One thing drove organizations to revamp their IT strategies in 2025: AI. But not everyone has been able to keep up with AI’s fast-paced evolution, Thrive Chief Technology Officer Michael Gray said. Those falling behind could risk never catching up, putting the resilience of their tech stack at risk. David Jones, VP of solution engineering at Dynatrace, agreed with Gray, adding that many organizations are unprepared to fully leverage AI tech like generative AI. “You’ve got this technology in generative AI and LLMs that has basically descended upon the industry like that Wile E. Coyote sledgehammer, and the impact has just been tremendous,” Jones said. “What’s happened is organizations are really struggling right now with the amount of complexity.” The race to innovate. Gray pointed to the industry-wide desire to put “a whole AI umbrella over your company.” In previous years, many companies focused mostly on making employees comfortable with using AI regularly to solve smaller problems. “Maybe I’m not changing a core process next week, but I’ve AI-enabled my employees and they can summarize that email that they didn’t quite understand,” Gray said. “That’s one of the bigger things—have a strategy to have AI-enabled employees, which is actually super easy. You just give them software…give them some amount of training, and you allow it in your environment.” What felt impossible is now commonplace. Company-wide use of generative AI is now normal—employees can use this specific technology to write emails, take meeting notes, and create job descriptions for new positions—all tasks that Gray said he isn’t sure anyone actually enjoys doing. Gray says he even uses generative AI to create an agenda for one-on-one meetings with his boss. At first, he was hesitant about the value added from the tool, but reported being “way more productive” in those meetings. “I will tell you it has made a sizable difference, it is such an easy thing for anybody to do,” Gray said. “You don’t need anything more than the idea and some GenAI tools.” Sooooo basic. Gray thinks that IT teams strategizing this year were forced to take the industry’s momentum behind AI innovation into account. However, he added, “data processing” should have been front-of-mind for these teams. Many big problems that the industry looks to solve, Gray estimated, are 70% processing data and around 20–30% development. “There have been times where I found we didn’t need a developer at all, there were already processes that exist, and one team just wasn’t talking to another,” Gray said. “The other team had already automated the steps, but the first department had no idea that it was already taken care of. That communication plus processing data is really where I tell people to start.” With all of the rapid change happening, it has proven to be harder to navigate the updating of an organization’s entire technology stack, which can lead those orgs to fall behind in AI. Tool consolidation, Jones said, is one of the easier paths toward simplification. “There’s a ton of smart people in the industry, and you could go to a good chunk of them and say, ‘Make me a connector from this system to this system,’” Jones said. “Eventually, when you got wires all over the floor, you’re going to trip over them…The right approach would be, start consolidating your tools, start consolidating your platforms.” | 
