Box

IBM, a global technology leader with over a century of innovation, solved a challenge familiar to many organizations: critical information scattered across dozens of systems, leading to slow answers, inconsistent workflows, and manual processes that drain productivity. How they achieved success with Box: ➡️ Powered AskIBM and AskIT with Box AI, using governed Box Hubs as the trusted content layer to deliver instant, source-backed answers to 250,000 employees ➡️ Collapsed IT response times from hours to seconds, with auto-generated reports and answers arriving complete with clear source links ➡️ Implemented centralized orchestration via Box for seamless collaboration across multiple AI agents Jennifer Kady, VP and GM for Worldwide Data Sales at IBM, shared: "AskIBM is the one place we go for anything that we need. And it's now powered heavily by Box Hubs. Anything I do in terms of orchestration uses that as the single pane of glass." Key learnings for your organization: Start with pain points that deliver immediate, measurable value. Think in systems rather than silos and build capabilities that scale across the enterprise. Most importantly, build trust through transparency by ensuring every AI response traces back to source content. When employees trust the system, adoption follows naturally. Learn how Box can help your organization pioneer the future of work. 👇 https://lnkd.in/gUCTxQgE

OpenAI’s new model GPT 5.5, is raising the bar for enterprises that need AI to reason accurately across complex content, not just generate fluent answers. In Box’s evaluation of GPT 5.5 across enterprise content use cases, one result stood out: the performance gap widened as tasks required more sustained, multi-step reasoning. Across key workflows, GPT 5.5 delivered measurable gains over GPT 5.4: → Report Drafting from Data: 81% vs. 76% (+5 percentage points) → Expert Review and Verification: 79% vs. 74% (+5 percentage points) → Data Analysis: 78% vs. 61% (+17 percentage points) → Due Diligence: 69% vs. 57% (+12 percentage points). Box AI Product Manager, Sidharth Srinivasan, explains how these results reinforce an important point for enterprise AI: value comes not only from strong generation, but from the ability to transform, reconcile, and reason across complex business content with accuracy and consistency. Read the full evaluation: https://bit.ly/4sTlFKL

Our CTO Ben Kus made an important point about OpenClaw-style agents: The real shift isn’t that they respond better. it’s that they persist. They remember. they keep working. they can act without waiting for the next prompt. That’s the opportunity. And that’s the risk. Because if an agent has access to an account, it can do what that account can do. Read emails. Send messages. Take action. That’s why one of the most practical ideas Ben highlights is giving agents separate accounts with constrained permissions and bounded autonomy. Not your full user access. Not unlimited reach. Just the access they need to do the job. For enterprises, that’s the real conversation around persistent agents: not just what they can do, but what they should be allowed to do on their own. OpenClaw makes the future of agents feel more real. But trust, security, and permission design are what will make that future deployable. Watch the latest from our AI Explainer series: https://lnkd.in/gtSvipGF How are you thinking about constrained access and autonomy for AI agents in the enterprise?

Today at Google Cloud Next 2026, the potential of agentic AI is meeting the reality of enterprise content. While most AI strategies can solve for the model, they often hit a wall when it comes to making that AI work securely with a company’s most sensitive data. Box is here to bridge that gap by turning siloed files into active participants in your AI workflows. The next phase of our integration with Google Cloud is live. The Box Agent for Gemini Enterprise is coming soon to the Agent Gallery in the Gemini Enterprise app — allowing teams to search, analyze, and trigger workflows across their Box content directly within the Gemini Enterprise app. This progress is anchored by a sophisticated partnership with Google Cloud. By integrating Gemini models, Gemini Enterprise Agent Platform, and BigQuery, Box Agents do more than just store files—they surface deep insights and automate intricate processes. We have already seen millions of executions where Gemini 2.5 Flash and Pro power revolutionary data extraction, turning static files into actionable metadata with unprecedented speed. The future of agentic work is here. Read the full announcement and visit us at Booth #2115 to see it all in action! https://lnkd.in/g2fdQtGN

OpenAI just announced workspace agents in ChatGPT. And Box is already built in. Workspace agents are shared agents that handle complex tasks and long-running workflows across tools and teams. That means you can build agents that pull context from Box and other enterprise tools to get the latest status on a workstream, prepare for your next meeting, or run long-horizon workflows that would have required significant manual effort before. Box is also built directly into the knowledge search agent template and can be easily added as a knowledge source to any agent your team builds. A wealth management firm, for example, can build a client onboarding agent that checks for new documents, flags risks, and generates a human-ready summary automatically every single morning. Box is where enterprise content lives. Now it's where workspace agents work too. Watch the demo. 👇

Northern Rockies Regional Municipality serves its community by delivering essential public services across a vast region, managing everything from public works and emergency services to constituent requests and Freedom of Information Act responses. How they transformed with Box: ➡️ Unlocked unstructured data by querying files, contracts, and documents in seconds instead of manually sifting through content one by one ➡️ Transformed FOIA requests by automating email ingestion into Box, allowing staff to find relevant information instantly instead of combing through thousands of emails ➡️ Kept humans in control with AI generating first drafts and surfacing insights while people review every output and make every final decision Rob Blain, Technological Services Manager at Northern Rockies, shared: "We became comfortable knowing that Box is not going to be training on our data. And Box exceeds most countries' strict security policies." For municipalities and government agencies navigating limited budgets, legacy systems, and growing constituent demands, Northern Rockies shows that a security-first approach to AI isn't a barrier to transformation. It's the foundation that makes transformation sustainable. Read the full story here. 👇 https://lnkd.in/gBEAZPWd

Every IT leader knows the moment. Someone starts using ChatGPT for work. Then more people do. And suddenly you're governing something that was never designed for your enterprise in the first place. Jeff Chambers, VP of IT at WongDoody, has lived that moment. On the latest AI-First CIO episode, he shared three things every IT leader needs to hear: 1. Security breaks first. People's first experience with AI is personal and unsecured. When they carry that mindset into the enterprise, that's where the real challenge begins. 2. "Human in the lead" beats "human in the loop." Reviewing AI outputs isn't enough. Humans need to own the origin, evaluation, and ongoing vetting of every AI tool in the organization. 3. The ROI timeline is longer than you think. AI strategy isn't a project with an end date. It's ongoing change management — and the milestones matter as much as the technology. Jeff's framing that's stuck with us: "Processes need to be reevaluated from the ground up. Understand your complete business process across all of your systems, where your content is, and get that house in order." Watch the full episode: https://lnkd.in/g3tFpd2r What was the first thing that broke in your organization when AI started getting used at scale?

A 27-year-old bug in OpenBSD. A 16-year-old FFmpeg flaw. A FreeBSD vulnerability granting unauthenticated root access to anyone on the network. All found by AI. Overnight. Autonomously. Anthropic's Claude Mythos and Project Glasswing marks a genuine inflection point for enterprise security. The same AI that finds decades-old vulnerabilities can also help stop new ones from being created in the first place. Our CISO Heather Ceylan shares 4 things every security leader should be doing right now: 1. Revisit your threat models. 2. Get ahead of the Glasswing patch wave. 3. Talk to your vendors. 4. Invest harder in the fundamentals. "AI found a bug that the entire industry missed for 27 years. That should make every CISO uncomfortable and optimistic in equal measure. What matters now is what we do with the head start." Read Heather's full take here. 👇 https://lnkd.in/gj8KJfgj

There is a paradox hiding inside most enterprise AI strategies. The more agents you add, the harder it becomes to maintain consistency, trust, and control. It's not that individual agents fail. The problem is that when agents operate from different versions of the same document, different permission sets, and different content sources, their outputs inevitably diverge. More automation, but not more alignment. The fix isn't better orchestration. It's a better content foundation. When every agent works from the same governed, authoritative source of truth, outputs compound instead of conflict. That's the infrastructure decision that separates enterprises that successfully scale AI from those buried under their own agent sprawl. Read the full breakdown here. 👇 https://lnkd.in/gb3adFsC