VentureBeat is making a significant shift beyond its traditional role as a news outlet, formalizing its commitment to deep, proprietary enterprise AI research with the appointment of its first-ever Lead Analyst. Rob Strechay, who joins from theCUBE Research where he served as managing director and principal analyst, will anchor this new initiative. His arrival signals a calculated expansion: VentureBeat Research is being built specifically to serve the directors, VPs, CIOs, and CTOs who are now accountable for evaluating, purchasing, and deploying enterprise AI systems at scale, moving past surface-level coverage to provide the kind of architectural and operational analysis that technical decision-makers can defend in budget reviews.
Why VentureBeat Is Shifting from News Coverage to Deep Research
The enterprise AI landscape is undergoing a fundamental transformation. For the past two years, the dominant narrative revolved around experimentation: which foundation model to try, how to build a proof-of-concept chatbot, and what the technology could theoretically do. That phase is ending. Organizations are now moving generative AI into production, and the questions they face are far more concrete and operationally demanding. They need to know how to orchestrate environments that span multiple vendors, where security vulnerabilities emerge in agentic pipelines, and how to solve the utilization problems that are quietly draining infrastructure budgets.
Answering those questions requires more than daily reporting. It demands empirical data, forensic analysis of infrastructure choices, and a deep understanding of how systems behave under production-grade pressure. This is the gap VentureBeat Research is designed to fill, and Strechay’s appointment is the foundational step in that strategy.
The Practitioner Background That Sets Strechay Apart
Strechay brings nearly three decades of experience that spans the full spectrum of enterprise technology. He has sat on every side of the table: as a practitioner managing infrastructure, as a product executive at multiple startups including Zerto, as an executive at Amazon Web Services where he helped build a new analytics service, and as an industry analyst at Enterprise Strategy Group and most recently at theCUBE Research and SiliconANGLE.
This breadth matters because the most valuable research for enterprise buyers does not come from analysts who have only studied technology from the outside. It comes from people who have built systems, managed budgets, and lived through the consequences of architectural decisions. During his time at theCUBE, Strechay conducted executive interviews and analyzed the evolution of cloud, data, and AI infrastructure, giving him a direct line into how the largest enterprises in the world are thinking about their technology stacks.
His coverage at VentureBeat will initially focus on four critical domains: cloud infrastructure, advanced data infrastructure, platform engineering and DevOps orchestration and observability, and the intersection points where AI and enterprise security collide. These are the areas where the most expensive decisions are being made today, and where the margin for error is shrinking.
What Is the VB Pulse Survey and Why Does It Matter?
VentureBeat has already established a proprietary data engine around its monthly VB Pulse surveys, which track five dimensions of enterprise AI adoption: agentic orchestration, agent reliability and evaluations, agentic security and identity, AI infrastructure and compute, and context layers including retrieval-augmented generation (RAG). These surveys are designed to capture the actual state of deployment across organizations, not the aspirations or vendor talking points that dominate the market.
The June report on agentic orchestration, drawn from a survey of 145 enterprises, produced a finding that carries real strategic weight: two-thirds of those organizations had hedged their AI model strategy rather than committing to a single provider. That decision proved prescient when Anthropic’s Claude models suffered an outage in June, reinforcing for many enterprises the risk of vendor lock-in at the model layer. Data points like these are exactly what technical decision-makers need when building their own multi-vendor strategies.
Strechay’s infrastructure-level expertise complements this survey engine. He has already contributed by providing a substantive review of the AI Infrastructure & Compute survey before it went into the field, and in May he published an analysis of enterprise GPU utilization that examined the compute waste sitting inside enterprise AI infrastructure — a problem he estimates costs enterprises billions in underutilized hardware.
The \$40 Billion GPU Utilization Problem That Enterprises Cannot Ignore
Strechay’s May analysis highlighted a specific, measurable problem that is often overlooked in the rush to deploy AI: GPU utilization. The underlying infrastructure that powers enterprise AI workloads is expensive, and much of it is being wasted. When organizations provision GPUs for inference or training without proper orchestration, they end up paying for compute cycles that never actually do work.
This is not a trivial inefficiency. With enterprise AI infrastructure spending accelerating into the hundreds of billions globally, even modest improvements in utilization translate into massive cost savings. Strechay’s analysis pegs the scale of this waste at levels that demand executive attention, and his work will continue to focus on the practical mechanisms — observability, scheduling, right-sizing — that can address it.
For CIOs and CTOs who are being asked to justify their AI infrastructure budgets, this kind of analysis offers something that vendor benchmarks and marketing materials cannot: a clear-eyed look at where money is being burned and how to stop it.
VB In Conversation: From High-Level Overviews to Architectural Blueprints
The expanded research footprint will be anchored by a deepening of VentureBeat’s existing VB In Conversation video interview series, which Strechay will host. The format is being redesigned to move beyond the standard industry overview into something far more granular. Each episode will bring architectural blueprints, actual deployment barriers, and back-end infrastructure realities to light through in-depth technical interviews with the architects and product leaders behind leading enterprise AI systems.
The goal is to give viewers an unvarnished look at which tools perform under production-grade pressure — and which do not. In an environment where every vendor claims to be the solution, the ability to see behind the curtain of real deployments is invaluable. Strechay’s experience hosting executive interviews at theCUBE makes him well-suited to this format, and his technical background ensures he will press for specifics rather than accepting generalities.
The series will appear on VentureBeat and on VentureBeat’s YouTube channel, alongside written analysis from Strechay on the site. This multi-format approach ensures that the research reaches decision-makers whether they prefer to read, watch, or listen.
What Enterprise Practitioners Can Expect from VentureBeat Research
The research offering is built with a specific audience in mind: the technical decision-makers who are accountable for outcomes. These are the people who cannot afford to be wrong about their platform choices, because the cost of a bad infrastructure decision at enterprise scale is measured in millions of dollars and months of lost time.
“VentureBeat has built an audience of enterprise builders and technology buyers that any analyst would want to serve,” Strechay said. “My goal is to use deep empirical metrics and VentureBeat’s proprietary tracking data to help enterprise buyers and the people building for them make sound platform and infrastructure decisions during the most disruptive transition enterprise technology has seen.”
For practitioners who want to participate in the monthly VB Pulse surveys or arrange an analyst briefing with Strechay, the research team can be reached directly. This open channel is intentional: the research is designed to be responsive to the questions the market is actually asking, not the questions that analysts assume are important.
The Strategic Significance of a Dedicated Research Function at a Media Company
VentureBeat’s move to formalize its research capabilities reflects a broader trend in enterprise technology media. As the pace of change accelerates, the gap between what news coverage can provide and what decision-makers actually need has widened. News tells you what happened. Research tells you what it means, how it compares, and what you should do about it.
By embedding a full-time analyst with Strechay’s credentials, VentureBeat is effectively creating a new category of offering: analyst-grade research delivered through a media company’s distribution engine. This gives the research reach that traditional analyst firms struggle to match, while preserving the independence and rigor that enterprise buyers demand.
The timing is also significant. The enterprise AI stack is being rewritten in real time, and the vendors who are winning today may not be the ones who win tomorrow. Organizations that make infrastructure decisions based on current momentum rather than empirical evidence are taking on enormous technical debt. VentureBeat Research, with its combination of proprietary survey data and deep technical analysis, is positioning itself as a hedge against that risk.
Strechay’s appointment is the opening move, not the endgame. The research engine will continue to expand, with new surveys, new data products, and deeper coverage of the technologies that are reshaping enterprise infrastructure. For the technical decision-makers who are navigating this transition, the arrival of an independent, empirically grounded voice is a welcome development.
