我现在对人工智能有一种不健康的痴迷的原因是，我的整个职业生涯基本上都在解决一个问题：你如何.

The reason I have an unhealthy obsession with AI right now is because I've spent my entire professional life on essentially one problem: how do you increase the value of content in the enterprise. How do you secure it, how do you collaborate on it, how do you govern it, and how to integrate it across all your applications.But there's been one glaring issue that we've dealt with since the founding of Box. We could never really process information at scale in any real automated way. There have been many attempts at this problem (often in the search space), but nothing that really fundamentally transformed what you can do with enterprise knowledge.For years the primary kind of data that we could query, analyze, and process with computers was structured data. This meant anything you could shove into a database you could understand with computers - your CRM, ERP, product analytics, HR, and other data.But all of the unstructured data that powers our daily knowledge work - marketing assets, contracts, financial documents, medical research, engineering documentation - was only valuable when a human was operating on it. There was just simply no real way to apply automation at scale to any of this data, which meant all knowledge work was largely rate limited by our ability to process information ourselves, often manually.AI models have obviously dramatically changed this reality. And the past couple weeks perfectly highlight this incredible progress. GPT-5.6, Fable 5, Grok 4.5, Muse Spark 1.1, and a leading array of open weights models are all showing incredible advancements on working with unstructured data.The inherent broad intelligence, reasoning, math, and coding skills in these models, combined with deep domain expertise trained into them across finance, legal, healthcare, life sciences, and other critical fields, means that we're able to completely change what we can do with this unstructured data at scale.What this unlocks is the ability to ask insanely complex questions of your data that were never before possible, and let agents just run on for minutes or hours across these data sets to accelerate knowledge work.And it's not just about automating the work that we already do. While this is highly valuable, it wouldn't be particularly transformative. What's exciting is that you can now throw compute at unstructured data problems that wouldn't have been possible before. Analyze every risk on my contracts, do due diligence more deeply on a prospective investment or acquisition, look through all past client interactions in an industry to find best practices to replicate, comb through life sciences research or clinical trial data for new insights, and on and on.So that's why we're insanely excited about what AI Agents can now do with content on Box.Box: GPT-5.6 Sol is a breakthrough in complex reasoning and data analysis. Here, it analyzes hundreds of pages across a lending deal, reconciles terms across agreements, financials, diligence, collateral, and risk materials, flags issues, and saves a source-cited report to Box.