“We’ve reached the point where every organization surveyed – 100% – uses some form of AI.”
— Dynatrace, State of Observability 2025
Yet only 33% have managed to scale AI initiatives across their organizations, and 69% still require human validation for AI-driven decisions.
Add to this the rapid rise of automation, increasingly autonomous AI agents, the spread of generative models, and the growing complexity of operations — and for most leaders, it all points to one thing: loss of control.
Because as systems learn and act on their own, only those who truly see what’s happening remain in control.
Key Trends from the 2025 Report
The State of Observability 2025 makes one thing clear: observability has become the critical control layer of the AI era. Many organizations have already recognized that transparency is no longer optional — it is an operational necessity.
According to the report, three out of four (75%) organizations increased their observability budgets in the past year, and over 70% plan further growth within the next 12 months.
The shift in priorities is striking:
for the first time in the report’s history, AI capabilities have overtaken cloud compatibility and data collection simplicity as the number-one criterion for selecting an observability platform.
The New Roles of Observability
The State of Observability 2025 identifies three key areas where observability is reshaping organizational control:
AI governance
Companies are delegating more decisions to AI, yet trust remains far from automatic — the report confirms a significant AI trust gap.
Today, 69% of respondents still require human oversight of AI decisions, underscoring how lack of transparency limits confidence in autonomous operations.
Observability provides the visibility needed to trace data sources, monitor AI decision paths, and ensure that every outcome is explainable, traceable, and verifiable.
Security and compliance
98% of security leaders now use AI in risk management, and an increasing number of enterprises are integrating security, compliance, and observability into a single unified data model.
This convergence enables real-time visibility across systems and supports faster, more responsible incident response.
Integrated operations
In complex, hybrid enterprise environments, observability has become the common language across teams. It integrates development, security, financial, and sustainability perspectives into a single “shared intelligence layer” that supports informed, real-time decisions.. Organizations that can operate this layer maintain control — even as AI systems grow more autonomous.
Executive Perspective: Observability as a Decision-Enablement System
Monitoring once focused on the IT “vitals” — CPU, memory, network, and error logs.
Observability has evolved further: it not only shows what happens, but also why.
Modern platforms connect technical data with business processes, revealing in real time how performance degradation, latency, or outages impact costs, revenue, and customer experience.
According to the State of Observability 2025, nearly one-third of organizations already correlate observability data directly with business KPIs. A slowdown in service performance now appears as a revenue risk, while an optimized process translates into measurable cost savings and operational efficiency.
Observability no longer serves the IT team alone — it has become a strategic cockpit for leadership, where technology, data, and business outcomes align in a single, real-time view.
Conclusion – There Is No Control Without Visibility
Today’s enterprises no longer simply operate systems; they manage self-learning, decision-making ecosystems.
In this environment, complete transparency is not a luxury — it is the foundation of accountability and control.
The State of Observability 2025 shows that observability has emerged as the new control layer for the AI era.
The enterprise IT landscape is rapidly evolving toward an AI-native model, where intelligence is not a feature but a fundamental design principle.
This shift requires reimagining operations around AI’s capabilities — and observability is the capability that makes this transformation possible.
With observability, organizations can connect data, processes, and decisions across systems, ensuring that AI remains transparent, auditable, and aligned with business intent.
Telvice Insight
At Telvice Zrt., our mission is to help organizations not only use AI but truly understand and govern it.
Through our observability solutions, data, processes, and decisions become part of one coherent system — enabling real-time visibility, measurable trust, and sustainable performance.
