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While is taking the business world by storm, it鈥檚 important to note that it鈥檚 not necessarily new. Many of today's promises for AI were also made in the past. It was less than 40 years ago that , packed with expert knowledge, were supposed to unlock the promises of AI. What went wrong? ''People believed their own hype,'' said S. Jerrold Kaplan, cofounder of one leading artificial intelligence company, TeKnowledge. So as generative AI occupies massive mind space for most innovative companies, the question they must ask is, 鈥淎re we doing this the right way?鈥�

Unfortunately, many aren鈥檛. In fact, there鈥檚 a bit of an vibe鈥攖he ancient symbol of a snake eating its tail. As companies rush to use AI, they鈥檙e making mistakes that could cost money and put the organization in jeopardy. Even the most innovative companies鈥攖he ones consistently ahead of the tech curve鈥攎ust proceed with caution because we鈥檙e still in a "flying the plane while we build it" mode

With that in mind, let鈥檚 explore how companies can use companies AI to forward innovation while protecting themselves.

Tap into AI for product idea and concept development

Product people must always find the next big thing or improve upon the last big thing. Even the most creative teams may stare at a blank whiteboard and scratch their heads, trying to dream up compelling ideas.

Generative AI is great for idea and concept development. For example, input your identified customer problems and use AI to think of potential solutions. Then take each of those solutions and ask how to solve them. To be clear, you鈥檙e not going to find transformative innovation in the answer, but AI can help guide your team toward new ideas that you can discuss.

And that鈥檚 the key鈥攆ind novel ideas that align with your company鈥檚 overarching innovation goals. From there, use human smarts to build them out. Humans are essential to using generative AI to your advantage because you need to do more than just generate a bunch of ideas.

It鈥檚 essential to understand the problem customers are attempting to solve. That requires listening and thinking鈥攏ot just assembling data from various sources. Currently, humans are better at that. So while generative AI can create the idea list faster, it's still just a guide. You need to dig deep to understand the problem.

Use AI for product development strategies

Product development is built on key performance indicators (KPIs) that guide product people from ideation to launch. But what KPIs should you choose? This is a perfect job for AI, especially for companies that track diverse and complex metrics for products.

Use your knowledge of the industry you鈥檙e targeting and your organization's data and let AI guide you toward KPIs that will help keep product development moving forward and on time. Another bonus: Your AI research may uncover new KPIs you hadn鈥檛 thought of previously but may make more sense based on the product.

And that鈥檚 the great thing about cutting-edge technology like AI; it can guide you toward discoveries and illuminate new ways of doing things. You simply cannot survive as an innovative tech company while holding onto a 鈥渢hat鈥檚 the way we鈥檝e always done it鈥� mentality, and AI can help counter that crippling mindset.

Incorporate AI into InnovationOps

Companies are adopting an , which operationalizes innovation to build innovative philosophies into corporate DNA. The idea is to bring together an organization鈥檚 people, processes and innovative jobs to be done.

A key component of such a philosophy is emphasizing collaboration and data availability. The more insight an organization has, the more likely it is to glean discoveries that might have otherwise remained siloed. Learnings from help to support an InnovationOps approach, as it provides unique insight that cross-functional teams can access and use for their specific projects and products.

Keep AI human-based

A common fear many have about generative AI is that it will take their jobs. Not exactly. It鈥檒l be a human who understands how to use AI. Don鈥檛 underestimate people's importance in making AI a driving force in your innovation efforts.

Generative AI can go wide, but it doesn鈥檛 necessarily go deep. You need smart people who understand the industries you work in, the history of the products you鈥檝e developed and the unique problems your customers face to input the correct data into large language models (LLMs) to get the output necessary to move the needle. Every organization needs to start training product people to become prompting experts to get to the buried product treasure more quickly.

Safeguard your IP and brand

Don鈥檛 put anything into an AI tool you wouldn鈥檛 want to show up in someone else鈥檚 query or give hackers access to. While inputting every bit of information you can think of in an innovation project is tempting, you have to be careful. Oversharing proprietary information on a generative AI is a for companies. You can fall victim to inconsistent messaging and branding and potentially share information that shouldn鈥檛 be available to the public. We鈥檙e also seeing increased cyber criminals .

Research and refine AI output

Generative AI鈥檚 knowledge isn鈥檛 up to date. So your query results shouldn鈥檛 necessarily be taken at face value. It probably won't know about recent competitive pivots, legislation or compliance updates. Use your expertise to research AI insight to make sure what you鈥檙e getting is accurate. And remember, , so it鈥檚 just as essential to cross-check research for that, too. Again, this is where having smart, meticulous people on board will help to refine AI insight. They know your industry and organization better than AI and can use queries as a helpful starting point for something bigger.

The promise of AI in innovation is huge, as it unlocks unprecedented efficiency and head-turning output. We鈥檙e only seeing the tip of the iceberg as it relates to the promise the technology holds, so lean into it. But do so with governance鈥攏o one wants snake tail for dinner.

Learn how to help its customers achieve innovation goal in an ever-changing business environment.

This article originally appeared in .