New York – Just over a month after GPT 5.1, OpenAI on Thursday released GPT 5.2, the latest version of its flagship generative AI model, seeming to support the contention of many in the tech world that AI technology is advancing faster than it can be adopted.
For the last three years, since Popularizing Generic AI After OpenAI released ChatGPT, the market shifted from hype about AI models to hype about agentic AI. Sometimes it seems like enterprises are barely adopting a technology before vendors like Microsoft, AWS, Google, and OpenAI release their next product.
Intensity in AI business
Sometimes, a crowd of AI models and agentic ai tools May feel heavy.
“There’s a lot of hype and noise, and I don’t think people like (OpenAI CEO Sam Altman) are making it easy,” said Peter Guagenti, CEO of agentic AI vendor Everworker, during an interview with AI Business at Informa’s AI Summit.
Everworker is focused on helping businesses create, customize, and deploy agentic AI workers without using code.
Guagenti added, “They’re talking nonsense and all that.” “It’s really scary and overwhelming.”
Due to the noise and promotional energy around new AI releases, enterprises may feel like they are behind, while to others, the technology may seem advanced and intriguing.
It certainly sounded compelling to Naomi Tadesse, an assistant architect at General Motors.
“There’s a lot of AI everywhere,” Tadesse said in an interview, referring to the dozens of AI vendors showcasing their tools on the AI Summit floor. “There’s a lot of AI integrated within manufacturing, within automotive… things that will help or assist you in doing things much faster. It’s very interesting.”
He added, “Taking away jobs, all that stuff…I don’t necessarily like it.” “But I can see that everyone is moving toward AI, and everyone is trying to move forward.”
Adoption starts with use case
However, in Moving towards AIGuagenti, enterprises need to be deliberate rather than moving forward at full speed everworkerSaid.
“What I recommend is to turn the volume down,” he said. “Start small, stay focused. Where is the pain in your business today? Where in your business can’t you hire today? Where are there extra expenses in your business that you know aren’t adding value?”
“Start with these simple, obvious use cases where you get high reward and low risk,” he adds.
data driver
Beyond starting with simple applications, enterprises should focus on their data.
“Without data overview“I don’t believe that trust ever exists between AI applications,” said David Swan, a sales engineer at Retool, a developer of low-code software and AI development platforms, during a panel at the conference on Dec. 10.
Data overview is also important because it helps ensure that the use cases to which enterprises are applying AI technology are correctly based.
“Context really matters for AI,” Anuradha Mardapu, manager of data engineering and analytics, data governance at American Airlines, said in an interview. “Pointing the data to the right use case really matters.”
He said that enterprises should not only focus on data, but they should also ensure that their data is ready. One way to determine if the data is ready is to verify that it fits the application. Indeed, there is a certain lack of consideration for ensuring that the data is the right data for the job and that it is properly prepared and controlled which is reflected in the sometimes hasty pace with which many businesses are adopting AI technology.
While many say the pace of adoption is slow, for Maradapu, it is somewhat the opposite.
“We are moving so fast without considering all the underlying governance processes and foundations,” he said. “So it’s really slowly becoming more chaotic.”
make it accessible
One way to make things less cluttered, Guagenti said, is for enterprises to provide everyone within their organization access to AI tools.
“These are all specialized agents who are focused on a departmental or use case,” he said.
One organization that says it’s working on making the tools less confusing for workers is NBC Universal.
In a heated conversation at the conference on December 10, Chris Krainer, EVP, Chief Digital and Technology Officer NBC Universal Destinations & ExperiencesDiscussed how enterprises can use generative and agentic AI to address challenging points within the organization.
“It doesn’t matter whether you’re a front-line engagement leader for us, or you’re an AI data scientist in the back,” Krainer said. “It doesn’t really matter. Everyone has friction in their work.”
He added, “We’re trying to demystify it and also try to make it clear that this is a tool that we’re going to use, but here’s the lens through which we’re trying to use it.”
