6 hard truths of generative AI in the enterprise

Michael Corrigan, CIO of World Insurance, says that while genAI is powerful and evolving very rapidly, it is maturing very slowly. There is also a lot of hype and misnomers about it, he says.

“It definitely requires a strategy and roadmap to be implemented properly for it to have a positive impact on your business, to be able to enhance your capabilities, and reach your business goals,’’ Corrigan says.

It also requires organizations to establish use cases and the tools they want to use because shadow genAI is creeping in.

“Even if a company hasn’t rolled out a particular AI tool, employees are out there using ChatGPT and all sorts of third-party AI tools because it is making them more efficient,’’ says Briggs & Stratton’s Olsson. “The hard truth is, if you don’t start giving them tools, they’re going to find them; … even if they’re not doing anything with AI, the data risk is there. It’s a new information security risk.”

Dave Pawlak, executive director of IT at Consumers Energy, agrees, saying genAI must be implemented securely “and it’s not as easy as what the public is experiencing with OpenAI or other [open] generative AI tools.”

Still, even with all these hard truths, Kermisch, Pawlak, Baig, and others say there is value in implementing genAI quickly, safely, and at scale.

“It will allow you to go from pilot to scale,’’ Baig said. “Unlike other digital disruptions, I believe we’re in a phase of genAI where a level of investment is needed,” as well as a better understanding of the technology. “You have an incredible opportunity to take advantage of this and it makes it even more important for CIOs to play a leading role in leading organizations forward.”