AI is quickly moving from boardroom buzzword to boardroom headache. Enterprises are waking up to the fact that bringing large language models in-house is not just about performance or cost, but about control, accountability, and trust. In this episode of Tech Talks Daily, I sit down with Octavian Tanase, Chief Product Officer at Hitachi Vantara, to unpack what this shift really means for business and technology leaders.
Octavian explains why governance has become the defining challenge of the AI era. Companies are under pressure not only to innovate but also to meet new regulatory demands and maintain trust with customers. That requires more than patching together tools or hoping for transparency from public AI providers. It means creating governance frameworks that deliver traceability, auditability, and explainability as standard practice, not as afterthoughts.
We explore why vector databases may need something like a time-machine capability to document when and how information is added, giving enterprises a provable audit trail. This level of accountability supports both internal oversight and external compliance, turning abstract AI ethics debates into real operational requirements.
Our conversation also turns to the role of infrastructure. Hitachi Vantara’s VSP One, with its tagline “One Data Platform, No Limits,” has been built to simplify data complexity across block, file, and object storage while providing a unified foundation for AI workloads. Octavian shares how this unified approach helps enterprises run compliant, explainable, and efficient AI across hybrid environments that span both on-premises and the cloud.
This isn’t just a story about technology, but about the future of trust in digital business. If AI remains a black box, its value will always be limited. If it becomes explainable, traceable, and accountable, it can transform not only efficiency but also relationships with customers, regulators, and partners.
So, how can leaders strike the right balance between governance and innovation without slowing down progress? Octavian leaves listeners with a forward-looking perspective on what the next few years of enterprise AI will demand, and why those who build on strong governance today may end up with the most resilient advantage tomorrow.
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