Kevin Coleman on why approvals are the hard part of enterprise agents

At the AI Engineer World’s Fair 2026, Ravenna co-founder Kevin Coleman discussed how the company automates internal employee-support tasks such as software access, payroll updates, and IT requests through a combination of AI agents and deterministic workflows. He argued that enterprise approvals must be applied at the level of individual resources and requesters rather than entire workflows, because actions that appear similar can carry very different risks depending on the systems and permissions involved. Ravenna uses deterministic processes for consequential tasks such as routing access requests to approvers, while delegating lower-risk work, such as creating collaboration groups or channels, to agents. The company’s service-desk users are increasingly building automations themselves, including nontechnical employees, while Ravenna also uses AI internally for customer configuration, sales support, and event outreach despite high model costs. To address customer demand for many system connections, Ravenna created a coding agent that can research APIs and generate integrations, though this expansion creates new governance challenges because every generated action must be assessed for risk and approval requirements. Coleman said the company’s main constraint has shifted from integration coverage to prioritizing customer requests without compromising software quality, while emphasizing that permission modeling and resource classification remain more important for enterprise agents than model capability alone.

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