On Thursday, Box launched its developer conference Boxworks by announcing a new set of AI features, building agentic AI models into the backbone of the company’s products.
It’s more product announcements than usual for the conference, reflecting the increasingly fast pace of AI development at the company: Box launched its AI studio last year, followed by a new set of data-extraction agents in February, and others for search and deep research in May.
Now, the company is rolling out a new system called Box Automate that works as a kind of operating system for AI agents, breaking workflows into different segments that can be augmented with AI as necessary.
I spoke with CEO Aaron Levie about the company’s approach to AI, and the perilous work of competing with foundation model companies. Unsurprisingly, he was very bullish about the possibilities for AI agents in the modern workplace, but he was also clear-eyed about the limitations of current models and how to manage those limitations with existing technology.
This interview has been edited for length and clarity.
TechCrunch: You’re announcing a bunch of AI products today, so I want to start by asking about the big-picture vision. Why build AI agents into a cloud content-management service?
Aaron Levie: So the thing that we think about all day long – and what our focus is at Box – is how much work is changing due to AI. And the vast majority of the impact right now is on workflows involving unstructured data. We’ve already been able to automate anything that deals with structured data that goes into a database. If you think about CRM systems, ERP systems, HR systems, we’ve already had years of automation in that space. But where we’ve never had automation is anything that touches unstructured data.
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Think about any kind of legal review process, any kind of marketing asset management process, any kind of M&A deal review — all of those workflows deal with lots of unstructured data. People have to review that data, make updates to it, make decisions and so on. We’ve never been able to bring much automation to those workflows. We’ve been able to sort of describe them in software, but computers just haven’t been good enough at reading a document or looking at a marketing asset.
So for us, AI agents mean that, for the first time ever, we can actually tap into all of this unstructured data.
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