Three insights you may have missed from theCUBE's coverage of Pure Accelerate
As enterprises advance their artificial intelligence initiatives, they're discovering that the real constraint isn't model sophistication - It's data. AI outcomes now depend on whether organizations can access, mobilize and operationalize data as an active system rather than a passive repository. This shift was a defining theme at Pure Accelerate 2026.
Key Takeaways
- Three insights from Pure Accelerate 2026 show how governance, partner ecosystems and infrastructure modernization shape enterprise AI outcomes at scale.
- There's a new data dynamic - which makes data sort of primary - and they call it data primacy.
I think it's a very good term, where data is really central to everything.
- Enterprises that treat governance as a foundational control layer rather than an afterthought are better positioned to manage data access , security and compliance as AI deployments scale, explained Lynn Lucas , chief marketing officer of Everpure, and Phil Goodwin , research vice president of multicloud data management and protection at IDC Corp.
"This pivot to more of a data-centric model rather than hardware-centric ...
- " Addressing those challenges requires more than new infrastructure.
Everpure's Enterprise Data Cloud Success Blueprint is a framework designed to help organizations assess data maturity, noted Stephanie Richardson , vice president of product marketing at Everpure.
- That reality is driving greater collaboration across the technology ecosystem to help customers transform raw enterprise data into AI-ready data and measurable AI outcomes, noted Shawn Rosemarin , vice president of R&D and customer engineering at Everpure, and Jason Hardy , vice president of storage technology at Nvidia Corp.
Stats & Key Facts
- #UPDATED 12:30 EDT / JUNE 24 2026 AI Three insights you may have missed from theCUBE's coverage of Pure Accelerate by Victoria Gayton As enterprises advance their artificial intelligence initiatives, they're discovering that the real constraint isn't model sophistication - It's data.
Three insights from Pure Accelerate 2026 show how governance, partner ecosystems and infrastructure modernization shape enterprise AI outcomes at scale. UPDATED 12:30 EDT / JUNE 24 2026 AI Three insights you may have missed from theCUBE's coverage of Pure Accelerate by Victoria Gayton As enterprises advance their artificial intelligence initiatives, they're discovering that the real constraint isn't model sophistication - It's data. AI outcomes now depend on whether organizations can access, mobilize and operationalize data as an active system rather than a passive repository.
This shift was a defining theme at Pure Accelerate 2026 . The challenge is not simply whether organizations can store data, but whether they can mobilize and operationalize it to achieve meaningful AI outcomes, according to Christophe Bertrand , principal analyst for cyber resiliency and data management at theCUBE Research. "This is not about storage anymore.
It's about data," Bertrand said in a keynote analysis during the event. "And that was very clear in the [chief executive officer's] address. There's a new data dynamic - which makes data sort of primary - and they call it data primacy.
For more details please read the original article at SiliconANGLE AI.
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