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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

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...