Rowan Curran, Senior Analyst and J. P. Gownder Vice President and Principal Analyst
When ChatGPT was released in November 2022, a big shift happened. Yes, AI and large language models existed for years before that, but ChatGPT performed in a way that past models had not — and it got people excited. Since then, it’s been full speed ahead with generative AI (genAI) for both consumers and enterprises.
In April, Senior Analyst Rowan Curran provided an update on the impact that generative AI was having on the business, and since then, there’s already a lot more to talk about. This time, Curran is joined by VP and Principal Analyst J. P. Gownder to discuss how this once-in-a-generation technology is changing the future of work.
There’s been a lot of movement along the genAI maturity curve in the past few months, says Curran, with some enterprise users moving from pilot to deployment, while others are focusing on building out policy and cultural approaches. Gownder agrees, saying he’s seen a lot of “positive curiosity” recently from clients asking how generative AI can fit into their future-of-work strategies.
The interest has grown rapidly in the past few months because there are realistic options to work with both at the consumer level and the enterprise level, proving that this technology is not just a buzzword. As an example of the changes happening, Gownder points to the education space — specifically, teachers who have had to suddenly figure out how to adjust their teaching methods to a world where students are actively using ChatGPT or Google’s Duet AI and weren’t only a semester ago. “This isn’t to scare you, but it’s just to say this is a very fast-moving trend,” he says. “I think it is an inflection point.”
And the explosion in interest in generative AI overall has driven more interest in enterprise AI use cases, allowing technology leaders to bring some AI projects off the back burner (see our 2024 Planning Guides for more details on how to budget for AI in the year ahead).
But there’s still a lot of misunderstanding about generative AI. Curran says the rapid explosion on the consumer side of generative AI has created some misguided enthusiasm on the enterprise side. He says that perhaps too many companies are focusing on building a “corporate strategy for ChatGPT” because they’ve been impressed with the interface but in fact should be focusing on a broader approach to the use of generative AI. Gownder explains that Forrester’s Robotics Quotient (RQ) model can help organizations lay the groundwork for an enterprise AI strategy.
The episode closes with two real-world examples of some of the most unexpected uses of generative AI (one rather unsettling, the other more uplifting). To hear more about the new research Curran and Gownder reference in the episode, be sure to check out both the Technology & Innovation North America and Data Strategy & Insights events in September.