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The Most AI-Ready Companies Outpace Peers in the Race to Value

According to the Cisco AI Readiness Index, a small but consistent group of companies surveyed — the "Pacesetters," about 13% of organizations for the last three years — outperform their peers across every measure of AI value in the global study of over 8,000 AI leaders across 30 markets and 26 industries.

The Pacesetters' sustained advantage indicates a new form of resilience: a disciplined, system-level approach that balances strategic drivers with the data and infrastructure needed to keep pace with AI's accelerating evolution. They're already architecting for the future with 98% designing their networks for the growth, scale and complexity of AI compared to 46% overall.

The combination of foresight and foundation is delivering real, tangible results at a time when two major forces are starting to reshape the landscape: AI agents, which raise the bar for scale, security, and governance; and AI Infrastructure Debt, the early warning signs of hidden bottlenecks that threaten to erode long-term value.

The Pacesetter Profile: Readiness as Competitive Advantage

Cisco's research outlines a consistent pattern among these leaders delivering real returns.

They make AI part of the business, not a side project

Nearly all Pacesetters (99%) have a defined AI roadmap (vs 58% overall) and 91% (vs 35%) have a change-management plan. Budgets match intent, with 79% making AI the top investment priority (vs 24%) and 96% with short- and long-term funding strategies (vs 43%).

They build infrastructure that's ready to grow

They architect for the always-on AI era. 71% of Pacesetters say their networks are fully flexible and can scale instantly for any AI project (vs 15% overall), and 77% are investing in new data-center capacity within the next 12 months (vs 43%).

They move pilots into production

62% have a mature, repeatable innovation process for generating and scaling AI use cases (vs 13% overall), and three-quarters (77%) have already finalized those use cases (vs 18%).

They measure what matters

95% track the impact of their AI investments — three times higher than others — and 71% are confident their use cases will generate new revenue streams, more than double the overall average.

They turn security into strength

87% are highly aware of AI-specific threats (vs 42% overall), 62% integrate AI into their security and identity systems (vs 29%), and 75% are fully equipped to control and secure AI agents (vs 31%). Trust is part of the Pacesetters' value equation.

Pacesetters achieve more widespread results than their peers because of this approach: 90% report gains in profitability, productivity, and innovation, compared with ~60% overall.

AI Agents: Ambition Outpacing Readiness

The Index shows 83% of organizations plan to deploy AI agents, and nearly 40% expect them to work alongside employees within a year. But for majority of these companies, AI agents are exposing weak foundations — systems that can barely handle reactive, task-based AI, let alone AI systems that act autonomously and learn continuously. More than half (54%) of respondents say their networks can't scale for complexity or data volume and just 15% describe their networks as flexible or adaptable.

Pacesetters are again the exception. Their disciplined, system-level approach has already helped lay the foundations they will need to scale.

AI Infrastructure Debt: The emerging drag on value

The report introduces a new concept — AI Infrastructure Debt — the modern evolution of technical and digital debt that once held back digital transformation.

It's the silent accumulation of compromises, deferred upgrades, and underfunded architecture that erodes the value of AI over time. Some early warning signs are already visible: 62% expect workloads to rise by over 30% within three years, 64% struggle to centralize data, only 26% have robust GPU capacity and fewer than one in three can detect or prevent AI-specific threats.

These early warning signs point to a gap between AI ambition and operational readiness. But when the systems that power AI aren't secure, the debt can increase risk. Pacesetters aren't immune, but their foresight, governance, and investment discipline help them to avoid problems compounding into more costly risks.

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The Most AI-Ready Companies Outpace Peers in the Race to Value

According to the Cisco AI Readiness Index, a small but consistent group of companies surveyed — the "Pacesetters," about 13% of organizations for the last three years — outperform their peers across every measure of AI value in the global study of over 8,000 AI leaders across 30 markets and 26 industries.

The Pacesetters' sustained advantage indicates a new form of resilience: a disciplined, system-level approach that balances strategic drivers with the data and infrastructure needed to keep pace with AI's accelerating evolution. They're already architecting for the future with 98% designing their networks for the growth, scale and complexity of AI compared to 46% overall.

The combination of foresight and foundation is delivering real, tangible results at a time when two major forces are starting to reshape the landscape: AI agents, which raise the bar for scale, security, and governance; and AI Infrastructure Debt, the early warning signs of hidden bottlenecks that threaten to erode long-term value.

The Pacesetter Profile: Readiness as Competitive Advantage

Cisco's research outlines a consistent pattern among these leaders delivering real returns.

They make AI part of the business, not a side project

Nearly all Pacesetters (99%) have a defined AI roadmap (vs 58% overall) and 91% (vs 35%) have a change-management plan. Budgets match intent, with 79% making AI the top investment priority (vs 24%) and 96% with short- and long-term funding strategies (vs 43%).

They build infrastructure that's ready to grow

They architect for the always-on AI era. 71% of Pacesetters say their networks are fully flexible and can scale instantly for any AI project (vs 15% overall), and 77% are investing in new data-center capacity within the next 12 months (vs 43%).

They move pilots into production

62% have a mature, repeatable innovation process for generating and scaling AI use cases (vs 13% overall), and three-quarters (77%) have already finalized those use cases (vs 18%).

They measure what matters

95% track the impact of their AI investments — three times higher than others — and 71% are confident their use cases will generate new revenue streams, more than double the overall average.

They turn security into strength

87% are highly aware of AI-specific threats (vs 42% overall), 62% integrate AI into their security and identity systems (vs 29%), and 75% are fully equipped to control and secure AI agents (vs 31%). Trust is part of the Pacesetters' value equation.

Pacesetters achieve more widespread results than their peers because of this approach: 90% report gains in profitability, productivity, and innovation, compared with ~60% overall.

AI Agents: Ambition Outpacing Readiness

The Index shows 83% of organizations plan to deploy AI agents, and nearly 40% expect them to work alongside employees within a year. But for majority of these companies, AI agents are exposing weak foundations — systems that can barely handle reactive, task-based AI, let alone AI systems that act autonomously and learn continuously. More than half (54%) of respondents say their networks can't scale for complexity or data volume and just 15% describe their networks as flexible or adaptable.

Pacesetters are again the exception. Their disciplined, system-level approach has already helped lay the foundations they will need to scale.

AI Infrastructure Debt: The emerging drag on value

The report introduces a new concept — AI Infrastructure Debt — the modern evolution of technical and digital debt that once held back digital transformation.

It's the silent accumulation of compromises, deferred upgrades, and underfunded architecture that erodes the value of AI over time. Some early warning signs are already visible: 62% expect workloads to rise by over 30% within three years, 64% struggle to centralize data, only 26% have robust GPU capacity and fewer than one in three can detect or prevent AI-specific threats.

These early warning signs point to a gap between AI ambition and operational readiness. But when the systems that power AI aren't secure, the debt can increase risk. Pacesetters aren't immune, but their foresight, governance, and investment discipline help them to avoid problems compounding into more costly risks.

Hot Topics

The Latest

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...