A structural shift: reliability as the gating factor<\/b><\/p>\n
\nThe research found that approximately ~50% of projects are in Proof-of-Concept (POC) or pilot stage. Adoption is still early but growing rapidly with 26% of organizations having 11 or more projects. As organizations move beyond experimentation and into scaled deployment, they are increasingly seeking platforms that are reliable, trustworthy, and proven.<\/p>\n
\nThis shift is reflected in both ambition and execution, with 74% expecting budgets to rise again next year. These findings point to a structural inflection point where reliability, resilience, governance, and real-time insight define enterprise readiness for agentic AI.<\/p>\n
\nKey findings from the report:<\/p>\n
- \n
- \nAlmost half (48%) of the senior global leaders surveyed anticipate budget increases of at least $2M, suggesting investments are still prudent.<\/p>\n<\/li>\n
- \nAI agents are most commonly deployed within IT operations and DevOps (72%), followed by software engineering (56%) and customer support (51%).<\/p>\n<\/li>\n
- \nOf those surveyed, business leaders say improving decision-making with real-time insights is top priority (51%) when deploying agentic AI, followed closely by improving system performance and reliability (50%) and improving internal efficiency to reduce operational costs (50%).<\/p>\n<\/li>\n
- \nThe greatest ROI expected for agentic AI projects is in ITOps\/system monitoring (44%), cybersecurity (27%) and data processing & reporting (25%).<\/p>\n<\/li>\n
- \nThe top two main barriers to agentic AI production at this time are security, privacy or compliance concerns (52%) and technical challenges to managing and monitoring agents at scale (51%), followed by shortage of skilled staff or training (44%).<\/p>\n<\/li>\n<\/ul>\n
Trust and human oversight<\/b><\/p>\n
\nOrganizations signal that human guidance remains a purposeful part of agentic AI strategy, even as they build toward greater autonomy. The report shows leaders expect a 50\/50 human\u2013AI collaboration for IT and routine customer-support applications and a 60\/40 human\u2013AI collaboration for business applications, signaling that human judgment guides the system by setting goals, defining boundaries, and ensuring accountability.<\/p>\n
\nAdditional findings include:<\/p>\n
- \n
- \nWhile over half (64%) of organizations deploy a mix of autonomous and human-supervised agents, 69% of agentic AI\u2013powered decisions are still verified by humans, and 87% of organizations are actively building or deploying agents that require human supervision.<\/p>\n<\/li>\n
- \nOnly 13% of organizations use fully autonomous agents, and just 23% rely exclusively on human\u2011supervised agents.<\/p>\n<\/li>\n
- \nThe top validation methods include data quality checks (50%), human review of agent outputs (47%), and monitoring for drift or anomalies (41%).<\/p>\n<\/li>\n
- \n44% still use manual methods to review communication flows among AI agents, highlighting the need for more automated, governed oversight mechanisms. Autonomy.<\/p>\n<\/li>\n<\/ul>\n
\n\u201cOrganizations are not slowing adoption because they question the value of AI, but because scaling autonomous systems safely requires confidence that those systems will behave reliably and as intended in real-world conditions,\u201d said Alois Reitbauer, Chief Technology Strategist at Dynatrace. \u201cWith most enterprises now spending millions of dollars annually and planning further budget increases, agentic AI is becoming a core part of digital operations. At the same time, the data shows a clear shift underway. While human oversight remains essential today, organizations are increasingly preparing for more autonomous, AI-driven decision-making. The focus is now on building the trust and operational reliability needed to scale agentic AI responsibly.\u201d<\/p>\n
Observability enables trust and scale for Agentic AI<\/b><\/p>\n
\nAs organizations scale agentic AI beyond pilot projects, observability is the crucial intelligence layer that helps to build trust by providing visibility across every stage of the agentic AI lifecycle, from development and implementation through to operationalization. The report found that observability is already used across the entire lifecycle, with the highest adoption during implementation (69%), followed by operationalization (57%) and development (54%), underscoring its role as a foundational capability as agentic AI moves into production.<\/p>\n
\nAdditionally, the report found:<\/p>\n
- \n
- \nNearly 70% of organizations surveyed already use observability during agentic AI implementation to gain real-time visibility into agent behavior, system performance, and decision-making in production environments.<\/p>\n<\/li>\n
- \n50% use agentic AI for both internal and external use cases, 33% for internal purposes only, and 18% for external purposes only.<\/p>\n<\/li>\n
- \n50% have agentic AI projects in production for limited use cases, 44% have projects in broad adoption across select departments, and 23% have projects in mature, enterprise-wide integration.<\/p>\n<\/li>\n<\/ul>\n
\n\u201cObservability is a vital component of a successful agentic AI strategy,\u201d continued Reitbauer. \u201cThe Dynatrace AI Center of Excellence (AI CoE) works with many of our largest customers, and as organizations push toward greater autonomy, they need real-time visibility into how AI agents behave, interact, and make decisions. Observability not only helps teams understand performance and outcomes, but it provides the transparency and confidence required to scale agentic AI responsibly and with appropriate oversight.\u201d<\/p>\n
\nDownload the full report here:<\/b>The Pulse of Agentic AI 2026<\/i>:<\/b><\/a> Balancing innovation with control from pilot to production.<\/p>\n
Methodology<\/b><\/p>\n
\nThis report is based on a global survey of 919 senior leaders and decision makers directly involved in or responsible for agentic AI development and implementation in large enterprises with annual revenues of $100 million or more. It was conducted and analyzed by Qualtrics partner Y2 Analytics on behalf of Dynatrace during November and December 2025. The sample included 206 respondents in the US, 85 in Latin America, 380 in Europe, 81 in the Middle East, and 196 in Asia Pacific.<\/p>\n
Additional Resources<\/b><\/p>\n
- \n
- Autonomous operations hit inflection point: New agentic AI report reveals what’s fueling scale (and blocking it)<\/a><\/li>\n<\/ul>\n
About Dynatrace<\/b><\/p>\n
\nDynatrace is advancing observability for today\u2019s digital businesses, helping to transform the complexity of modern digital ecosystems into powerful business assets. By leveraging AI-powered insights, Dynatrace enables organizations to analyze, automate, and innovate faster to drive their business forward. To learn more about how Dynatrace can help your business, visit www.dynatrace.com<\/a>, visit our blog<\/a> and follow us on LinkedIn<\/a> and X @dynatrace<\/a>.<\/p>\n
\nCurious to see how you can simplify your cloud and maximize the impact of your digital teams? Let us show you. Sign up for a 15-day Dynatrace trial<\/a>.<\/p>\n
Dynatrace and the Dynatrace logo are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners. \u00a9 2025 Dynatrace LLC.<\/i><\/p>\n
Cautionary Language Concerning Forward-Looking Statements<\/b><\/p>\n
\nThis press release includes certain \u201cforward-looking statements\u201d within the meaning of the Private Securities Litigation Reform Act of 1995, including statements regarding Dynatrace\u2019s capabilities and platform and the expected current and future benefits to organizations from using the Dynatrace platform. These forward-looking statements include all statements that are not historical facts and statements identified by words such as \u201cwill,\u201d \u201cexpects,\u201d \u201canticipates,\u201d \u201cintends,\u201d \u201cplans,\u201d \u201cbelieves,\u201d \u201cseeks,\u201d \u201cestimates,\u201d and words of similar meaning. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies, and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies, and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations, or strategies will be attained or achieved. Actual results may differ materially from those described in the forward-looking statements and will be affected by a variety of risks and factors that are beyond our control, including the risks set forth under the caption \u201cRisk Factors\u201d in our Annual Report on Form 10-K, subsequent Quarterly Reports on Form 10-Q, and our other SEC filings. We assume no obligation to update any forward-looking statements contained in this document because of new information, future events, or otherwise.<\/p>\n
<\/p>\n
View source version on businesswire.com: <\/span>https:\/\/www.businesswire.com\/news\/home\/20260122228846\/en\/<\/a><\/span><\/p>\n
\nMedia Relations:
\n
Dynatrace PR Team
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pr-team@dynatrace.com<\/a><\/p>\nKEYWORDS:<\/b> Massachusetts United States North America<\/p>\n
INDUSTRY KEYWORDS:<\/b> Data Management Security Technology Other Technology Software Artificial Intelligence<\/p>\n
- Autonomous operations hit inflection point: New agentic AI report reveals what’s fueling scale (and blocking it)<\/a><\/li>\n<\/ul>\n
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