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August 11, 2026
Scaling Enterprise AI Beyond the Model: CEO Perspective
QBurst CEO Arun ‘Rak’ Ramchandran, in an interview with CTO, outlines what organizations often underestimate when deploying AI at scale—from integration and data readiness to governance and operational costs. Where Do the Hidden Costs of Enterprise AI Come from? Rak argues that model inference is merely the visible tip of the deployment iceberg. The real financial strain of enterprise AI lies buried in backend architecture. As companies graduate from standalone copilots to complex, multi-agent ecosystems, expenses multiply across three layers: orchestration, integration, and governance. Integration and data access alone often account for 40-60% of the total cost of ownership (TCO), as specialized AI agents require secure, real-time connections to existing systems of record to deliver tangible value. Compounding this is a steep governance and liability tax. In regulated sectors, mandated controls like audit logging, observability, and human-in-the-loop reviews can inflate base costs by an additional 40-80%. To prevent expenditures from spiraling out of control, leadership must treat AI deployment as a rigorous systems architecture problem. When companies haphazardly stitch together different agents, they create fragmented token budgets and serious accountability blind spots. What Makes Enterprise AI Ready to Scale? Rak also discusses why organizations should look beyond model accuracy or usage when assessing AI. What matters is how effectively AI improves the broader business process while operating with appropriate governance and human oversight. Central to this is what Rak calls “Glass Box AI”—an approach that makes autonomous AI decisions transparent and traceable. In practice, he points to three priorities: defining clear boundaries for agents, creating a coordination layer to manage permissions and monitor actions, and treating governance as an operating cost from the outset. Ultimately, scaling AI is as much about getting the foundations right as it is about advancing the technology itself. As Rak puts it, “You cannot automate chaos. AI is only as powerful as the data and the discipline feeding it.”
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January 19, 2026
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December 16, 2025
QBurst at Huddle Global 2025
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QBurst at Gartner IT Symposium
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