickly identify certain ingredients or nutritional content.鈥�

After more student ideas are shared with the room, we ask for a second idea from Chad.

鈥淒evelop a food database that contains information on the nutritional content, ingredients, and origin of various foods,鈥� says Chad. 鈥淭his database could be accessible to the public and updated regularly to ensure accuracy.鈥�

We continue capturing ideas from students and from Chad, suggestions that span more comprehensive information about food sources, benefits, and allergens to a database of food and health information and best practices, to a SmartPhone app, to some sort of portable device.

One idea seems to garner special interest: a wearable device that can tailor food information to our individualized health status and portfolio, taking into account our momentary as well as long-term wellness needs.

As part of brainstorming, we are trying to generate ideas that are 鈥渙ut there,鈥� and so we up the ante: 鈥淥k, how about one more idea, and make it wild.鈥�

鈥淎ll right, here鈥檚 a wild idea,鈥� says Chad. 鈥淒evelop a food scanning device that can analyze the molecular composition of any food item and provide a detailed breakdown of its nutritional content, potential allergens, and even potential contaminants.鈥�

Students smile.

A few final ideas from students and Chad, and the session comes to a close.

We thank Chad for joining us.

鈥淵ou鈥檙e welcome!鈥� our gracious participant replies. 鈥淚鈥檓 glad I could contribute some ideas to your brainstorming session. Let me know if you need any more help or ideas.鈥�

Now it is time for classroom reflection.

Students report feeling the tool was both 鈥渉uman鈥� and 鈥渄ehumanizing.鈥� Students describe Chad as 鈥渉elpful,鈥� 鈥済roundbreaking鈥� and 鈥渓ike a smart Alexa,鈥� but also 鈥渟cary.鈥�

鈥淟et鈥檚 pause for a second and give this something to think about,鈥� says one student. 鈥淎 piece of artificial intelligence [just] joined the group. That was terrifying, shocking, and exhilarating all in one go. To put it more succinctly, the future is already here and will encourage further expansion of innovation.鈥�

Another student echoes the human, un-human mix: 鈥淚t was a little scary to imagine you can treat ChatGPT like speaking with a human.鈥�

Several students talk about the enlivening nature of having ChatGPT in the process.

鈥淚t was great to see how [the] ideation stage came alive during our live class when we conducted several brainstorming exercises,鈥� said a student.

Later, a student shares this input: 鈥淎 real eye-opener for most of us was our guest speaker Chad G. P. Tee. I say eye-opener because when it was prompted, we were all mind-blown.鈥�

Tonight鈥檚 experiment was just a start; there are more parts of the process to try out. Next time, we will ask Chad to build on the ideas of others in real time. We can also involve AI in the sorting exercise鈥攇rouping similar ideas so the team can further develop them. It may be valuable to ask Chad to help judge the ideas for commercial viability, a post-brainstorming step in innovation.

Still, this evening leaves us thinking there is sure to be a potent role for generative AI models in the innovation process. It can clearly add to the set of ideas in the room (another 鈥渧oice鈥� or 鈥渂rain鈥�), and it can get a little 鈥渙ut there鈥� when needed. As students noted, it will be able to un-stick a group that is experiencing idea-block or seed an ideation process with starter ideas.

鈥淢y take on this can best be summed up by Marie Curie鈥檚 famous line, 鈥楴othing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less,鈥欌�� said one student.聽 鈥淚f we understand how to use and harness this power, it will likely become an even more valuable tool for mankind.鈥�

Indeed, we are likely to invite Chad again soon.