Applications of Generative AI in IT Operations (AIOps)

Over the past several years, the use of Generative AI in conversational AI platforms has become increasingly popular in various industries. From marketing and advertising to data analysis and customer service, Generative AI is running wild (in a really good way).

In this article, we will explore how Generative AI – and ChatGPT in particular – can be effectively used to improve operations efficiency. We’ll also explore how the AIOps platform can be used to prevent outages, predict and prescribe IT issues, and enable system admins to be on top of any infrastructure concerns.

As a primer for anyone who may be unfamiliar, According to the glossary of AI terms, Generative AI refers to the use of machine learning algorithms, including large language models or LLMOps (Large Language Model Operations), to create new and original data, such as text, images, and sounds. One popular application of Generative AI is ChatGPT, an artificial intelligence-based chatbot capable of generating natural-sounding human-like responses.

ChatGPT is based on the GPT architecture, which stands for Generative Pretrained Transformer and is a prime example of a large language model (LLM). It relies on deep learning techniques to understand natural language and generate relevant responses based on prompts and inputs. The platform has been trained on a vast amount of data, making it capable of generating responses that are both accurate and relevant.

Generative AI and ChatGPT can be used in various ways to improve IT operations efficiency. Below are some examples of how these technologies can be used.

(Please note that these are not all of the ways Generative AI can be used for IT operations teams. The great thing about this technology is that it advances fast and the possibilities are limitless.)

When comparing generative AI vs predictive AI, One of the more impactful benefits of predictive AI is its ability to identify patterns and predict outcomes. By analyzing historical data, machine learning algorithms can spot trends and accurately predict when a system failure is imminent. This capability can be especially useful for IT operations, where system downtime comes with expensive consequences.

In the IT industry, rough estimates calculate the cost of downtime at around $5,600 per minute. Depending on the size of the company and the daily revenue, that can lead to a cost of anywhere between $145,000 to $450,000 per hour. In some industries, the cost can be as high as $50,000 per minute – costing millions per hour!

With predictive maintenance, system admins can identify potential issues before they occur and take action to prevent them. This involves proactively replacing components, implementing software updates, or adjusting system configurations.

IT support teams can be overwhelmed by the number of tickets they receive, leading to delays in resolution and customer frustration. By using Generative AI & ChatGPT’s ability, support teams can automate the ticketing process and free up time for more complex issues.

Chatbots triage tickets, gather necessary information, and even resolve simple issues without human intervention. This can significantly reduce response times and also improve efficiency and customer satisfaction.

Generative AI and ChatGPT can be leveraged to identify and fix problems before they become dangerous and costly. It does so by analyzing system logs and user feedback using technologies that are capable of identifying potential issues and suggesting solutions in real-time.

For instance, if a user reports slow performance on a particular application, ChatGPT can analyze the logs and suggest optimizations to improve performance.

The user can then follow these steps to improve performance without needing to file support tasks or go through a long, drawn-out process that complicates things and creates operational bottlenecks.

An IT Operation chatbot can be used to provide personalized support to users, while also automating routine tasks. By analyzing user behavior and preferences, these chatbots provide tailored recommendations desk support, and assistance to identify user intentions.

For instance, if a user is struggling to complete a particular task, the chatbot can automatically provide step-by-step instructions or suggest alternative approaches. This not only improves user satisfaction but also reduces the workload on IT support and operations teams.

The AIOps solution by Aisera is an artificial intelligence-based platform that helps businesses automate IT operations, improve system uptime, and prevent outages. Because it’s powered by ChatGPT, it’s able to understand and process natural language and generate relevant responses.

Below are some ways the platform can improve IT operations efficiency:

AIOps can help businesses prevent outages by identifying potential issues before they occur. The platform uses machine learning algorithms to analyze data and identify patterns that can indicate the possibility of an outage. It’s then able to generate automated responses to fix the issue or alert IT staff to take corrective action.

This functionality is rooted in AIOps’ predictive maintenance capabilities (which is kind of like the secret sauce that keeps everything running). The platform analyzes historical data from various sources, including logs, tickets, and user behavior, to identify patterns and predict when systems are likely to fail.

System admins then use the predictive maintenance capabilities of AIOps to take proactive action before downtime or server outage occurs. If the platform predicts that a server maintenance particular component is likely to fail, system admins can proactively replace the component before it causes downtime.

In addition to predictive insights, the AIOps solution provides prescriptive insights. The platform analyzes data and looks for potential solutions to issues

Suppose that there’s an issue with a particular application. The platform can suggest specific optimizations to improve performance. It can also suggest specific actions for system admins to take to address potential security issues.

To provide predictive and prescriptive insights, Aisera’s AIOps solution uses a variety of machine learning algorithms, including deep learning, reinforcement learning, and natural language processing (NLP). These algorithms allow the platform to analyze data from various sources and provide accurate and relevant insights.

The platform also uses NLP to understand the intent behind user requests and provide accurate and relevant responses. This capability can be particularly useful for IT support teams, which can quickly see user intent, find solutions to common IT issues and reduce response times.

Automated ticketing is a process in which a chatbot or virtual assistant handles the initial triage and resolution of support tickets without human intervention. This approach reduces response times and improves customer satisfaction. AIOps uses ChatGPT-powered chatbots to automate common IT tasks, including the triage and resolution of support tickets.

Here’s how that works…

When a user submits a support ticket, the chatbot analyzes the ticket and asks follow-up questions to gather additional information. The chatbot then suggests solutions to the user or escalates the ticket to a human support agent (only if necessary).

This process gives users immediate assistance from the chatbot, rather than having to wait for a human support agent to become available. (Because, let’s be honest, nobody likes waiting on the phone for 45 minutes at a time.)

AIOps uses NLP to understand the user’s intent and provide accurate and relevant responses. The chatbot can handle a wide range of support requests, including password resets, software installations technical troubleshooting, and network configurations – even if it’s never seen a particular request before.

By automating these common IT tasks, the chatbot frees up time for IT support teams to focus on more complex issues.

In addition to triaging support tickets, the chatbot tool also can provide step-by-step instructions to users. This capability can be particularly useful for users who are not familiar with a particular IT system or application.

As mentioned, Aisera’s AIOps platform can essentially help system admins stay on top of any infrastructure concerns, reducing the workload on IT staff and improving system uptime.

It automates various IT operations tasks, such as monitoring, troubleshooting, and resolving incidents. This creates more margin in each staff member’s schedule, which ensures greater stability throughout the organization.

Aisera’s AIOps provides analytics and insights into IT operations by examining data from numerous sources, including tickets, logs, and user behavior.

Data Collection and Integration. The first step in providing analytics and insights into IT operations is collecting and integrating data from various sources.

In the AIOps use cases it can integrate with other IT systems, including IT service management (ITSM) platforms, security information, and event management (SIEM) tools and platforms, and network monitoring tools.

The platform is also capable of analyzing data from these sources and providing users with a comprehensive view of the IT infrastructure. By analyzing data from multiple sources, the platform gives more accurate and relevant insights into IT operations.

Real-time Monitoring and automation. The platform provides real-time monitoring and automation of IT operations, allowing system admins to stay on top of any infrastructure concerns. The platform can monitor system logs, network activity, and user behavior to identify potential issues before they become critical.

Aisera’s AIOps solution provides self-service capabilities that allow users to quickly find answers to their queries and resolve issues, including technical troubleshooting, without involving IT staff.

This capability is particularly useful for large organizations that receive a high volume of support requests, as it can significantly reduce the workload on IT support teams.

The platform uses NLP to understand the intent behind user queries and generate relevant responses. This means that users can ask questions in their own words, without needing to use technical jargon or specific IT terminology.

The self-service capabilities of Aisera’s AIOps solution include a knowledge base and virtual assistant. The knowledge base is a centralized repository of information that users can access to find answers to their queries.

It can include articles, FAQs, videos, and other types of content. Users can search the knowledge base using natural language queries, making it easy to find the information they need.

The virtual assistant is a more advanced version of the chatbot that can handle more complex support requests. It utilizes machine learning algorithms to understand the intent behind user queries and provide more personalized support.

AIOps can analyze historical data to identify trends in IT operations. It analyzes data from various sources, including logs, tickets, and user behavior, to identify patterns and trends.

For example, it’s able to analyze ticket data to identify common support requests. System admins can then use this information to proactively address potential issues, reducing response times and improving customer satisfaction.

AIOps also analyzes data to identify areas for optimization. For instance, if the platform identifies a particular application that is causing performance issues, system admins can take action to optimize the application and improve system performance.

Predictive and Prescriptive Insights. AIOps can provide predictive and prescriptive insights into potential IT issues. By analyzing data and identifying patterns, for example it predicts when systems are likely to fail and suggest specific actions for system admins to take.

If the platform predicts that a particular component is likely to fail, system admins can proactively replace the component before it causes downtime. It’s also able to suggest specific optimizations to improve system performance.

AIOps uses NLP to understand the intent behind user requests and provide accurate and relevant responses. It’s built with the ability to analyze user intent and behavior and then provide relevant responses and personalized support to users.

For example, if a user is struggling to complete a particular task, it can provide step-by-step detailed instructions, or suggest alternative approaches. This capability can improve user satisfaction and reduce response times for IT support teams.

Want to address service disruptions before the fact? At Aisera, we like to refer to our AIOps solution as being “purpose-built.” That’s because we’ve architected it with the end in mind.

When you integrate our cutting-edge platform into your IT operations, you’ll notice the difference. Book your free demo today!