Does AI intend to come up with another large viral product? Here’s what to know

Can generative AI cure human imagination? This is a difficult (though terrifying) query, and so far studies have shown mixed results. Lynn Wu, associate professor at Wharton School, and her colleagues decided to measure the influence of artificial intelligence on product innovation, analyzing indicators reminiscent of patents and revenues.

Test

The Wu study was based on two sorts of research: a survey of 331 firms on their technology development practices, in addition to performance evaluation of over 2,000 public industrial firms and complex recent patents. Its purpose was to discover two things: how do firms integrate artificial intelligence? And how does it affect the innovation of business products?

Results

Ai was bad in creating “thin air” breakthroughs. “This is a fundamental limitation,” says Wu. “When that does Invent something radically new, it can be AI hallucinations. “But AI is superb in a different form of innovation – combining existing ideas to create something recent.

Many firms in the study used AI for this purpose and were awarded for this: they were 3% to 7% more productive with patents and revenues than firms that didn’t use these tools. AI had a particular impact on the strongly muted and decentralized firms. When different departments didn’t talk to each other, artificial intelligence filled the gap to make knowledge for everyone in the team who want to develop a recent product.

What we have learned

People are good in combining three to five ideas in our heads. “But when you have to combine more elements, then the machine can really help you,” says Wu. For example, if you would like to dream of a recent drink that teenagers will go to monkeys, generative artificial intelligence can mix and match 1000’s of preferences for this age group to find a concept that hit the sign.

How to use it

Do you would like to introduce innovations to your personal product? Tojin Eapen, an elderly worker at the conference council, developed a strategy supported by research based on the combination: Ask AI to mix three random words (say, “phone”, “lava” and “lobster”) in the concept of a recent product. What you come back is probably not so practical, but it may well encourage your team to develop a more useful idea. For a specific Polite Product – let’s say, footwear – you may start with your category (“shoe”) and add two other words that are random (“telescope”) or related (“security”) and see what will occur.

Before investing time or money in the idea, EaPen suggests that AI play the devil’s lawyer. You can ask: “What are the 10 ways, how can this idea fail?” or “What will customers don’t like in this product?” or “What are the three critical risk?”

When using AI, at all times remember: it may well be helpful – but it’ll be helpful for a competitor in exactly the same way. “So regardless of whether it is reserved data or something special,” says Wu, “better invent your moat to protect what you have.”