How’s that AI copilot working out for you?

Everyone is selling “AI assistance” right now. Copilots for code. Copilots for detections. Copilots for parsing. The market is flooded with “assistance.” 

Here is what came up in recent conversations with top-tier industry analysts and enterprise buyers. They are not asking for faster manual work. They are asking for the manual work to disappear, while they still have visibility over it.

That is the gap. Helping someone write better regex is not the same thing as owning the pipeline.

The industry is shifting from assistance to autonomy. From AI-theater to an Autonomous Security Data Layer. Not because of “AI” but because easing operator burden can make a huge difference with your SIEM bill and efficiency, not to mention your team’s workload. Below are three learnings from the front lines of the telemetry market.

1. Cost is a byproduct. Noise is the lack of data governance.

Everyone starts with the SIEM bill. Everyone, because it’s easy to measure and easy to panic about. But cost is just a symptom, not the root problem. Poor data quality is.

The failure is that upstream data collection allows raw, noisy, unclassified data flow straight into storage and your SIEM. Garbage in, garbage out. You pay more, and you get less. It’s not just your analysts who suffer with alerts based on noisy or incomplete data. It also affects engineer workload significantly, who will then need to clean up data in your SIEM. Don’t get me wrong, SIEMs are great tools for detection, but very expensive ones for data cleaning.

The analysts and buyers we spoke with keep landing on the same point: “cost savings” plays upstairs. Engineers want control. 

Normalize and classify upstream. Route intentionally: only security-relevant data should get into the SIEM. Then the bill drops on its own because you stop paying for storing noise.

If your cost strategy is “ingest less,” you are cutting blindfolded, and probably weakening your threat detection. If your strategy is “ingest better,” the budget follows the engineering.

2. Copilots Optimize Toil. They Don’t Remove It.

There is a big difference between AI-suggested pipelines and automation. Most “AI pipeline” products are still DIY with autocomplete.

“If you still approve, version, or debug the regex, you still own the pipeline.”

AI-generated parsers still need supervision:

• You validate.
• You deploy.
• You maintain.

Then schema drift hits, because a vendor updates a field. Your parser silently degrades. Your detections rot. This is the part nobody puts on the demo slide. The work never ends. It just moves from “write parser” to “babysit parser.”

And it is unnecessary. A lot of security telemetry comes from the same off-the-shelf sources. Firewalls. WEC. EDR. IDPs. SaaS audit logs. Why should every team on Earth rebuild the same parsers, over and over?

The market signal we heard is direct. Teams want autonomous processing for standard tasks. Normalization. Routing. Classification. Without a human approving each step. That is not “AI help.” That is relieving the operator from pipeline maintenance.

3. Security and observability will share plumbing. They will not share a mission.

There is constant talk about the convergence of security and observability under a single pipeline vendor. One pipeline to rule them all. It sounds efficient. It usually becomes a compromise.

“Same tech stack. Different failure modes.”

Security has governance pressure. Chain of custody. Compliance. Detection integrity. Observability optimizes for app uptime and developer speed. Security optimizes for adversaries and audit trails.

When you force one pipeline to do both, you get a tool that fits neither team. Jack of all trades,  master of none. Security teams want dedicated tooling that understands their pain, one that speaks security. 

The bottom line

The era of manual regex maintenance is ending. Teams want to shift left: fix data upstream, before the SIEM. Stop treating pipeline maintenance as normal work.

Ask yourself this: if you are still setting up and maintaining your pipelines for standard security product logs, do you have the right pipeline? Or the vendor gave you a second job?

Copilots help you type faster. An Autonomous Data Layer lets you work on something else.