Some companies get real value from AI agents. Most don’t, yet. The difference usually comes down to a handful of decisions made before the model gets involved at all.
Start narrow
Companies actually getting value don’t start with an ambitious, open-ended use case. They automate one workflow, document review, support triage, code migration, prove it works, then expand. Cognizant’s tiered model follows exactly this pattern: strategy first, then a scoped pilot, only then full delivery.
The model usually isn’t the bottleneck
Governance, integration, and workforce readiness separate pilots that scale from pilots that stall, not model capability. Budget for those specifically.
Set autonomy by reversibility
Full autonomy for reversible actions, drafting, internal analysis. Explicit confirmation for anything that sends, deletes, or triggers a real transaction. That one distinction prevents most of the failures that make headlines. Our full risk guide covers it in depth.
Build workflows that can swap between model providers rather than locking into one vendor’s API. Pricing changes and abrupt shutdowns have both happened this year.
See McKinsey’s own research on the state of enterprise AI adoption.
