How generative AI changes IT operations

Generative AI can provide valuable analysis and insights to IT operators. But what about data security, reliability, workflow integration, and the conditions needed for successful deployment?

butterfly transformation

IT leaders are thrilled about the potential of generative AI for IT operations. But they also want to know how it works, why it works, and what it will do for them before taking the leap and adopting this new technology.

As the Field CTO for BigPanda, Incident Intelligence and Automation powered by AIOps, I’ve been running experiments with large language models and generative AI technology that were so impressive that I pushed my company to deliver a generative AI solution to our customers as soon as possible.

Yes, there is hype around AI. And yes, there are reasons to be skeptical. Yet generative AI is already shaping the way we think about IT operations. So let me answer your questions, explain the basics of how this works, and share how generative AI can help IT ops teams stay ahead of the curve.

An intelligent assistant for IT ops and devops teams

Generative AI is an advanced form of AI that uses large language models to rapidly analyze vast amounts of data, process complex patterns, and generate insightful responses. And when good data is used, it’s rapid, accurate, and provides high-value analysis in natural language.

Within IT operations, generative AI can analyze incidents, identify patterns, summarize them, suggest root causes in real time, and provide valuable insights to operators. It can also act as a smart assistant for IT ops, SREs, and devops teams, greatly reducing stress and improving incident response. Our early adopters found it reduces up to 10 minutes for each incident. Generative AI can ultimately provide IT teams with another pair of eyes, like having a full-stack engineer instantly available for any question.

Your questions about generative AI, answered

I’ve been talking with many IT leaders who are thrilled about these potential benefits, but they question generative AI’s data security, reliability, workflow integration, and the conditions needed for successful deployment. Here are some of the answers to the questions I often hear about using generative AI in IT operations.

Is generative AI secure? 

Yes, but it can depend on the platform you are using. You’ll want to understand the security measures in place, especially when dealing with sensitive data. Be sure to ask how your generative AI platform and any third-party vendors handle data, ensure compliance, and maintain data security when adopting this technology.

Will generative AI replace IT ops teams?

Generative AI is not intended to replace human practitioners but rather to act as an assistant or tool that helps them do their jobs better. AI can fill the skills gap by translating complex technical issues into easy-to-understand terms, making it easier for all individuals to understand the implications and probable resolution paths. While generative AI can provide valuable insights to practitioners, it is nowhere close to being able to replace skilled IT professionals.

How reliable is generative AI? 

95% of the time BigPanda Generative AI accurately speculated on the root cause of an incident, outperforming human capabilities. This level of accuracy translates to quicker incident resolution and reduced downtime. However, you’ll need good data to ensure generative AI reliability.

Will generative AI work with our data?

Data quality is a crucial factor in the success of generative AI. But with data quality, it’s “garbage in, garbage out.” For instance, some AIOps platforms don’t use enriched or correlated data, are only able to apply generative AI to querying data, or just offer basic analysis without visibility into impact or probable root cause.

High-quality data is essential for training AI models and ensuring accurate results. But if your data isn’t quite where you want it, that can be fixed with an AIOps vendor who provides enrichment and correlation. That’s why companies need to focus on data enrichment and integrity to maximize the potential of generative AI in IT operations.

Does using generative AI require extra resources?

There’s a perception that implementing generative AI requires significant resources, infrastructure, and expertise. However, AI is an enabling technology that can be useful for organizations of all sizes, including smaller businesses. Generative AI can be simple to use, and companies can start by implementing AI in specific areas of IT operations and then gradually scaling up. This strategic approach leads to immediate wins for companies of all resource levels.

A new era for IT operations

Generative AI is disrupting the IT operations landscape, offering businesses an intelligent and proactive approach to incident management. By analyzing vast amounts of data, providing accurate insights, and acting as a smart assistant, generative AI empowers IT professionals, streamlines operations, and multiplies team productivity.

So if you’re ready to get started with generative AI, check that your generative AI vendor offers security and data best practices, analytics with visibility into impact and probable root cause, and has comprehensive capabilities for fast, accurate, and consistent incident analysis. As more businesses embrace the power of generative AI, we can expect more innovative use cases to emerge, transforming the IT industry further.

I believe that generative AI is just the first step. We are continuously fine-tuning this technology and working towards automatic remediation. Now, by harnessing the enormous potential of generative AI, IT leaders can unlock efficiency to take their IT operations to new heights.

Blair Sibille is the Field CTO at BigPanda.

Generative AI Insights provides a venue for technology leaders—including vendors and other third parties—to explore and discuss the challenges and opportunities of generative artificial intelligence. The selection is wide-ranging, from technology deep dives to case studies to expert opinion, but also subjective, based on our judgment of which topics and treatments will best serve InfoWorld’s technically sophisticated audience. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content. Contact


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