AI ROI

Enterprises are learning the biggest AI bill is not tokens but invisible AI they cannot see, govern, or measure. This article explains how ERP and IT leaders can bring AI agents, tools, and workflows under real governance before sprawl, risk, and cost spiral out of control.

Enterprises that once rewarded employees for maximizing AI usage are now discovering how quickly token costs can spiral. As finance leaders tighten budgets, AI pilots are being judged on workflow‑level outcomes, model routing discipline, and whether they actually improve delivery, code quality, and ERP operations—not just how many tokens they consume.

The SAP Discovery Center serves as a crucial self-service portal for enterprises like Agilent and Sutherland, providing essential resources and reusable architectures to streamline AI adoption and minimize risks, ultimately helping organizations select strategic starting points for their AI initiatives.

As small and midsize businesses increasingly integrate AI into operations, they are facing a shift towards viewing AI as a recurring operational expense rather than a simple software enhancement, prompting the need for clear governance and targeted use cases to ensure measurable value while controlling costs.

In Q&A with ERP Today, TDWI VP of Research Fern Halper explains why AI pilots stall, what breaks when enterprise data foundations are weak, and how organizations can operationalize AI for long-term ROI.