AIOps solutions need both traditional AI and generative AI

The ability of traditional AI to not only make predictions of existing patterns and relationships but uncover new ones, in near real-time, is what makes the technology invaluable to a true AIOps solution. A model that can analyze new data and infer the presence of an attack or predict a problem that will interfere with availability or degrade performance is necessary. Traditional AI is particularly adept at both; imbuing the observe capability with the ability to detect anomalies and providing the discovery of patterns and relationships for the analyze capability.

Generative AI can generate code, configurations, and content. It replicates existing patterns and applies them to generate new content. It does not create anything, but instead relies on relationships between objects that are either strengthened or weakened based on feedback.

Indeed, asking generative AI to analyze new data is fraught with risk. It may give you a correct answer, but it also might hallucinate and give you the wrong answer. That's because ultimately generative AI is a numbers game, and if the relationships or patterns aren't strong or don't exist enough between data points, it will simply fill in the blanks-right or wrong.

What generative AI offers us is accessibility to the data-because we do not need to be experts in a query language or rely on developers to build us an interface-and the ability to automatically generate code or configurations that can be executed to resolve a problem. That, too, is accessibility, as it alleviates the need to be an expert in writing code or leveraging multiple APIs.

But without traditional AI to analyze telemetry data in real-time, such a system is only partially addressing two of the three capabilities needed for a fully functional AIOps solution. Thus, we need to use both traditional and generative AI:

• Observe: traditional AI for anomaly detection.
• Analyze: traditional AI to uncover patterns and relationships.
• Engage: generative AI to enable users to visualize and interact with data and insights.
• Act: generative AI to turn insights into action.

So, while I'm bullish on generative AI and its ability to simplify and even accelerate operations, I'm also aware that to realize the full potential of the AI in AIOps, it will take both traditional and generative AI.