In theory, generative AI can do lots of amazing things in the realm of IT operations, from writing code, to managing tickets, to helping troubleshoot incidents and beyond.
But in reality, few organizations seem to have embraced GenAI for all of these tasks. The typical IT team today is using GenAI in limited ways, if at all.
To prove the point, let's take a look at the current state of generative AI in ITOps, including which tools are leveraging GenAI, how much adoption they're seeing, and what IT pros say about their plans for implementing generative AI.
Generative AI and ITOps Tools: The Art of the Possible
It's easy to think up use cases for generative AI in IT operations. It's harder to build tools that actually deliver on those use cases — and to date, the extent to which software vendors that cater to IT operations have actually baked GenAI into their products is limited to a handful of narrow areas.
Managing tickets
One is ticket management. Here, generative AI offers a lot of value because it can interpret and summarize user-submitted tickets. Vendors such as ServiceNow and Rezolve offer tools that leverage GenAI for this purpose.
However, not every IT ticketing solution currently leverages GenAI, and even if you use one that does, you're probably going to have to interpret and manage some tickets by hand. GenAI can speed workflows in this context, but it can't replace humans.
Incident response
In a similar fashion, certain vendors of incident response tools, such as Jeli, offer GenAI-based features that summarize incidents. The goal here is to make it easier for stakeholders to understand what has happened, and what should happen next, when they're in the midst of troubleshooting an outage.
As with ticket management, generative AI can accelerate workflows for incident response, but you'll still need humans to handle tricky issues that GenAI can't understand — and to review incident summaries in case AI gets them wrong.
Script generation
For IT operations engineers with limited coding skills — or those who simply aren't familiar with a certain language or system — generative AI tools like Copilot and ChatGPT can come in handy as a means of generating scripts. For example, if you need to write a cron job or generate some PowerShell code for a maintenance task, the code produced by GenAI tools is likely to work pretty well.
The limitation here is that generative AI likely won't excel at producing complex scripts, and to date, no vendor appears focused on this use case. Most tools designed for AI-assisted coding cater primarily to the coding needs of software developers, not IT engineers whose main requirement is to write scripts rather than applications.
What GenAI Is Not Doing for IT Teams
While generative AI is currently bringing real value to the use cases described above, there are many other IT operations needs that GenAI doesn't address — despite in theory being capable of it.
Take system monitoring. In theory, you could use natural language to tell a GenAI-powered tool what your SLAs and SLOs are, then ask it to monitor logs and metrics and manage alerts based on your requirements. But this is a complex task, and because tools like ChatGPT can't directly connect to monitoring systems, there's not a good way to address this use case with current GenAI technology. Unless a monitoring and observability vendor were to build a tool for this specific need, it's unlikely that GenAI will be able to help IT teams on this front.
For another example, consider system design and architecture. The task of figuring out how to plan an IT environment — which tools and services to deploy and how to configure them — often falls to IT engineers. Generative AI tools could theoretically assist here by allowing engineers to explain what their priorities are — for example, which types of security and performance goals they must meet — then let a GenAI model make suggestions. But once again, no tools currently excel at this type of work.
ITOps Teams Can Benefit From GenAI, but Only to an Extent
Some IT operations teams are leveraging generative AI, but only for certain types of tasks, and it's hard to imagine GenAI addressing a broader set of use cases in ITOps anytime soon.
Vendors that cater to the IT operations market have currently only implemented GenAI to address low-hanging fruit, not to take advantage of the technology in more sophisticated ways.
It's worth noting, too, that the number of IT leaders who plan to implement GenAI-based technologies appears low. The 2023 ITPro Today IT Priorities Survey found that only 25% of respondents planned to deploy AI technology (see figure above). Like software vendors, IT pros seem to see only a limited amount of potential in GenAI.
About the author
Christopher Tozzi is a technology analyst with subject matter expertise in cloud computing, application development, open source software, virtualization, containers and more. He also lectures at a major university in the Albany, New York, area. His book, “For Fun and Profit: A History of the Free and Open Source Software Revolution,” was published by MIT Press.
