A new global study suggests that enterprises are entering a decisive phase in the evolution of agentic AI, with reliability and governance now defining whether adoption can move beyond experimentation. Dynatrace has released The Pulse of Agentic AI 2026, highlighting how observability is becoming essential as organizations seek to operationalize autonomous systems responsibly across the MarTech and enterprise technology landscape.
The report is based on a survey of 919 senior global leaders responsible for implementing agentic AI initiatives. It finds that enterprises are not hesitating because they question the value of AI. Instead, many are struggling to govern, validate, and safely scale systems that act autonomously in live production environments. This challenge places Agentic AI at a clear inflection point, where ambition is high but execution depends on trust and operational readiness.
According to the study, roughly half of agentic AI projects remain in proof of concept or pilot stages, while adoption is accelerating among more advanced organizations. More than a quarter of respondents reported running eleven or more projects, signaling momentum toward broader deployment. Budget expectations reinforce this trend, with nearly three quarters anticipating increased investment next year and almost half expecting budget increases of at least two million dollars.
As enterprises attempt to move from pilots to scaled use, reliability is emerging as the key gating factor. Leaders cited real time decision making, system performance, and internal efficiency as top priorities for deploying agentic AI. The strongest expected returns are concentrated in IT operations and system monitoring, followed by cybersecurity and data processing and reporting. However, security, privacy, and compliance concerns remain the most significant barriers, closely followed by technical challenges related to monitoring agents at scale and a shortage of skilled talent.
The report also highlights the continued importance of human oversight. Most organizations expect a balanced collaboration between humans and AI for IT and customer support use cases, with an even greater human role in business applications. While a majority deploy a mix of autonomous and supervised agents, nearly seventy percent of AI driven decisions are still verified by humans. Fully autonomous deployments remain rare, underscoring how trust is still being built.
“Organizations 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,” said Alois Reitbauer. “With 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.”
Observability plays a central role in this transition. The study found that it is already widely used across development, implementation, and operationalization stages, providing visibility into agent behavior and system performance. As enterprises approach this Agentic AI inflection point, the ability to observe, validate, and govern autonomous systems is emerging as a foundational requirement for long term success.
Recommended Marketing News:
- Questex’s StreamTV Europe Builds Momentum as Streaming Industry Converges in Lisbon
- Pinch AI Raises $5 Million to Combat Rising Retail Return Fraud
- AnyMind Group Expands Japan Social Commerce With Bcode Acquisition
For media inquiries, you can write to our MarTech Newsroom at info@intentamplify.com
