More Than Half of Companies Have Deployed AI Agents

Learn more about PagerDuty

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.

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.

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More Than Half of Companies Have Deployed AI Agents

Learn more about PagerDuty

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.

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.

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As AI Scales Across Enterprises, Breaking Points Emerge

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Preparing Network Infrastructure for AI Starts with the Basics

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

The Network Data Problem Slowing Down Enterprise AIOps

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

The Governance Gap Behind AI's Infrastructure Problem

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

MEAN TIME TO INSIGHT Podcast - Episode 27: Observability Unification

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

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This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

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