As AI becomes embedded in ERP workflows, a new set of constraints is coming into focus. Performance matters, but so do governance, data residency, and operational control. For many organizations, especially those operating across borders or in regulated industries, these constraints make generic public cloud deployment insufficient.
Oracle NetSuite’s experience reflects that shift. Evan Goldberg, EVP of the Oracle NetSuite Global Business Unit, notes that global customers increasingly see ERP infrastructure not as a technical detail, but as a strategic control point.
“From the beginning, we had customers who were geographically scattered but needed everyone working reliably from the same system,” he says. “That shaped how we thought about performance, access, and trust.”
Those concerns are intensifying as AI enters finance and operations. Autonomous processes touch sensitive data: payroll, supplier pricing, customer contracts, and forecasts. Inconsistent governance or unclear data boundaries quickly erode confidence.
When AI Meets Regulation
Oracle’s expansion of Oracle Cloud Infrastructure (OCI) Dedicated Regions directly addresses this problem by allowing enterprises to run a full cloud and AI stack within their own data centers or sovereign environments, while maintaining the same services, controls, and update cadence as public OCI regions. This approach reflects a broader market reality: enterprise AI must operate where the data lives, not where the cloud happens to be cheapest.
For NetSuite customers, that consistency matters. ERP systems do not tolerate fragmentation well. AI models trained or executed in disconnected environments introduce latency, reconciliation challenges, and governance gaps that undermine trust.
Goldberg frames the issue pragmatically. “People want real-time information they can rely on,” he says. “They don’t want surprises at the end of the quarter.”
That expectation extends to AI. If recommendations, forecasts, or corrections behave differently depending on geography or deployment model, adoption stalls. Infrastructure uniformity becomes a prerequisite for autonomy.
What This Means for ERP Insiders
Data sovereignty is becoming a first-order requirement for ERP AI, not a regional experiment. As governments tighten data protection and localization rules, enterprises can no longer treat infrastructure location as an afterthought. ERP providers that cannot offer consistent AI and cloud services across public, private, and sovereign environments will face growing resistance from global customers. Flexibility in deployment is becoming a baseline expectation, not a premium feature.
Consistency across environments will shape trust in autonomous ERP systems. AI-driven recommendations only gain adoption when users trust them implicitly. If outputs vary by region or deployment model, confidence collapses. Those that can deliver the same behavior, governance, and performance everywhere gain a structural advantage as autonomy increases.
Infrastructure strategy is now inseparable from ERP risk management. In the AI era, infrastructure choices directly affect financial accuracy, compliance posture, and operational resilience. For ERP buyers, evaluating AI capabilities without examining how and where they run creates blind spots. Those best positioned for long-term success will be the ones that treat infrastructure as part of the ERP contract, not as an invisible dependency.
