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Artificial Intelligence

Updating IT support – 7 ways that generative AI will make a big difference


The potential for generative AI tools like ChatGPT to support people in their daily work is widespread – and IT support is no exception. In this post, we’ll look at the seven ways generative AI can revolutionize daily tasks and enhance productivity in IT support as the technology continues to develop.  

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7 ways that Gen AI will make a big difference

1. Automating license management for new and departing employees

Generative AI will likely be instrumental in efficiently managing software licenses for both new and departing employees. An AI system can automatically acquire essential licenses for a new employee, and also disable the licenses no longer required for an employee leaving the company. By integrating generative AI with Robot Framework, the solution would be able to go through different SaaS service providers and make the necessary changes to licenses per individual. The system could also maintain a registry from where it’s possible to get an employee-specific list of the licenses in use.

2. Chatbots for automating responses to IT-related queries

A chatbot trained on the content found in the company's intranet could play a role in handling IT-related questions. With such a system, whenever an employee posts a question on the IT support slack channel, the chatbot would promptly respond if the matter related to information available in the intranet.

IT support personnel frequently deal with recurring queries from employees, such as password reset requests or connectivity issues. Generative AI could generate automated responses to these common inquiries, significantly reducing response time. These automated response mechanisms will allow IT support to focus on more complex issues, thereby improving overall efficiency and effectiveness. 

3. Generating solution scripts

When faced with complex technical problems, IT professionals could feed the issue into the AI system. The AI, having learned from countless similar situations, would then be able to generate a script with potential solutions – saving significant troubleshooting time and increasing the efficiency of issue resolution.

4. Analyzing system logs

When troubleshooting, IT support professionals have to go through extensive system logs. AI tools could come to the rescue here by analyzing these logs and highlighting anomalies or potential areas of concern. This would potentially save hours of manual work and help IT support professionals to pinpoint the root cause of issues faster.

5. Helping with unexpected errors

Generative AI will likely prove helpful when it comes to troubleshooting unexpected errors. By inputting the error codes or descriptions into the AI system, it would generate the most likely solutions based on its vast knowledge base. This will allow IT support professionals to provide quick and efficient help, greatly improving after-sales service.

6. Helping with unexpected errors

One of the common tasks for IT support professionals is to create and update user manuals and instructions. With the AI system, they could input basic outlines and the tool would generate comprehensive and user-friendly guides. This will reduce workload and ensure clear and consistent communication with the company's employees.

7. Predicting future issues

An AI system can analyze historical data to predict potential future IT problems. By inputting the company's system status and issue logs, an AI tool can predict potential areas of concern based on the patterns it has recognized. This will allow IT support professionals to proactively address issues before they can significantly impact the organization's operations.


Overall, generative AI still has to develop to become more accurate (avoiding “hallucinations” or nonsensical or false information). But the potential of such systems is already clearly visible. By integrating generative AI into everyday work, IT support professionals should experience an impressive increase in efficiency, effectiveness, and overall work satisfaction.