Skip to main content

More Than Half of Companies Have Deployed AI Agents

More than half (51%) of companies are already leveraging AI agents, according to the PagerDuty Agentic AI Survey.

Agentic AI adoption is poised to accelerate faster than generative AI (GenAI) while reshaping automation and decision-making across industries. Companies are no longer just experimenting. The survey data shows that 94% of companies believe they will adopt agentic AI more quickly than GenAI, with 55% strongly agreeing that they will integrate it across their organizations at an accelerated pace. As businesses look to automate complex workflows and drive efficiency, agentic AI is emerging as the next phase of AI-driven transformation, offering faster deployment and deeper operational impact.

Image
Pagerduty

Key findings include:

Confidence in GenAI

The majority of respondents (63%) have fully integrated GenAI into their company. 73% of organizations in the UK and 69% in Australia lead the charge with 64% in the US not far behind. However, traction in Japan shows to be noticeably slower as only 44% of companies have fully integrated GenAI.

AI Maturity and Adoption

71% of companies that have fully implemented GenAI are far more likely to have already deployed agentic AI, compared to just 19% of companies that have yet to fully implement GenAI.

Strong Return on Investment (ROI) Expectations

62% of companies expect more than 100% ROI from agentic AI, with an average expected return of 171% on their investment. GenAI has already delivered strong financial results, with an average ROI of 152%.

Automating Workflows at Scale

52%, more than half, of companies expect agentic AI to automate or accelerate between 26% and 50% of their workloads, unlocking significant operational efficiencies.

Future Impact of AI

44% of business leaders expect agentic AI to have a greater overall impact than GenAI, while 40% believe the latter will prove more transformative, demonstrating that companies are divided on whether agentic AI will cause an industry shift similar to GenAI.

Lessons from GenAI Implementation

44% of business leaders cite rushed AI adoption without proper planning as the biggest challenge, which is one of the mistakes leaders hope to avoid repeating from their GenAI deployment. Cost control (40%), improved employee training (37%), and stronger data infrastructure (37%) were also among the top priorities for AI strategy refinement.

AI Investment Is Scaling Up

75% of organizations are investing $1 million or more in AI initiatives, reflecting a commitment to long-term AI-driven transformation, showcasing ongoing interest in AI implementation leading to increasing budget allocations.

"Leaders need to provide tangible, quantifiable benefits from their AI deployments if they want to justify the investment," said Eric Johnson, CIO at PagerDuty. "PagerDuty's latest survey data illustrates how strongly organizations believe agentic AI will help unlock real value from AI and automation, as 62% of survey respondents anticipate triple-digit ROI. Companies that successfully integrate agentic AI into their operations can expect increased efficiency gains by automating complexity and accelerating decision-making."

Many organizations learned firsthand that insufficient training hindered GenAI adoption and are taking a different approach with agentic AI. Every company surveyed has various plans to implement agentic AI training, with 61% prioritizing organization-wide seminars or structured initiatives.

Additionally, 56% of organizations will offer an external course to their employees, while 52% plan to host official office hours and formal internal mentorship programs to ensure employees can effectively integrate and leverage AI agents in their workflows.

Methodology: The survey of 1,000 IT and business executives across the US, UK, Australia, and Japan was conducted by Wakefield Research.

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 ...

More Than Half of Companies Have Deployed AI Agents

More than half (51%) of companies are already leveraging AI agents, according to the PagerDuty Agentic AI Survey.

Agentic AI adoption is poised to accelerate faster than generative AI (GenAI) while reshaping automation and decision-making across industries. Companies are no longer just experimenting. The survey data shows that 94% of companies believe they will adopt agentic AI more quickly than GenAI, with 55% strongly agreeing that they will integrate it across their organizations at an accelerated pace. As businesses look to automate complex workflows and drive efficiency, agentic AI is emerging as the next phase of AI-driven transformation, offering faster deployment and deeper operational impact.

Image
Pagerduty

Key findings include:

Confidence in GenAI

The majority of respondents (63%) have fully integrated GenAI into their company. 73% of organizations in the UK and 69% in Australia lead the charge with 64% in the US not far behind. However, traction in Japan shows to be noticeably slower as only 44% of companies have fully integrated GenAI.

AI Maturity and Adoption

71% of companies that have fully implemented GenAI are far more likely to have already deployed agentic AI, compared to just 19% of companies that have yet to fully implement GenAI.

Strong Return on Investment (ROI) Expectations

62% of companies expect more than 100% ROI from agentic AI, with an average expected return of 171% on their investment. GenAI has already delivered strong financial results, with an average ROI of 152%.

Automating Workflows at Scale

52%, more than half, of companies expect agentic AI to automate or accelerate between 26% and 50% of their workloads, unlocking significant operational efficiencies.

Future Impact of AI

44% of business leaders expect agentic AI to have a greater overall impact than GenAI, while 40% believe the latter will prove more transformative, demonstrating that companies are divided on whether agentic AI will cause an industry shift similar to GenAI.

Lessons from GenAI Implementation

44% of business leaders cite rushed AI adoption without proper planning as the biggest challenge, which is one of the mistakes leaders hope to avoid repeating from their GenAI deployment. Cost control (40%), improved employee training (37%), and stronger data infrastructure (37%) were also among the top priorities for AI strategy refinement.

AI Investment Is Scaling Up

75% of organizations are investing $1 million or more in AI initiatives, reflecting a commitment to long-term AI-driven transformation, showcasing ongoing interest in AI implementation leading to increasing budget allocations.

"Leaders need to provide tangible, quantifiable benefits from their AI deployments if they want to justify the investment," said Eric Johnson, CIO at PagerDuty. "PagerDuty's latest survey data illustrates how strongly organizations believe agentic AI will help unlock real value from AI and automation, as 62% of survey respondents anticipate triple-digit ROI. Companies that successfully integrate agentic AI into their operations can expect increased efficiency gains by automating complexity and accelerating decision-making."

Many organizations learned firsthand that insufficient training hindered GenAI adoption and are taking a different approach with agentic AI. Every company surveyed has various plans to implement agentic AI training, with 61% prioritizing organization-wide seminars or structured initiatives.

Additionally, 56% of organizations will offer an external course to their employees, while 52% plan to host official office hours and formal internal mentorship programs to ensure employees can effectively integrate and leverage AI agents in their workflows.

Methodology: The survey of 1,000 IT and business executives across the US, UK, Australia, and Japan was conducted by Wakefield Research.

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 ...