Standardize First, Automate Second: The Fastest Path to Agentic AI at Scale

Scaling agentic AI depends on process discipline, clear ownership, and governance that is in place before automation expands.

View the article for clear answers to the questions enterprise leaders are asking:

Q: Why do agentic AI pilots succeed, but scaling slows down?

A: Pilots run in controlled settings. At scale, process variation, data gaps, unclear accountability, and control requirements start to limit results.

Q: What does “standardize first” mean in practice?

A: Align teams on the same inputs, steps, decision rules, and exception handling so automation runs consistently across locations and systems.

Q: What needs to be set before agents can take action across workflows?

A: Ownership, access boundaries, escalation paths, and auditability, plus controls that match the risk of the process.

Q: What should we measure beyond hours saved?

A: Exception rates, rework, handoffs, intervention frequency, end to end cycle time, and control performance.

It also features insights from Jesús Villalobos Arce, Process Enablement GBS Americas (SSON Speaker), on how standardization and governance create the conditions for agentic AI to scale.

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