Why AIOps Failed and Event Intelligence Solutions Are Different
AIOps was supposed to be the revolution we’d all been waiting for. The idea was powerful: combine the might of big data and sophisticated machine learning to automate those tedious and complex IT operations processes, finally. Gartner introduced the term in 2017, but it was soon co-opted by vendors eager to label everything from anomaly detection to log analytics as AIOps. The result? Confusion. Buyers had no clue what AIOps was, and vendors couldn’t agree on what it did.
I’ve spent years nudging analysts to move on from the AIOps moniker. Now, Gartner has finally introduced Event Intelligence Solutions (EIS) with the latest Market Guide. This rebrand isn’t just cosmetic. It’s a much-needed correction that brings clarity, focus, and realism to a space that’s long been clouded by hype.
What Went Wrong With AIOps: The Hype vs. Reality Problem
The issue with AIOps wasn’t semantics; it was substance. “AIOps” products applied basic statistical methods, not actual AI. Vendors promised automation and labor savings, but what IT organizations got were lengthy implementations, low-quality data, and minimal payback. Most deployments never went much beyond simple event correlation and noise filtering.
Ironically, the most significant outcomes of AIOps had nothing to do with the technology itself; they were process improvements that resulted from attempting to implement it in the first place.
Why Event Intelligence Is Different
EIS is narrower in its sights. It utilizes AI and analytics to enhance event management, reducing response time, automating manual triage, and accelerating automation. That context gives teams something concrete to think about, build upon, and measure.
EIS value pillars are clearly established:
- Augmentation: Reducing manual labor through detection and correlation
- Acceleration: Speeding up triage with contextual, actionable insights
- Automation: Continuously processing more responses with no human intervention
The Three Pillars of Event Intelligence: Augmentation, Acceleration, and Automation
As GenAI swamps the market, sellers are rapidly incorporating LLMs for summaries, insights, and even chat-based collaboration. On the other hand, observability, ITSM, and infra monitoring vendors are all transitioning to the same EIS turf.
But it doesn’t work without good data. AI can’t fix broken pipes or poor context. Success with EIS depends on high-quality event data, accurate dependency maps, and insight into service definitions, escalation routes, and historical incidents. And above all, organizations need the will and process maturity to act on what the platform enables them to do.
Moving Beyond AIOps: Why IT Leaders Must Focus on Process Maturity
Event Intelligence is the proper progression. It steers the conversation away from mythical AI hype and towards tangible, actionable outcomes. But IT leaders must step up and do the work: align stakeholders, pre-clean data, mature processes, and steer clear of the temptation to chase hype.
Tech is easy. People and processes are the real challenge.
