Research shows that companies are increasing investments while cautiously scaling up until reliability is proven in production.
THE Dynatrace, a leading platform for observability based on Artificial Intelligence (AI), announces the “The Pulse of Agentic AI 2026””, a groundbreaking global study focused on how observability and reliability determine the successful operationalization of agentic AI. The research, involving 919 senior leaders worldwide responsible for implementing agentic AI, reveals that companies are not hesitating because they doubt Artificial Intelligence, but because they are still unable to safely govern, validate, or scale autonomous systems.
A structural change: reliability as a determining factor.
The research found that approximately 50% of the projects are in the proof-of-concept (PoC) or pilot phase. Adoption is still in its early stages, but growing rapidly, with 26% of organizations having 11 or more projects. As organizations move beyond experimentation and into large-scale implementation, they increasingly seek platforms that are reliable, secure, and have proven effectiveness.
This shift is reflected in both ambition and execution, with 74% expecting budgets to increase again next year. These findings point to a structural inflection point where reliability, resilience, governance, and real-time insights define companies' readiness for agentic AI.
Key findings of the report:
– Almost half (48%) of the senior global leaders surveyed foresee budget increases of at least US$ 2 million, suggesting that investments are still prudent.
– AI agents are most commonly deployed in IT and DevOps operations (72%), followed by software engineering (56%) and customer support (51%).
– Among those interviewed, business leaders state that improving decision-making with real-time insights is the top priority (51%) when implementing agent AI, closely followed by improving system performance and reliability (50%) and improving internal efficiency to reduce operating costs (50%).
– The highest expected ROI for agency AI projects is in ITOps/systems monitoring (44%), cybersecurity (27%), and data processing and reporting (25%).
– The two main barriers to bringing agentic AI to production at this time are concerns about security, privacy or compliance (52%) and the technical challenges of managing and monitoring agents at scale (51%), followed by a shortage of qualified personnel or training (44%).
Trust and human supervision
Organizations are signaling that human guidance remains an important part of their agentic AI strategy, even as they move toward greater autonomy. The report shows that leaders expect 50/50 collaboration between humans and AI for IT applications and routine customer support, and 60/40 collaboration between humans and AI for business applications, signaling that human judgment guides the system in setting goals, establishing boundaries, and ensuring accountability.
Other findings include:
– Although more than half (64%) of organizations use a combination of autonomous and human-supervised agents, 69% of decisions based on agentic AI are still verified by humans, and 87% of organizations are actively developing or implementing agents that require human supervision.
– Only 13% of organizations use fully autonomous agents, and only 23% rely exclusively on agents supervised by humans.
The main validation methods include data quality checks (50%), human review of results (outputs) of the agents (47%) and monitoring of deviations or anomalies (41%).
– 44% still uses manual methods to review communication flows between AI agents, highlighting the need for more automated and governed oversight mechanisms. Autonomy.
“Organizations aren’t slowing adoption because they question the value of AI, but because the secure scalability of autonomous systems requires confidence that these systems will behave reliably and as expected under real-world conditions,” says Alois Reitbauer, Chief Technology Strategist at Dynatrace. “With most companies spending millions of dollars annually and planning further budget increases, agentive AI is becoming a central part of digital operations. At the same time, 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 now is on building the operational trust and reliability needed to responsibly scale agentive AI.”
Observability enables trust and scale for agentic AI.
As organizations scale agentic AI beyond pilot projects, observability is the crucial intelligence layer that helps build trust by providing visibility across all stages of the agentic AI lifecycle, from development and implementation to operationalization. The report found that observability is already used throughout the lifecycle, with the highest adoption during implementation (69%), followed by operationalization (57%) and development (54%), highlighting its role as a fundamental capability as agentic AI moves into production.
Furthermore, the report found that:
Nearly 70% of the organizations surveyed already use observability during the implementation of agentic AI to gain real-time visibility into agent behavior, system performance, and decision-making in production environments.
– 50% uses agentive AI for internal and external use cases, 33% for internal use only, and 18% for external use only.
– 50% have agency AI projects in production for limited use cases, 44% have projects in broad adoption in selected departments, and 23% have projects in mature integration across the enterprise.
“Observability is a vital component of a successful agentic AI strategy,” Reitbauer continues. “Dynatrace’s AI Center of Excellence (AI CoE) works with many of our largest clients, and as organizations seek 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 also provides the transparency and trust needed to scale agentic AI responsibly and with proper oversight.”
Download the full report at “The Pulse of Agentic AI 2026: Balancing innovation with control from pilot to production”.
Methodology
This report is based on a global survey of 919 senior leaders and decision-makers directly involved in or responsible for the development and implementation of agentic AI at large companies with annual revenue of US$$ 100 million or more. It was conducted and analyzed by Y2 Analytics, a Qualtrics partner, on behalf of Dynatrace, during November and December 2025. The sample included 206 respondents in the United States, 85 in Latin America, 380 in Europe, 81 in the Middle East, and 196 in Asia-Pacific.
Additional resources
About Dynatrace
Dynatrace is advancing observability for today's 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 businesses forward. To learn more about how Dynatrace can help businesses, visit [website address - not provided in the original text]. www.dynatrace.com, visit our blog and follow us on LinkedInno and in X @dynatrace. To learn how you can simplify the cloud and maximize the impact of digital teams, take a free 15-day trial.
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