Why Enterprise AI Agents Need a New Kind of Operating Procedure

With 80% of AI projects failing to return business value, your team has an urgent opportunity to overcome the underlying challenges and build an AI foundation. This whitepaper explores the inherent problems with applying standard operating procedures to agentic operations and what to do instead to build AI agents that actually work in production.

Too often, organizations build AI workflows that automate work the way it's supposed to be done instead of how it actually happens. In reality, human operators use undocumented workarounds, especially when dealing with edge cases and exceptions. Without this operational context or the ability to audit AI decision-making, these organizations won’t be able to build AI agents that can handle real workloads reliably and efficiently.

That means CIOs, CTOs, COOs, and heads of transformation need to define the requirements for their AI foundation long before AI pilots are rolled out.

This practical guide outlines how missing context, governance, and measurement capabilities are setting up your AI initiatives for failure, as well as how you can start investigating the gaps in your AI foundation with Skan AI's BASE framework: a systematic approach to rolling out agentic operations that deliver returns on investment in weeks instead of years.