The Most Important AI Lesson Businesses Learned in 2025

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, the most important AI business lesson from 2025 The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive in. Now, just a heads up, today's show is a main episode only. We're kind of getting into crazy time of the year where on any given day, the format might be a little bit different. Just for your own planning and so you know, we will mostly be here on our regular schedule, although not of course on Christmas or New Year's, but there'll be a bunch of fun end of year content, a couple interviews even that I'm really excited about. And while that's not what this is, we're still in regular content mode until about the 23rd. Today's main episode just got a little bit long, so we will be back with our normal split between the headlines and the main episode tomorrow. So with all that out of the way, let's get into today's topic. Welcome back to The AI Daily Brief. In case you haven't been able to tell, I love end of year content. It's a time that as the barrage of news slows down a little bit, people take a little bit of extra time to reflect on the year that was, they start to prepare and look forward to how they want to operate in the year to come. And from a content perspective, everyone is putting together their best trend reports and ideas and thoughts for the future. And that creates a really interesting lens through which to explore some of the big issues facing AI and all of the people in industries who are trying to figure out how to adopt it and adapt to it. Now the latest of these reports is Deloitte's 17th Annual Tech Trends Report. This is a monster 72-page document that goes deep across six different themes. Now rather than getting into each and every theme, I want to highlight what I believe is the big idea and the clear through line throughout all of this, that I think is perhaps the most important lesson for enterprises and businesses who tried to adopt AI in 2025 The lesson is of course that to fully take advantage of AI, it is going to require much more than just simply dropping a chat bot on the head of your employees and saying, go be more productive. If you've spent any time on LinkedIn over the past couple of weeks, you've probably seen some version of this iceberg image, which has AI strategy at the top. And then of course underneath the water are all the things that make AI more challenging in its quest to transform but also more powerful if you can address them. That's things like legacy systems, data pipelines, integration, debt and undocumented code. So today we will use the Deloitte Tech Trends Report as a lens to explore that exact topic while also covering some of the other interesting things that they're servicing. Now the two areas of their six big themes where they address this are first, the agentic reality check, preparing for a silicon-based workforce, and section four, the great rebuild, architecting an AI Native Tech organization. Let's pop over to agents first. 2025 was supposed to be the year of agents, and in many ways I think it was. We certainly saw from studies like KPMG's Pulse Survey that enterprise adoption of agents was significant throughout the year. What's more, whereas I think it could have easily devolved into a bunch of showcase pilots and experiments, I think we pretty quickly skipped over that step and went right on into in-production agents that were actually meant to have purpose. At the same time, it's pretty clear that agents didn't fundamentally upend everything inside the organization as some thought they might. With the possible exception, of course, of software engineering, where coding agents were the most disruptive and powerful force of the year. So again, Deloitte calls their section on this the agentic reality check. And right, despite its promise, many agentic AI implementations are failing, but leading organizations that are reimagining operations and managing agents as workers are finding success. And here in a single sentence is the theme which I will be effectively beating you over the head with for the next two weeks. True value comes from redesigning operations, not just layering agents onto old workflows. What does that mean? Well, Deloitte says it means building agent-compatible architectures, implementing robust orchestration frameworks and developing new management approaches for digital workers. It also, they say, means rethinking work itself. As organizations embrace the full potential of agents, not only are their processes likely to change, but so will their definition of a worker. So let's talk some numbers. Gardner predicts that from a starting point of zero in 2024, by 2028, agents will make 15% of work decisions autonomously, and a third of software applications will have agentic AI integrated in some way. And yet there are challenges. One of the things that's really interesting to me is that you can find a wild range of organizational self-reporting on agentic deployments. For example, I mentioned the KPMG Pulse Survey. In their Q3 Pulse Survey, they found that 42% of organizations had deployed at least some agents, which was up from 11% in Q1. Deloitte's 2025 Emerging Technology Trends, however, which based on my research was conducted between June and July of this year, found that 30% of organizations exploring agent options and 38% piloting solutions, but only 11% actively had agents in production. Now, the self-reporting bias of all of these is real, and also the terminology isn't super precise. But I think it's fair to say that wherever on that spectrum, from the Deloitte numbers to the KPMG numbers, the truth actually lies, we're still really early. And that I think is embodied in this other stat from Deloitte, where 42% of organizations said that they are still developing their agentic strategy roadmap with more than a third, 35%, having no formal strategy at all. The survey also identifies three big barriers. And for those of you listening at home, I'll pause for just a second to see if you can guess them.