StackAI's Hakan Gureren was recently featured in VKTR to examine how enterprises are actually deploying human-in-the-loop (HITL) AI in production.

Drawing on his work with hundreds of enterprises across regulated industries, Gureren challenges the common assumption that the endgame for AI agents is full autonomy with humans removed entirely. What he sees in real deployments is the opposite: humans embedded in workflows at precisely the right moments, for precisely the right decisions.

The article walks through how HITL architectures play out across four settings. In legal services, AI agents read contracts and flag deviations at high speed, but no recommendation reaches a client without attorney review routed through Outlook or Gmail. At real estate and investment firms, deal-review agents assemble opportunity profiles from multiple systems, then pause for analyst approval via Slack or Teams before any business-critical action, since a fabricated cap rate or misread rent roll isn't a recoverable error. In IT support, AI proposes ticket resolutions that an agent approves, edits, or escalates before anything reaches the user. And in professional services, AI compresses proposal drafting from days to hours while a human ensures the firm still sounds like itself.

Gureren identifies a common architecture beneath all four: the agent handles reading, searching, summarizing, and drafting, while the human owns the moment of judgment. He notes that the strongest deployments avoid adding friction by routing checkpoints through tools reviewers already use rather than separate consoles or forms. Adoption clusters in law, financial services, investment management, and healthcare, where the cost of a wrong answer outweighs the cost of a slow one. His closing argument is that in high-trust, regulated environments, human-in-the-loop isn't a compromise on the vision of AI transformation but the vision itself. Read the full article here.