Introducing the HyperFRAME Research Lens: Why Primary Data Matters

The Research Lens is a recurring series built on semi‑annual surveys of global business and technology professionals. Our first Lens, State of the Enterprise AI Stack, was released this month (March 2026) with the first update planned for Q3. A second Lens, centered on Infrastructure & Operations, will be launched in Q2 2026 with its first update scheduled for Q4.

Why We Conduct Our Own Research

Independent data is essential to producing analysis that is both credible and actionable. While our daily work with vendors, service providers, and enterprise leaders gives us a strong qualitative view of the market, primary research provides the quantitative backbone that makes our insights defensible. It allows us to gather pure, un-biased data that is independently developed and not influenced by third-party vendors, providers, or special interest groups.

Primary Research Enables Us To:

Develop defensible insights. Vendor narratives and market noise can distort reality. Proprietary data allows us to anchor our analysis in measurable enterprise behavior rather than marketing claims or anecdotal signals.

Ask the right questions. Our analysts understand the technologies, the players, and the operational realities of enterprise IT. That expertise allows us to design surveys that are topical, durable, and target the right audiences to extract decision‑grade insights, not broad, generic statistics built for mass‑market consumption.

Track trends over time while remaining agile. Semi‑annual updates provide agility to adapt to changing market conditions while allowing us to measure sentiment, adoption, investment patterns, and organizational readiness over time. This provides both visibility into market direction and the ability to benchmark how expectations align (or fail to align) with actual outcomes.

Provide free, transparent, unfiltered data. Beyond our published reports, we provide open, transparent, and direct access to our underlying datasets. That’s right, we #freethedata for the benefit of all. Our analysis serves as a roadmap, not a constraint, enabling organizations to interpret the data through their own lens based on their own priorities and operating environments.

Ensure statistical relevance. By controlling our own sampling, we can guarantee that respondent demographics—industry, region, company size, and maturity—are meaningful, balanced, and representative of the markets we cover.

How We Build the Research

Primary research data is part of our analytical methodology and we believe in transparency regarding our analytical process. Each Research Lens is developed collaboratively across the HyperFRAME analyst team. We design questions that capture the current state of the market while enabling longitudinal comparison over multiple cycles.

Our research surveys, sampling over 500 enterprise business and technology leaders, are global in nature and conducted using a double‑blind methodology, ensuring respondent anonymity and eliminating vendor influence. We do not compensate respondents, and each survey is designed for data capture within a short (e.g., 30‑day) window to capture current market conditions while creating a long-term dataset over time to minimize distortion from short‑term market events.

All respondents are qualified with a high level of involvement and/or decision influence within the topic area with the further requirement that their enterprise organization be actively engaged in planning, developing, deploying, or operating within the topic area.

How This Benefits You

The global landscape is changing rapidly as AI-fueled innovations in technology and market uncertainty create both unexpected opportunities and unanticipated risks. And while your organization may be similar to others, we believe it is still unique. Here’s your chance to interpret our data the way it makes sense for you and your organization. We’re here to guide and collaborate with you and answer any questions you may have along the way. But we don’t believe in keeping valuable data behind a paywall.

Interested in understanding the drivers behind enterprise AI deployments and why only 23% of AI/ML projects launched in the last year met ROI expectations? Or how enterprises are faced with increased security risks due to a lack of AI-modernized data architectures (only 14% have it) and AI governance (missing for 60% of enterprises)? Or perhaps you want to benchmark your organization’s use of multiple foundation models, AI skills readiness, or the use of AI as a critical competitive advantage against market peers?

You can access our latest Research Lens AND the underlying data – no registration required – by clicking here: State of the Enterprise AI Stack, 1H 2026.