We are witnessing a major AI evolution that has the potential to take IT operations teams to new heights.
First, we had the establishment of machine learning, then the dizzying rise of generative AI. Each of these brought a major leap forward that changed how ITOps teams work. But with the emergence of agentic AI, we are set to usher in a new era of ITOps.
What is Agentic AI?
Agentic AI is a system of action that works and connects with other ‘Agents’ to help teams quickly summarize, collate, analyze and resolve. This ability to process information at scale and rapidly take action offers ITOps teams an opportunity to get ahead of unplanned work, eliminating the time and toil from problem resolution.
But this era of change comes with its own challenges.
Adoption will be no walk in the park, and there are several key considerations organizations must assess before they adopt Agentic AI.
Agentic AI’s potential
Agentic AI represents a transformative step forward in how ITOps teams process, understand and act on data.
One of the biggest challenges ITOps teams face is ensuring the right information and context are available to them at the right time. Manually gathering, analyzing and summarizing data is time-consuming and humans are naturally more prone to errors than automated data management tools, which can lead to critical actions being delayed.
Agentic AI addresses the challenge of data management by rapidly analyzing vast amounts of data to detect an issue, analyze contributing factors and suggest potential remediation or actions to be taken. If the right guidelines or processes are in place, then these remediation steps can be automated, allowing the Agent to complete them itself.
These Agents can also be sent to “speak” with other Agents to get the right information and context that helps to make a decision or take action. This army of Agents will help to supercharge ITOps to deal with any type of incident:
- Well-understood incidents – Previously resolved issues where detailed runbooks and fixes were produced to help Agents address future occurrences.
- Partially understood incidents – Issues similar to ones that the team has previously seen, allowing them to develop potential remediations that Agents can be instructed to try.
- New, novel, and major incidents – Never-before-seen incidents that will require human input, with Agents helping to triage, diagnose and offer potential solutions.
The use of Agents to act as quickly as possible will help save teams countless hours and toil, greatly improving the experience for first responders and reducing burnout. Ultimately, Agentic AI will help organizations stay ahead of incidents and reduce the manual effort required to solve problems, allowing people to focus on higher-value tasks.
Process, Technology and People – Keeping humans in the loop
As with every AI development, there is concern around how Agentic AI could replace humans.
The reality is that people are still the most important piece of the ITOps puzzle. Human creativity will always be needed for troubleshooting, especially for novel situations Agents cannot cope with or resolve by themselves. It’s very difficult to foresee a world where humans aren’t involved in operations.
The challenge for organizations will be getting teams to appreciate what Agentic AI can do for them.
Agentic AI can help bring a significant competitive advantage. Once teams are shown how Agents can accelerate operations, then Agentic AI will become a more widely appreciated part of the ITOps toolkit. This can be done through an evidence-based approach, showing how Agents respond quickly to minor problems to prevent them from escalating into major outages. Teams can then get time back to focus on the things that matter most – innovating instead of firefighting.
Key considerations for Agentic AI
Agentic AI has huge potential, but also some pitfalls to manage. Once organizations reach the precipice of adoption, there are four key considerations to be made:
- Think about the problem you are trying to solve – Don’t force the square peg of Agentic AI into the round hole of a problem that it can’t solve. Carefully consider your problems and use cases, including how an Agent-to-human interface will help solve these problems.
- What will be automated vs. what will have human-in-the-loop – Every organization will have different risk tolerances. It is vital to understand those risk tolerances to clearly define what organizations are willing to let Agents do and allow to happen, compared to which actions need a human-in-the-loop to act as a backstop.
- Be cognizant of data security when using Agentic AI – Organizations must make decisions on what data sources Agentic AI can draw from for not only regulation compliance, but also to ensure the privacy of information being analyzed.
- Carefully audit and monitor – Keep close watch over how Agentic AI is being used and the data it is drawing on to ensure there is an ongoing process of human confirmation of the quality and accuracy of recommendations. Organizations must be mindful of areas where they cannot tolerate false positives or improper actions being output by their Agents. In critical moments, for example, organizations cannot afford false positives or bad decisions potentially leading to outages.
Why adopt Agentic AI?
Any organization that has an application needs development teams to deliver new capabilities and experiences at high speed. They want customers to get more from what is being built, but many developers are bogged down by manual tasks, dragged into incident response that Agents could take off their plate.
The number one thing Agentic AI will do for organizations is help incident response become better, faster and less cumbersome. It’s a force multiplier that will ultimately drive the best outcome and experience for customers and provide developers the time they need to continually improve the user experience.
