Data teams have more telemetry data available than ever before, but incident investigation has not gotten meaningfully faster. The natural assumption is that AI is the fix, so many organizations have added an AI layer and called it AI site reliability engineering (AI SRE).
However, this rush to meet organizational and customer reliability demands means most AI for observability is bolted onto architectures that are not designed to support it. Teams may get fast output but later discover that important information is missing because the tools don’t integrate deeply into the data platform. That’s not efficient or effective.
This blog post explains the characteristics that separate AI SRE tools that actually improve investigation speed and accuracy from those that simply summarize telemetry data.
To understand what effectiveness looks like, let’s start with what the current investigation baseline actually costs.
Incident investigations impact engineering productivity
