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AI · 2026-08-05 · 8 min read

Agentic AI in enterprise operations: what works in production today

Beyond chat: where multi-step agents pay off (procurement, support, IT ops), the failure modes we design against, and the evaluation harness every deployment needs.

The pattern that pays

Agents earn their keep when a task requires reading several sources, applying rules and producing a structured result that a human approves — supplier quote comparison, ticket triage with remediation, month-end reconciliation. Open-ended chat is the least valuable use.

Design against the failure modes

Hallucinated facts, silent tool failures and runaway loops are engineering problems with engineering answers: retrieval with citations, typed tool contracts, step budgets, and a human approval gate before any write to a system of record.

Evaluate like you test software

Golden datasets per workflow, automatic regression on every prompt or model change, and production sampling with human review. If you cannot measure accuracy, you cannot ship an update safely.

Cost and residency

Route simple steps to small models, cache retrieval, and keep data in-region. A well-designed workflow costs cents per task — and stays inside your compliance boundary.

Written by the Kunal Bearings engineering teamQuestions about this topic? Talk to us — we reply within one business day.

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