Amy Zwagerman Outlines Why Successful AI Adoption Requires Operations First, Automation Second in Inc.

In an expert column for Inc., Pepperdine Graziadio Business School's Amy Zwagerman argues that successful AI adoption depends far less on technical coding skills than on operational clarity, the ability to map, simplify, and document how work actually happens before applying technology. Recounting her own experience building a complex, 88-step automated workflow that failed due to flawed underlying logic rather than broken software, Zwagerman highlights a critical misconception in AI implementation: while human brains seamlessly handle ambiguity and unwritten judgment calls, machines require completely structured and explicit processes.

This gap between pitch and reality helps explain high failure rates across corporate tech initiatives; RAND estimates over 80 percent of AI projects fail to deliver business value, while MIT research indicates 95 percent of generative AI pilots yield zero measurable return. Successful initiatives succeed because they are deeply integrated into existing operations rather than bolted on as standalone tools. Pointing to SpaceX’s "The Algorithm" a five-step framework that places automation dead last behind questioning requirements, deleting unneeded steps, simplifying systems, and accelerating cycle times, Zwagerman emphasizes that rushing to automate before streamlining operations leads to costly missteps.

Ultimately, organizations seeking speed from AI and automation must first slow down to audit their daily operations. As Zwagerman notes, the teams that successfully harness AI are not necessarily those with the most advanced technical expertise, but those willing to do the foundational work of mapping their processes, eliminating inefficiencies, and building clear management systems.

Read the full opinion article in Inc. here.