Feb 9, 2026 · 4 min read
Enterprise software has always run on a simple power law: whoever controls the data wins. CRMs, ERPs, and HRIS platforms could be clunky, slow, and annoying, and still dominate because they were the data authority, the place the company treats as correct. Integrations pointed at them, workflows routed through them, and every downstream system had to bow to that authority. That dominance depended on one assumption: the data was inseparable from the application. That assumption just broke.
Most business systems are small in an absolute sense. A full Salesforce account, a decade of Jira tickets, or every Asana project for a company is tiny compared to modern storage and bandwidth. The advantage was never size. It was friction. You had to log in, learn the UI, and accept the workflow just to see the data, and that interface was the trap. Agents dissolve that trap.
When you connect an agent to your stack, you give it APIs, credentials, and context so it can actually do the job. Then it starts working: it fetches customer data to answer questions, scans projects to summarize risks, and reads documentation to draft updates. Because the dataset is small, a full copy happens fast, and keeping it synchronized is trivial. The data isn’t trapped anymore. It’s mirrored.
Once the agent has the data, it becomes the primary interface. People stop opening Salesforce to find a pipeline trend, stop searching Notion for the one doc they need, and just ask the agent. At that point, the old data authority is no longer where the work happens. It becomes a write endpoint, a backend, a place the agent pushes updates to. The data authority in practice is now the agent’s memory.
The obvious response is to lock the gates: rate-limit the API, restrict access, slow the agent down. But that makes the agent worse, which defeats the entire reason you connected it in the first place. And it doesn’t work anyway. A capable agent will build a cache, pull what it can, store it locally, and sync on its own schedule. The limit doesn’t prevent duplication. It just delays it.
There’s a world where today’s incumbents survive by shifting from owning the data to governing it. They become the place where permissions are defined, audits are kept, and compliance is enforced. That work matters, but it’s a smaller business. Governance is a feature, not a platform. If your only defensibility is “we store your data,” you are exposed.
This is the uncomfortable question for every enterprise vendor: if the data can leave instantly, what is your value? The credible answers look like workflow depth that’s hard to replicate, network effects between users, domain-specific intelligence embedded into the product, and execution infrastructure that agents rely on. “We’re where the data lives” is not enough anymore. For twenty years, it was. Now it’s just table stakes.
The agent doesn’t just store data, it uses it. It synthesizes across tools, routes work, makes decisions, and executes, which makes it the new hub even if the old app still exists in the background. So the real battle isn’t about where the data sits. It’s about where the work happens.
Data authorities were built for a world where data was trapped inside the interface. Agents undo that trap. When the assistant holds the context and drives the workflow, the old authority layer becomes a backend detail. If you sell software that depends on data gravity, you’re now in a race to build something else: execution depth, governance, or a workflow that the agent can’t replace. The agent is no longer just a helper. It’s the new data authority.