Splunk Reimagines Observability in the AI Era

AI agents are moving from experimentation into production. As that happens, enterprises face a new set of challenges: How do you know agents are producing reliable results? Are they staying within policy? What are they costing? And how do you understand their behavior at scale?

At its recent conference, Splunk outlined how it is reimagining its platform around these questions, bringing together observability, AI-powered security operations, and its growing integration with Cisco.

From Data to Agent Observability

Splunk has long built its business around helping organizations make sense of data. Now, that same capability is being applied to AI agents.

One challenge organizations face when deploying agents in production is ensuring that they remain reliable, compliant, and cost-effective. Splunk's new Observability Studio addresses this by focusing on understanding agent behavior and token usage.

The shift is important. As agents become more autonomous, monitoring traditional application performance is no longer enough. Organizations also need visibility into how agents operate, what they consume, and whether they are behaving as expected.

Turning Context Into Action

Observability provides the context. The next step is turning that context into action.

Splunk is extending AI agents into security operations, where security analysts can use agents to support detection, investigation, response, and governance.

This points to a broader evolution in enterprise AI. Agents aren't simply generating information or assisting employees. They are increasingly being connected to operational workflows where their actions can have direct business and security consequences.

That makes visibility and control increasingly important.

The Cisco Connection

Splunk's relationship with Cisco is another major part of the company's evolution.

Cisco acquired Splunk more than two years ago, and the integration has continued while Splunk remains available to its traditional customer base. Cisco customers can now discover Splunk capabilities through products including Cisco Command Center and AI Canvas.

The combination also gives Splunk access to Cisco's broad customer distribution, creating an opportunity to bring Splunk's data and observability capabilities to a wider enterprise audience.

The Bigger Story: Data at Machine Scale

The next phase of AI will generate enormous volumes of operational data about how agents behave, what they consume, and what they accomplish.

That creates an interesting opportunity for Splunk.

Its traditional strength has been making sense of data. In the agentic era, that increasingly means understanding data generated at machine scale and using it to improve the reliability, security, governance, and economics of AI systems.

The question now is less about whether enterprises will deploy AI agents and more about how they will manage them once they are operating at scale.

Splunk is betting that observability will be a critical part of that equation.