For the past several years, enterprise IT priorities have been clearly defined: build resilience, maintain compliance and ensure the ability to recover rapidly after disruption. Those priorities remain critical, but a new strategic question is emerging:
How do organizations responsibly support AI when their most valuable data lives across hybrid environments?
In this video, Alex Coombes, Vice President of Strategic Partner Development and Paul Dadamo, Director, Strategic Partner Development - Business at Commvault, discuss how modern enterprises are navigating this transition.
Overcoming the Complexity of AI Adoption
Enterprises are hybrid by nature. Some workloads are well suited for the cloud, while others need to remain on-premises because of sovereignty, governance, latency, or operational requirements. AI is no different. As organizations move from experimentation to production, they need the flexibility to bring AI-capable infrastructure closer to where enterprise data already lives.
VAST helps deliver that flexibility with a platform designed to host data on-premises at the scale and performance required for AI, analytics, and other data-intensive workloads.
According to Coombes, this is driving a major trend: regulated enterprises and organizations are starting to build their own AI factories within their own data centers. The primary driver behind this shift is total data sovereignty.
Why are they doing this? Sovereignty. Sovereignty of their data. Making sure that all of the prompts and the information they upload to AI stays within the walls of their own fort.
- Alex Coombes, Vice President, Vice President of Strategic Partner Development, Commvault
A Future-Ready Foundation for Responsible AI
AI outcomes depend on the quality, coverage, and accessibility of enterprise data. For many organizations, that data spans cloud, SaaS, databases, file systems, backup environments, and on-premises infrastructure. Commvault helps customers protect and manage that data across a broad range of workloads, while VAST Data provides a platform designed for the scale and performance demands of AI, analytics, and other data-intensive workloads.
Together, the focus is on helping organizations establish a stronger data foundation for AI, wherever those workloads need to run.
