NEW YORK, Dec. 15, 2025 (GLOBE NEWSWIRE) -- The C suite conversation is shifting fast according to new enterprise customer survey results released by Dan Herbatschek, CEO of Ramsey Theory Group. Enterprise leaders are no longer debating whether to deploy AI, but they are demanding clear answers to four fundamental questions that determine whether AI creates durable value or unmanaged risk.
“Results of our new enterprise customer survey this month shows that executives want AI that is controllable, cost-transparent, defensible, and operational at scale without sacrificing governance,” said Herbatschek.
These are the four top questions Ramsey Theory Group’s enterprise customers are asking right now:
1. Who Controls AI at Scale?
Enterprise leaders are increasingly concerned about the sprawl of AI models, agents, and third-party services embedded across the organization. What began as isolated pilots has evolved into dozens—sometimes hundreds—of AI systems influencing decisions, workflows, and customer interactions.
“The real fear isn’t that AI will fail,” Herbatschek said. “It’s that no one can clearly answer who owns it, who oversees it, or who can shut it down when it behaves unexpectedly.”
Boards and regulators are now pressing for centralized visibility, defined accountability, and enforceable controls that span models, agents, and vendors—not just individual applications.
2. How Much Is It Actually Costing Us?
AI’s financial footprint is becoming harder to ignore. Beyond software licensing, enterprises are grappling with GPU consumption, inference costs, data movement, integration overhead, and operational staffing—often without clear cost attribution.
“Many enterprise leaders we surveyed are discovering that AI cost overruns don’t show up on day one,” said Herbatschek. “They surface months later, when no one can tie spend back to business outcomes.”
As a result, enterprises are shifting from excitement about model capabilities to scrutiny of unit economics, ROI per use case, and FinOps-style discipline for AI workloads.
3. What Risk Are We Taking: Legally, Financially, and Reputationally?
From regulatory exposure to data leakage and automated decision errors, AI introduces a new class of enterprise risk. It is one that traditional compliance frameworks were not designed to handle.
“AI risk isn’t hypothetical anymore,” Herbatschek explained. “It’s operational risk, legal risk, and brand risk—all at once.”
Executives want provable answers to questions such as: Can we audit AI decisions? Can we explain them to regulators? Can we demonstrate appropriate human oversight? Increasingly, AI governance is being treated like financial controls or cybersecurity. It is a foundational requirement, not an afterthought.
4. How Do We Operationalize AI Without Losing Governance?
The most difficult challenge enterprises that Ramsey Theory Group surveyed have been facing is scaling AI without creating chaos. Leaders want AI embedded deeply into operations, but not at the expense of transparency, accountability, or trust.
“The goal isn’t to slow AI down,” said Herbatschek. “It’s to operationalize it responsibly, so innovation and governance move together instead of in opposition.”
This has led to the rise of centralized AI councils, standardized lifecycle management, human-in-the-loop controls, and continuous monitoring—all designed to ensure AI systems remain aligned with business intent and regulatory expectations.
About Ramsey Theory Group
Founded by CEO Dan Herbatschek, New York-based Ramsey Theory Group has offices in New Jersey and Los Angeles. The firm applies advanced mathematical frameworks and agentic AI to secure, optimize, and modernize enterprise operations across the logistics, automotive, field service, and healthcare industries. Its technology helps organizations detect anomalies earlier, automate decision-making safely, and govern AI systems with full transparency and control. Visit https://www.ramseytheory.com/ to learn more.
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