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EMA at 30: The Value of Consistency

Shamus McGillicuddy

Enterprise Management Associates (EMA) turns 30 this year. We're not the largest analyst firm, and we're not the loudest. What we have always strived to be is honest, independent, and reliable.

After three decades in this industry, we think those are the things that matter most.

The Challenge for Today's Buyers and Sellers

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment.

Technology markets are more competitive, fast-moving, and crowded than ever. Vendors face constant pressure to differentiate, explain increasingly complex products, and respond to rapidly changing buyer expectations. The result is a cornucopia of reports, white papers, webinars, demos, and perspectives … often well-intentioned, but difficult to evaluate in aggregate.

Today's buyers are moving beyond "quadrants" and asking harder questions like whether a product works in their environment, what the implementation really looks like, and what the trade-offs and "gotchas" are.

They require context, experience, and insight across multiple deployments, architectures, and organizational realities.

The challenge is clarity.

The Role of the Analyst Has Changed

Thirty years ago, analysts were translators. Documentation was sparse, and vendors weren't always great at explaining what their products actually did, so analysts helped buyers understand the options.

Today, many vendors have robust websites with videos, blogs, podcasts, white papers, and an AI chatbot ready to answer your questions.

The hard part is cutting through the marketing to understand what's real. Does a product actually do what the demo suggests? Is a new product category genuinely new, or is it a repackaging of a legacy technology?

Things have only gotten harder with AI. Every vendor is an AI company now. Cutting through that noise requires experience, skepticism, and a willingness to ask uncomfortable questions.

The analyst role has shifted from "explainer" to "the person who's seen this movie before."

What We've Tried to Be

EMA has never tried to compete with the largest firms on scale. We don't have scores of analysts, and we don't cover every category.

What sets us apart:

  • Independence: Our research is driven by what practitioners need to know, sometimes at the expense of a sale. That may not be a model that makes you the biggest, but it lets us say what we think.
  • Technical depth over breadth: We'd rather be the definitive source on five topics than a surface-level source on fifty. If we cover something, we cover it well.
  • Human judgment: In an age of AI-generated content, there's still value in a person who has the experience, will look you in the eye (or video camera), and tell you what they believe.
  • Consistency: Thirty years of showing up, building relationships, and earning trust through accuracy.

Why This Matters More Now

Even the most mature technology markets are experiencing disruption today, thanks to AI, cloud transformation, rising security threats, compliance requirements, and more. As new vendors emerge and try to define new categories, well-established vendors are trying to figure out their place in this volatile environment. Amidst this disruption, failure and disappointment are inevitable.

That's exactly when you need someone who's been observing the market long enough to recognize the patterns, who remembers what happened the last time vendors promised to solve all your problems, and who can ask the right questions.

Experience and independence are requirements for honest guidance in that environment.

Thirty Years

Thirty years is a long time. Long enough to see technologies come and go, vendors rise and fall, and categories reinvent themselves. Long enough to recognize when the fundamentals don't live up to the hype.

We're still here because we've earned trust by being consistent, independent, and honest. That's the only goal for the next thirty.

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

EMA at 30: The Value of Consistency

Shamus McGillicuddy

Enterprise Management Associates (EMA) turns 30 this year. We're not the largest analyst firm, and we're not the loudest. What we have always strived to be is honest, independent, and reliable.

After three decades in this industry, we think those are the things that matter most.

The Challenge for Today's Buyers and Sellers

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment.

Technology markets are more competitive, fast-moving, and crowded than ever. Vendors face constant pressure to differentiate, explain increasingly complex products, and respond to rapidly changing buyer expectations. The result is a cornucopia of reports, white papers, webinars, demos, and perspectives … often well-intentioned, but difficult to evaluate in aggregate.

Today's buyers are moving beyond "quadrants" and asking harder questions like whether a product works in their environment, what the implementation really looks like, and what the trade-offs and "gotchas" are.

They require context, experience, and insight across multiple deployments, architectures, and organizational realities.

The challenge is clarity.

The Role of the Analyst Has Changed

Thirty years ago, analysts were translators. Documentation was sparse, and vendors weren't always great at explaining what their products actually did, so analysts helped buyers understand the options.

Today, many vendors have robust websites with videos, blogs, podcasts, white papers, and an AI chatbot ready to answer your questions.

The hard part is cutting through the marketing to understand what's real. Does a product actually do what the demo suggests? Is a new product category genuinely new, or is it a repackaging of a legacy technology?

Things have only gotten harder with AI. Every vendor is an AI company now. Cutting through that noise requires experience, skepticism, and a willingness to ask uncomfortable questions.

The analyst role has shifted from "explainer" to "the person who's seen this movie before."

What We've Tried to Be

EMA has never tried to compete with the largest firms on scale. We don't have scores of analysts, and we don't cover every category.

What sets us apart:

  • Independence: Our research is driven by what practitioners need to know, sometimes at the expense of a sale. That may not be a model that makes you the biggest, but it lets us say what we think.
  • Technical depth over breadth: We'd rather be the definitive source on five topics than a surface-level source on fifty. If we cover something, we cover it well.
  • Human judgment: In an age of AI-generated content, there's still value in a person who has the experience, will look you in the eye (or video camera), and tell you what they believe.
  • Consistency: Thirty years of showing up, building relationships, and earning trust through accuracy.

Why This Matters More Now

Even the most mature technology markets are experiencing disruption today, thanks to AI, cloud transformation, rising security threats, compliance requirements, and more. As new vendors emerge and try to define new categories, well-established vendors are trying to figure out their place in this volatile environment. Amidst this disruption, failure and disappointment are inevitable.

That's exactly when you need someone who's been observing the market long enough to recognize the patterns, who remembers what happened the last time vendors promised to solve all your problems, and who can ask the right questions.

Experience and independence are requirements for honest guidance in that environment.

Thirty Years

Thirty years is a long time. Long enough to see technologies come and go, vendors rise and fall, and categories reinvent themselves. Long enough to recognize when the fundamentals don't live up to the hype.

We're still here because we've earned trust by being consistent, independent, and honest. That's the only goal for the next thirty.

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...