Another question to ask is: is that data properly secured? To function, AI agents need access to data — sometimes highly restricted data. “If you build an AI agent using your permissions, and I get my hands on the agent, can I now see data that I shouldn’t be able to see?” he asked. “I would say, make sure your data is secured before you start building AI agents, and that the user security will stay in force from the data level up to the agent level.”
While agentic AI is still a maturing technology, SaaS providers like Salesforce and ServiceNow are rapidly closing the gap by building no-code AI agent platforms that promise to make it easy for enterprises to automate parts of a workflow. “So as we go through this year, I think we’ll see more and more workflows being automated and a lot of time saved,” Coshow said.
The agentic AI market is a mix of startups, large established players, and homegrown, privately developed applications, said Coshow. “All the big players are going to be building in the ability to create AI agents inside their platform, and for obvious reasons. If I’m using a software platform and I can’t build automation, I can go someplace else to build that automation,” he said.
This story originally appeared on Computerworld
