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ChatGPT is everywhere, but we are only scratching the surface of the potential for such generative artificial intelligence (AI) capabilities. There are incredibly exciting opportunities for its role across innovation and research and development (R&D) just underneath the surface. Determined to find the answer, our innovation team dug deeper.

If you haven’t already begun experimenting or implementing the generative language model developed by OpenAI into your business processes, you’ve at least heard of ChatGPT. The chatbot has garnered significant attention in the AI community and beyond due to its human-like and conversational abilities—the service reached 100 million users in less than two months.

While the true threat or promise of generative AI will continue to be debated, it is more than certain that businesses can unlock real value for innovation by leaning into the application’s advanced language processing capabilities. New levels of consumer insights, more efficient processes and faster ways of working are just beneath the surface. To put the tool to the test, we used ChatGPT to simulate how we might drive new product development.

1. The ideation process: quality input yields a quality output

The answer you’re looking for depends on how you frame the question. Not as simple as it sounds! ChatGPT leverages a massive body of data from across the internet (over 570GB of data —approximately 300 billion words) to quickly answer user questions. And the question’s specific phrasing, wording, and context significantly influence the response.

Say you are looking for the next great innovation in laundry for a consumer products company. According to a report by Grand View Research, you already know that the global market for laundry care products is expected to grow at a compound annual growth rate of 4.9% from 2021 to 2028 (ChatGPT could also tell you this if you didn’t know). You could simply ask, “What will be the next disruptive laundry product?” ChatGPT will then list a few potential directions for disruptive laundry products like sustainable laundry solutions, smart laundry devices, multi-functional products, etc. The response is interesting and might help affirm some initial thinking, but probably nothing you didn’t already know.

But what if you tried a more creative angle like, “What do people love about laundry?”. This question is not as intuitive. But the insights from ChatGPT are potentially much more interesting and lead you to build a deeper understanding of consumer behaviors and emotions to anchor the next great innovation or product design.

Image credit: Francesco Fazio | openai.com/blog/chatgpt

Questions that lead to more questions lead to potential insights. This is the true power of a tool like ChatGPT. But it all starts with the question, and it pays to think about exactly what you want to know and how to frame the question.

2. The discovery process: less time researching and more time thinking

Underlying all innovation is discovery, from contextual (market research, trend analysis) to behavioral (ethnographic immersion). It is essential but incredibly time-consuming.

ChatGPT can do in seconds what traditional research might take hours and days—quickly gather information on a wide range of topics, sort through the data, and provide a view of what is important and what isn’t. Say you thought of four potential ideas for new laundry products, and now you want to gauge their relative attractiveness. You can ask ChatGPT to rank them for you based on their potential appeal to customers and even go further by asking ChatGPT to think about the types of customers that these ideas would most appeal to.

Image credit: Francesco Fazio | openai.com/blog/chatgpt

Just like the internet made encyclopedias obsolete, ChatGPT is turning traditional research on its head. In a matter of seconds, ChatGPT was able to rank new product ideas and provide a point of view of appeal by customer segment. This shortcuts the initial, more time-consuming research and allows you to go deeper into more specific areas of interest and shift your focus to higher-order tasks.

3. Preparing to go in market: accelerating the creative process

Companies are already starting to use generative AI to handle most basic and transactional customer interactions. But ChatGPT can also lean into the more creative process as well. Want to brainstorm copy for a marketing campaign? Or draft your new company’s mission statement? Or create a starter list of KPIs for your growing sales team? ChatGPT can quickly help you get started.

For example, let’s say you have built a new stain removal product and are ready to launch in market. Using ChatGPT, you can quickly brainstorm potential concepts for marketing campaigns and help draft advertisement copy. Your creative team now has a starting point to evaluate further and refine. Let’s say your team aligns on a campaign centered on eco-friendliness, ease of use, and stain-removing power. You can go a step further and ask ChatGPT to create compelling posts for social media. Here’s what you’d get:

Image credit: Francesco Fazio | openai.com/blog/chatgpt

Not bad, huh? Seeking opportunities to implement generative AI in tasks like these can help significantly accelerate and enhance your go-in-market strategy.

Generative AI and the future of innovation

The applications for generative AI do not just have potential; they are already changing the game’s rules for innovation. New concept development, accelerated research and discovery, and go-to-market strategy are just a couple of opportunity areas to leverage generative AI.

However, it’s not going to replace human decision-making. We know that the massive body of data used by generative AI tools is already available content. In fact, the data underlying ChatGPT is only current up to 2021. So not only is it somewhat dated, but it also can’t replace true primary research.

As long as you know the data you are working with and its strengths and limitations, generative AI’s abilities can still be incredibly powerful. And how much benefit it can provide comes down to knowing what questions to ask, where to dig deeper, and how to translate that knowledge into real action.