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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.

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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

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.

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The Latest

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

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OpenTelemetry (OTel) arrived with a grand promise: a unified, vendor-neutral standard for observability data (traces, metrics, logs) that would free engineers from vendor lock-in and provide deeper insights into complex systems ... No powerful technology comes without its challenges, and OpenTelemetry is no exception. The engineers we spoke with were frank about the friction points they've encountered ...

Enterprises are turning to AI-powered software platforms to make IT management more intelligent and ensure their systems and technology meet business needs for efficiency, lowers costs and innovation, according to new research from Information Services Group ...

The power of Kubernetes lies in its ability to orchestrate containerized applications with unparalleled efficiency. Yet, this power comes at a cost: the dynamic, distributed, and ephemeral nature of its architecture creates a monitoring challenge akin to tracking a constantly shifting, interconnected network of fleeting entities ... Due to the dynamic and complex nature of Kubernetes, monitoring poses a substantial challenge for DevOps and platform engineers. Here are the primary obstacles ...

The perception of IT has undergone a remarkable transformation in recent years. What was once viewed primarily as a cost center has transformed into a pivotal force driving business innovation and market leadership ... As someone who has witnessed and helped drive this evolution, it's become clear to me that the most successful organizations share a common thread: they've mastered the art of leveraging IT advancements to achieve measurable business outcomes ...

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 ...

Image
Pagerduty

 

Real privacy protection thanks to technology and processes is often portrayed as too hard and too costly to implement. So the most common strategy is to do as little as possible just to conform to formal requirements of current and incoming regulations. This is a missed opportunity ...

The expanding use of AI is driving enterprise interest in data operations (DataOps) to orchestrate data integration and processing and improve data quality and validity, according to a new report from Information Services Group (ISG) ...