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AI and Data Priorities for 2026
A strategic roadmap highlighting the most critical AI and data focus areas for 2026
AI at a Standstill? How Automation Unlocks Real ROI
In this episode of WWT Presents Research, host Robb Boyd and Corey Wanless, a principal solutions architect, explore ways in which organizations can automate infrastructure and processes for AI success.
A Guide for CTOs to Get Started with Enterprise AI
This report gives CTOs a decision-making framework to build AI programs that are sequenced around business outcomes, governed before they scale and staffed for production.
Powering the Next Frontier of Academic Research at The Texas A&M University System
Discover how The Texas A&M University System partnered with WWT to build VISION, one of the largest supercomputing environments in higher education that's powering a new wave of discovery, collaboration and high-performance experimentation.
Using Data to Pave the Way for AI and Automation
C-level leaders are looking to artificial intelligence (AI) to accelerate automation within their organizations. But in the rush to adopt AI, many forget that the success of both AI and automation hinges on an organization's data maturity.
Join Anshul Chaturvedi, a principal consultant with WWT focused on data, analytics and AI, as he talks about how organizations can mature their data capabilities to maximize their AI and automation investments. Anshul breaks down the interplay between automation and AI, pragmatic ways to start incorporating AI into an automation journey and provides tips on communicating progress to executive and line of business stakeholders.
What's new
Special Olympics: From Paper Schedules to the Most Ambitious App in USA Games History
Using AI, WWT built the Champions app to deliver more than anyone thought possible for every athlete, coach, fan, volunteer, delegate and guest in attendance.
Partner POV | Agentic AI Needs Rack-Scale CPU Performance – AMD EPYC Delivers It Today
Agentic AI is changing the shape of infrastructure.
The AI Data War: Winning the Battle for Enterprise Data Supremacy
Enterprise AI ambitions are outpacing the data foundations that support them. This research note breaks down the forces driving this crisis (legacy architecture debt, data gravity and ungoverned AI data sprawl) and offers a workload-first, platform-neutral roadmap to help CIOs and CDOs build the data foundations AI actually demands.
Closing the Enterprise Data and AI Readiness Gap: A Guide for Enterprise Leaders
Most enterprises have the platforms. Few have the operating discipline to activate them. This paper makes the case for treating data readiness as a leadership priority and outlines four actions to close the gap.
Partner POV | IBM Data Gate for Confluent: Turning Z data into real-time action
IBM Data Gate for Confluent revolutionizes enterprise AI by transforming IBM Z data into real-time event streams. This seamless integration enhances responsiveness in financial services, fraud detection, and transportation, enabling instant insights and proactive management.
A Practitioner's Guide to Closing the Enterprise Data and AI Readiness Gap
Enterprise AI initiatives stall not from a lack of technology but because data isn't ready to be activated. This paper gives data engineering and AI practitioners a structured framework for building activation-ready data foundations, covering lifecycle discipline, medallion architecture, governance design and execution sequencing.
NetApp Data Protection
In today's business environment, data is the operational backbone of every organization, and the cost of losing access to it even briefly can be catastrophic. Ransomware, unplanned outages, regulatory mandates, and the pressure to accelerate application development have made data protection one of the most urgent conversations happening in every customer account. What separates NetApp ONTAP from every other platform in this conversation is a fully integrated, storage-native data protection stack that works together by design no third-party tools, no patchwork solutions. Snapshot technology delivers near-instantaneous recovery points that serve as the foundation for everything else. SnapMirror extends those recovery points across data centers and into the cloud for disaster recovery with RPOs in minutes and zero downtime with SnapMirror Business Continuity. SnapVault turns that same efficiency into long-term backup that eliminates legacy tape and backup software complexity. SnapLock adds immutability to satisfy regulatory compliance while hardening against ransomware. And FlexClone creates instant, writable, space-efficient copies that accelerate dev and test without adding infrastructure cost. Together, these capabilities make NetApp a single platform conversation covering business continuity, compliance, and operational agility and that is exactly what we are here to explore today.
NetApp Data Mobility using FlexCache
In today's distributed enterprise, data proximity is performance. NetApp FlexCache is a native ONTAP caching technology that creates read-optimized volumes closer to where users and workloads actually live — whether that's a remote office, edge site, or cloud region — without replicating the full dataset. The result is dramatically reduced latency, lower WAN bandwidth consumption, and a seamless experience for end users who never know the data isn't local. For customers struggling with slow file access across geographically dispersed locations, or trying to accelerate high-performance compute workloads without the cost of full data duplication, FlexCache delivers enterprise-grade performance where it's needed most — at a fraction of the infrastructure overhead.
The Boardroom Reckoning on AI: Why AI Demands a New Kind of Leadership
AI is forcing a new leadership challenge inside the enterprise, in which boards are expected to oversee a fast-moving technology they do not manage day to day, while executives are tasked with deploying it responsibly at speed. In this episode, Byron Loflin, Global Head of Board Advisory at Nasdaq, and WWT AVP of Global Cyber Advocacy Kate Kuehn explore what that means for modern governance — from board-level AI literacy and trust between directors and management to error reporting, escalation paths and the growing need for stronger oversight as AI systems become more capable and more autonomous.
Partner POV | Why Physical AI Demands a New Data Architecture
Physical AI is revolutionizing industries by integrating AI models with real-world machines, demanding resilient, high-performance data infrastructures. Unlike digital AI, its failure impacts production and safety. This paradigm shift requires a data-first architecture, emphasizing portability, security, and scalability to ensure seamless, deterministic operations in dynamic environments.
Partner Overview | How Commvault & Satori Deliver Unified Data Access Governance for AI & Cloud
AI is rewriting the rules of data risk. Every new prompt or model expands the attack surface — and without unified data access governance, organizations cannot fully understand what sensitive data they have, who can access it, or what AI tools might expose. In this demo, see how Commvault Cloud, powered by Satori, discovers sensitive data, governs user + AI model access, enforces dynamic masking, and audits every interaction in real time.
Closing The Execution Gap For Store Modernization
Retail modernization often fails due to execution gaps, not strategy flaws. Overcoming technology debt, execution variability and AI expectations requires a holistic approach. By focusing on end-to-end lifecycle management, retailers can transform technology investments into growth drivers, ensuring seamless operations and enhanced customer experiences. Start small, assess and evolve strategically.
Partner Overview | Satori Named Leader in GigaOm's Data Access Governance Radar Report
Why governing data usage has become a security imperative.
A Guide for CTOs to Get Started with Enterprise AI
This report gives CTOs a decision-making framework to build AI programs that are sequenced around business outcomes, governed before they scale and staffed for production.
How Jack in the Box is Building the Data Foundation for AI
What does it really take to make AI useful in the enterprise? In this episode of the AI Proving Ground Podcast, Jack in the Box VP of Data and Analytics Paul Bruffett and WWT Managing Director of AI and Data Analytics Daniel Morrisroe detail how to turn fragmented data, legacy systems and disconnected workflows into an operational foundation the business can actually use. From modular data products and self-service analytics to forecasting, personalization and the road to more autonomous systems, this conversation offers practical lessons for leaders trying to move from modernization to measurable AI outcomes.
How UAE-Based Core42 is Rethinking AI Infrastructure From the Ground Up
How do you build an AI environment the business can scale, security can defend, regulators can accept and teams can actually use? In this episode of the AI Proving Ground Podcast, Core42 CTO Raghu Chakravarthi and WWT EVP Kraig Ecker discuss why sovereignty extends beyond data residency, heterogeneous infrastructure is becoming non-negotiable and why agents will sharply increase the need for observability, security guardrails and scalable inference design.
Garbage In, Garbage Amplified: The AI Feedback Loop Most Companies Miss
Most teams are using AI to summarize and connect internal data. Fewer realize they may be creating a feedback loop in the process. When AI-generated content gets stored alongside source material, it can quietly shift what is treated as truth. This blog article breaks down how it happens, why it matters, and one simple structural change that can prevent it.
Before You Scale AI, Fix Your Data Foundation
The new AI bottleneck is whether your enterprise data can be trusted, governed, and used at speed. Recorded live at NVIDIA GTC, this episode of the AI Proving Ground Podcast features Tore Sundelin of NetApp and Derek Elbert of World Wide Technology discussing why unstructured data, policy-based governance, data classification and unified AI data pipelines are becoming critical as enterprises push toward agentic AI and production-scale inference.
Partner POV | 4 trends that will reshape the autonomous workspace in 2026
AI is reshaping work, demanding efficiency and security. By 2026, IT consolidation will prioritize security, AI will enhance employee experiences, data sovereignty will gain importance, and IT leadership will balance innovation with trust.