Since the end of 2022, ChatGPT and other new generative artificial intelligence (AI) tools have begun to disrupt long-established business processes, functions, and professional roles with the prospect of significantly boosting productivity, effectiveness, and speed in business. But how can these tools augment human creativity? And in particular, how can we employ generative AI in workable, meaningful ways in the creative process? 

In part 1, I shared my initial experiences on how generative AI tools can support an innovation team at the front end of the creative process by broadening the perspectives of an innovation team during Xploration and boosting its idea quantity during Ideation. In today’s second and final part, let’s discuss how we can include —and intentionally choose to exclude— generative AI in the remaining three stages of X-IDEA (Development, Evaluation, and Action).

Stage D-Development: Use AI only to further humanly designed concepts

In the Development stage, we aim to turn idea quantity (hundreds to a thousand raw ideas generated during Ideation) into idea quality by developing a portfolio of relevant, realistic, and ideally meaningful idea concepts. We do this in three steps (Discover, Design, and Develop):

• First, we ask the human members of an innovation team to Discover the vital few intriguing ideas within the larger pool of raw ideas (including those that were AI-generated). Typically, 80% of the raw ideas get left behind, and the innovation teams continue working with those ca. 20% of intriguing ideas having an interesting or wild aspect.
• In the second step, the team members, individually or in small buddy teams, Design selected intriguing ideas into realistic idea concepts by employing the three principles of idea design - elaboration, combination, and transmutation.
• When we Develop the designed concept further in the third step, however, we can opt to invite generative AI back to help the innovation team expand on all concepts and add further value to them (e.g., by having generative AI run  them through the D Tool SCAMPER).

Overall, I propose limiting AI use in this second creative process stage. I suggest letting only human creators carry out the two central steps (of the Development-stage, Discovery and Design, as they also require unique human qualities like intuition, empathy, value perceptions, aesthetics, and psychological aspects of design. And besides, wouldn’t it be good to give generative AI some downtime here to prevent a non-human intelligence from performing the entire process all by itself?

Stage E-Evaluation: Get AI to assist with the job

The objective of the critical, reality-based Evaluation stage is to gauge the value potential of the concepts in the idea portfolio to help the teams find their top ideas that have the potential to succeed in the market and thus deserve to be pitched. Again, the teams go through three distinct steps (Evaluate, Enhance, Elect) here that can be supported by generative AI:

• Gen AI tools can help critically Evaluate an idea’s pros and cons (e.g., by listing its PMI-Plus, Minus, and Interesting aspects) and expand on the points listed by human team members.
• Special Gen AI tools can also help to create early prototypes of a promising idea concept in the second step, Enhance. For example, you can use the text-to-image models MidJourney or Stable Diffusion to visualize a new product concept or use OpenAI Codex or GitHub Copilot to write code for producing a quick-and-dirty version of an App. Moreover, ChatGPT can also be a quick way to give you eight ideas on how to Fix The Bugs of the eight cons of an otherwise promising idea concept. 
• When it’s time to Elect a team’s top ideas in the third step, you can also ask a generative AI tool to assess the value potential and feasibility of each promising idea concept on a rating scale from 1 (It sucks) to 6 (Wow), and then count its vote as one head of the innovation team. (However, beware of having your human votes being swayed by a generative AI assessment). 

Stage A-Action: Add AI as a key member of the idea activation team

The final Action stage of X-IDEA aims first to secure approval for a pitched top idea, then implement it, and finally release it into the market as a value-adding innovation. Like in the Xploration stage, I view the role of generative AI here as performing various “activation assistant” jobs supporting the top idea’s journey from pitch to implementation to launch. 

For example, generative AI can help a team prepare for the Q&A at the end of their top idea pitches or create a first draft of a Project Plan for activating an approved, funded top idea. But overall, it’s more of the time for human action here to get all the implementation work done rather than having generative AI rolling up its sleeves.

Conclusion: Generative AI is going to change the way we do business world — and innovate

When I first played around with generative AI tools in the creative process and looked at the outputs, my first impression was: “Wow, that’s much better than I thought.” From one moment to the next, I began seeing generative AI tools as an opportunity to innovate better and faster — provided these tools are applied mindfully to support and augment human creativity at the right point of time in the right way within the structured framework of an effective creative process method such as X-IDEA. Please make no mistake: Generative AI is here to stay, and its tools will only get more numerous, better, and more powerful over the coming years. So we better learn fast how to use it effectively to amplify and support our human creativity and innovativeness. 

• Learn more about X-IDEA on our website and by downloading our X-IDEA booklet.
• Are you intrigued to explore the potential of generative AI in supporting your creative journey? Embark on an X-IDEA innovation project with us, and we will unveil more new ways in which we leverage generative AI to tackle real-life innovation challenges that your business presently confronts. Reach out to us to find out more.

© Dr. Detlef Reis 2023.