Nov 22, 2023

Key metrics for evaluating AI in IT support

7 metrics for evaluating AI in IT support

Share this article

Artificial Intelligence is becoming an integral part of IT support, revolutionizing the way organizations offer assistance to their employees. Nowadays, most companies have adopted at least a simple form of AI in their effort to simplify and optimize their helpdesk operations and provide better and more efficient employee support. But how can you tell if your AI-powered IT support is hitting the mark?

In this blog article, we'll explore the essential metrics and Key Performance Indicators (KPIs) that can help you measure the success of AI in IT support and ensure that your digital colleagues are pulling their weight.

1. First Contact Resolution rate

The First Contact Resolution (FCR) rate is a critical metric that indicates how often AI successfully resolves issues on the initial interaction. A high FCR rate suggests that AI can swiftly and accurately tackle problems, reducing the need for escalations and follow-up support. Most human agent-based helpdesks aim for an average FCR of around 70% - so keep that in mind and compare it to your AI-powered FCR rate.

Pro Tip: To boost your FCR rate, ensure that your AI is equipped with a robust knowledge base and the ability to understand and address complex queries. For the latter, you need to ensure that the AI is trained on advanced LLMs and has NLP to understand the query context and intent. Even better, choose an AI platform that offers automated issue resolution, like Gaspar AI. This means that issues that are more than just info-requesting questions can still be resolved through the platform without human intervention.

For example, Gaspar, our advanced LLM-trained chatbot, is trained on high-quality data specific to the IT helpdesk sector, and thanks to our ChatGPT integration it can have interactive conversations with users in natural language. By integrating the platform with the most used apps, Gaspar AI can automatically reset passwords or automate approvals instead of just answering frequently asked questions. Finally, to ensure that you have a robust knowledge base which can lead to a better FCR rate, it gives you insights into information gaps in your knowledge repository .

2. Response and resolution time

Time is of the essence in IT support. AI can significantly impact response and resolution times by providing near-instant responses to inquiries and quick solutions to common issues. Tracking these times helps measure the efficiency of your AI IT support system.

Pro Tip: Monitor response and resolution times closely and aim to continually optimize them by asking your provider to fine-tune AI algorithms and workflows if needed.

With Gaspar AI, getting the right answers takes mere seconds. Even routine issues that take an unreasonably long time to get solved, such as password resets, get automatically resolved in 10 seconds .

3. Ticket volume and backlog

The number of tickets your IT support team receives, and the size of your backlog can provide insights into workload and the effectiveness of AI. A well-functioning AI system should help manage ticket volume by handling routine tasks and queries, reducing the burden on human support agents.

Pro Tip: Keep a close eye on how AI affects ticket volume and backlog, aiming for a decrease in the number of open tickets and a shorter backlog. On Gaspar AI’s Admin Portal, you get a daily overview of your ticket backlog as well as the number of tickets resolved via automation or automated information sharing.

4. Self-service utilization

AI can empower users to help themselves by providing intelligent self-service options, such as chatbots or knowledge bases. Monitoring self-service utilization helps assess how well AI is enabling users to find answers independently. To do this, you need to ensure that your AI provider gives data about employees’ utilization of the platform. For instance, with Gaspar AI you will receive insights about how many employees use our Generative AI chatbot, while on our Admin Portal you get data about the % of issues that are automatically resolved thanks to Gaspar, our AI chatbot.

Pro Tip: Ensure that your self-service tools are user-friendly and that AI provides accurate and relevant self-help suggestions. There’s a good reason why employees don’t use the traditional service desk : it usually involves having to deal with an unfriendly interface and complicated, highly technical systems, along with endlessly searching through an infinite number of articles in the internal repositories. Make sure that your AI-powered helpdesk is easy to use and intuitive. Gaspar AI for example integrates with and so that employees don’t have to switch platforms or learn a new system.

5. Employee Satisfaction

AI influences employee satisfaction. AI's ability to handle routine tasks and inquiries can reduce downtime and work-related stress and frustration, thus enhancing job satisfaction of both end users and support agents.

Pro Tip: Survey your support team and employees regularly to assess their job satisfaction and make necessary adjustments to AI workflows and processes.

6. Cost Efficiency

The cost per ticket is a crucial metric for evaluating the financial impact of AI in IT support. AI can help reduce the cost per ticket by streamlining processes and reducing the need for additional human resources.

Pro Tip: Regularly calculate the cost per ticket and set cost-saving goals. A decrease in this metric is a strong indicator of AI's cost efficiency. With Gaspar AI, our customers enjoy a helpdesk ticket cost of just $1, which is a dramatic decrease vs the $26.51 cost of a traditional helpdesk ticket.

7. Knowledge base content quality

For successful self-service, high-quality knowledge base content is essential. AI can help maintain and optimize knowledge base articles by ensuring accuracy, relevance, and completeness.

Pro Tip: Continuously assess and improve the quality of knowledge base content to enhance the effectiveness of AI-powered self-service. With Gaspar AI, it’s extremely easy to know when your articles need improvement. After automatically answering an employee’s question, the end user gives feedback on the answer in its simplest form: just like or dislike the answer. This way, you get aggregated data and feedback on whether certain articles need to be optimized, and you have a great place to start your journey towards a high-quality knowledge base.

Measuring the success of AI in IT support is vital for your ROI

Measuring the success of AI in IT support is vital for ensuring that your investment is paying off. By regularly monitoring the suggested metrics and KPIs, you can determine how effectively AI is delivering support, optimizing resources, and improving employee satisfaction. With AI-driven IT support, your company can transform the way it handles inquiries and issues, providing efficient, effective, and satisfying assistance to users while ensuring that your digital colleagues are making a positive impact on your IT operations.

Interested in learning more about the impact of AI in IT support? Contact us and we can discuss all your burning questions.