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ChatGPT is quickly becoming more than a fun novelty. It’s starting to play a role in real business use cases, taking on tasks such as writing emails, creating images for ads, and providing voice assistive technology.

Microsoft’s recent $10B investment in the company and plans to integrate ChatGPT into its Office Suite is just one example of how companies are staking their claim in generative AI.

Impressive as it may be, this technology is still in its infancy. It’s also trained on data from the open web, meaning any public site is fair game – accurate or not. Want to confirm the answer comes from a reliable source? You’ll have to find it yourself.

In a field like IT, where troubleshooting is a big part of the job, the enhanced search and discovery that comes with ChatGPT can save time and effort, especially for common, straightforward queries. But it’s not the most reliable tool for more complex incident responses or potential security concerns.

Don’t take my word for it. When asked how it performs on matters of incident response, here’s what ChatGPT had to say:

“Incident response is a complex task that requires a combination of technical and non-technical skills…it’s important to note that while ChatGPT can assist with the discovery process by providing relevant information, it’s not able to replace the expertise and judgment of human operators, who need to make sense of the information provided and make decisions about how to respond to the incident.”

As this response suggests, ChatGPT will unlikely start taking over human IT jobs anytime soon.

[ Also read Artificial intelligence: 3 trends to watch in 2023. ]

So with realistic expectations in mind, how will a resource like ChatGPT impact IT support in the near term? Let’s look at the strengths of ChatGPT and what it can do now.

1. Speed to resolution

ChatGPT can certainly help users get answers faster. People are probably using it more than they even know.

For example, ChatGPT is a good first line of defense for queries, helping to filter them based on importance and urgency. A low-priority IT issue may lend itself to a conversation with a Chatbot that can provide step-by-step solutions to simple problems such as “How do I reboot my computer?” or “How do I perform a software update?” Not only does this help resolve common issues, but it frees up IT teams for more challenging projects.

2. Limiting the cognitive burden

IT staffs are notoriously overworked. Add an industry talent shortage, larger economic factors, and mass tech layoffs, and it can be a stressful environment to work in.

Technology like ChatGPT can alleviate some burdens by helping IT teams organize. ChatGPT may not always provide the correct or contextually relevant answers, but it can leave breadcrumbs. ChatGPT-powered features can help uncover enterprise knowledge more easily than searching through troves of data and documents, or it can simply generate an answer that sparks the idea for a solution. ChatGPT can break down bigger problems into more digestible next steps.

3. Enhancing communication

From drafting emails to improving conversations between employees with varying language proficiencies, generative AI will significantly improve the art of conversation. The ability to overcome cultural nuances in the spirit of collaboration can lead to new ideas, creative solutions, and a better working environment.

Companies are more distributed than ever before, and tools like ChatGPT can go a long way in creating intelligible communication. Beyond clarifying language and cultural differences, its mission to create human-like responses can also help refine technical communications with non-technical staff members.

As it stands now, ChatGPT is not fail-proof. Its flaws are evident, and users should proceed with caution – especially those tasked with managing enterprise technology. But even with its shortcomings, ChatGPT is already significantly helping IT teams. As the technology advances, it will continue to provide value to burdened IT teams over the next year and beyond.

[ Want best practices for AI workloads? Get the eBook: Top considerations for building a production-ready AI/ML environment. ]

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