We’re going to enter a new phase of AI where the average consumer may not perceive a huge difference in any one model upgrade, but specific industries will feel significant improvements occur. The next phase of AI be about making models better and better for AI agents in real world knowledge work domains. We’re going to see new evals emerge that test for relevant tasks in these spaces, the generation of high quality data and environments that align to real work, training against specific tools and software in these spaces, and more. The test case of how to improve models on axis of real world capability has been proven out in coding, but now the same will start to happen across other high value fields like financial services, law, healthcare, life sciences and more. We’re only at the very beginning of this cycle.

The trillion dollar opportunity in enterprise software is AI Agents. The reason for this is AI Agents expand many software categories because most tools have been constrained by the number of users on the other end of the tool. Enterprise software traditionally enabled people to do their work. But now the software also comes with actual productive output as well. This then breaks the traditional limits that many software markets have had, because smaller customers can use these tools more, new departments and industries open up, and previously scarce areas of work can be scaled more. For instance, most estimates put the code IDE category at a few billion dollars just a few years ago. This has - amazingly - always been a very small category of software. Well, now with AI Agents, the IDE market and coding in general is one of the fastest categories of spend in tech. This is because it’s bringing automation to a high value activity and supplying the world with a traditionally very scarce and high cost resource, engineers. The same is going to be true for many other categories of work across legal, financial services, healthcare, and more. Amazingly, this now opens up many niche categories that just wouldn’t have been economically viable for a software company before. For instance, making a business out of selling software to life sciences regulatory compliance managers would have been sub-scale before, but in a world of AI Agents this all of a sudden becomes possible. We’re already seeing this in our initial Box AI Agent use cases. Many of the early Agents being created by customers are for automating or augmenting work in previously underserved areas. This is letting customers automate a process they never would have gotten around to before, or dramatically expanding the output of work they were already doing. In all cases it’s more TAM that software wasn’t touching before. In all, it’s clear that AI Agents are going to grow many software categories. It’s an incredible time to be going after these spaces because even the small ones will now be massive, and the big ones will just get bigger. Tons of opportunity.

The software business model will be seats for the user and consumption for the agents. The big upside now is that there are many AI Agent opportunities where the TAM vastly exceeds the previous potential seat revenue. Because now you deliver work, not just enable it.