Immuta

AI agents don’t wait in line. But most data access models still assume they will. That’s the breaking point. For years, tickets and static roles were “good enough.” Slow, but workable when humans were the only ones asking for data. Now agents are in the loop, and everything cracks. They either get way too much access just to keep things moving, or they hit a wall and stall. And when something goes wrong, it’s not even clear who (or what) did what. This isn’t just a scale issue. The model itself breaks. That’s what Immuta CTO Steven Touw gets into here, and why we’re extending data provisioning to support Agentic Data Access. Access has to be dynamic, temporary, and policy-driven—for humans and agents. Anything else doesn’t hold up. https://lnkd.in/e96R4HPN

The next phase of enterprise AI won’t be limited by models. It will come down to whether organizations can actually deliver data at the speed those systems require. In this piece, Matthew Carroll breaks down why provisioning is becoming the real constraint, and why access models built around tickets and approvals can’t keep up. The teams that get this right will unlock far more value from the data they already have. Read more ➟ https://lnkd.in/eD7WKWM3

AI agents don’t submit tickets. So why is data access still built that way? That’s the shift behind Agentic Data Access, and it’s starting to show up in the broader data conversation. We appreciate the mention from Solutions Review this week! ➡️ https://lnkd.in/e6kv7787

Access still moves through tickets, manual approvals and processes, even as the demand for AI and the need for strong governance continues to grow. If this resonates with you, here are a few recent perspectives we've shared on what needs to change: → The New Data Delivery Mandate: Instant, Governed, and Everywhere: https://lnkd.in/eVJZ_4M9 → How AI Agents Change the Rules of Access Governance: https://lnkd.in/eb_aG6dP → Solving the Agentic Breaking Point: Why AI Demands a New Blueprint for Data Access: https://lnkd.in/eXdfJFHv → Introducing Agentic Data Access: The Next Era of Data Provisioning: https://lnkd.in/efPbHcQJ → Immuta: A Framework for GxP Compliance in the Use of Data Within Life Sciences: https://lnkd.in/ee9sB8iu 

Most AI pilots start with impersonation. It works...until it doesn’t. Here’s what breaks at enterprise scale. Swipe through. ⤵️ https://lnkd.in/eFqfm2dk

The future of data depends on fast, responsible access, and we continue to grow the team that makes it happen: → Resident Solution Architect, US (East): https://bit.ly/4rW7YLi  → GTM Engineer (Remote): https://bit.ly/4dcFIiU  → GTM Engineer (London): https://bit.ly/3PskaVD  → Enterprise Account Executive, US (West): https://bit.ly/4ddvMFZ  → Regional Director, Sales (West & Central US): https://bit.ly/4s08DLE  → Sr. Pre-Sales Solution Architect (EMEA): https://bit.ly/4d8r9Nq  → Sr. Product Manager, Govern (Remote): https://bit.ly/4rTu4gE  → Sr. Software Engineer, Agentic Access (Remote): https://bitly.cx/Btwc View all of our open roles here: https://lnkd.in/eV8NR9zG 

AI agents operate at machine speed, while most access models still assume human pace. That gap is where things break. When access decisions can’t keep up, systems stall or controls get loosened just to keep things moving. Unfortunately...neither scales. https://lnkd.in/eFqfm2dk

Most data teams have modernized their platforms. Few have modernized how data gets delivered. That gap is starting to show. AI is driving continuous, programmatic demand for data. But provisioning still relies on tickets, approvals, and manual steps. The result: - Slower AI initiatives - Growing access backlogs - More pressure on governance teams So what does a modern provisioning model look like? We’re breaking that down with Microsoft and Warner Bros. Discovery on March 31. Join us: https://lnkd.in/ejRGRFqC #DataProvisioning #AI #DataGovernance #AIGovernance #DataSecurity

AI agents are starting to show up in places most teams didn’t expect. They’re not just answering questions. They’re pulling data from multiple systems, testing queries, and working through problems on their own. And they don’t do it once or twice a day. They do it continuously. That’s where things start to break. Most access models were built around people. Tickets, approvals, standing permissions. That works when requests are occasional. It doesn’t hold up when requests never stop. So the question changes. It’s not just who should have access. It’s whether a specific request should be allowed right now, given the context. That’s a different way of thinking about access. It’s what we’re building toward with Agentic Data Access — a model where access is provisioned dynamically, based on policy, intent, and context, not just identity. If you’re starting to see this shift in your own environment, this is worth a look. Learn more → https://lnkd.in/eFqfm2dk

When access requests move at machine speed, governance can’t rely on human-scale processes. Agentic Data Access is about closing that gap, with just-in-time, policy-based provisioning that keeps systems responsive and accountable. This is how you operationalize AI safely. https://lnkd.in/eD7WKWM3