2026: The End of the Dashboard as We Know It?
Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Tucker Callaway, CEO, Mezmo
Sounds like an R.E.M. track, doesn't it?
Since its inception, observability has centered on the dashboard-a human-centric tool for making complex data consumable. While AI is amplifying both scale and complexity challenges, it also presents an opportunity to solve issues that have long plagued Observability. The LLM's ability to perform investigative, correlation, and pattern-matching tasks puts AI agents at the center of the next wave of Observability. The industry is on the cusp of a new, AI-driven landscape where observability becomes more context-aware, anticipatory, and integrated into operational workflows. We are at an inflection point where systems can detect issues that matter faster, connect signals more intelligently, and support teams with higher-confidence.
Here are my predictions for where the industry is headed by 2026.
Prediction 1: "Agentic RCA" Becomes the Default
There is a lot of "energy" around AI SRE right now-a mix of excitement, skepticism, and hype. But when we cut through the noise, one reality is emerging: Agentic Root Cause Analysis (RCA) is viable today. The core promise of observability has always been to detect and diagnose issues with speed and precision, and we've now proven that AI models are more than sufficient to deliver this outcome. Agentic RCA is the critical gate to a fully autonomous future; if you cannot confidently detect and diagnose anomalous behavior, all downstream potential, like auto-remediation, can never be realized. By 2026, the expectation will shift. The question will no longer be whether an agent can identify the root cause, but whether it's worth a human's time to validate it.
Prediction 2: Data Processing Shifts to Support Agent-First Analysis
To deliver on the promise of AI-driven observability, the data model has to evolve. The traditional store-then-analyze pattern is no longer sufficient when AI agents need fast, contextualized information to reason effectively. The next wave of observability will transform both what we retain and how we prepare it for analysis, enabling Active Analysis, which captures high-value signals close to the source while reducing noise, and Active Context, which structures and refines data for AI-ready insights. Together, these approaches create a pipeline optimized for faster, more accurate agent-driven reasoning at scale.
Prediction 3: The Dashboard's Role Shifts from Operations to Governance
This brings us to the dashboard. If agents are performing the analysis and we have supplied those agents with the right data to be successful in diagnosing root cause, the operation dependency on dashboards and UIs for investigations ends. The agentic analysis will not only speed up MTTR but the need to maintain the array of dashboards we support today will decrease toil as well. As a result, SREs will start to get back to what they truly love: designing and architecting resilient, high-performance systems.
So, will dashboards be dead by 2026? Likely not, but the purpose will change. By 2026, we will see a shift from the dashboard as an operational tool to a source of trust and confidence. Its primary function will become risk management, compliance, and audit. As we empower agents to act autonomously, the dashboard will become the verification layer that provides governance and peace of mind, not the workbench.
This is an incredibly exciting time. The toil of maintaining our complex systems is becoming an embedded capability, delivering monumental benefits for consumers and SREs. This will inspire a new generation of providers built for this intelligent, agent-driven future. The future is context-engineered and, for the first time, moving us beyond the dashboard to a more autonomous and powerful world.
...and I feel fine.
