AI is often presented as the next step in automating IT operations. But in IT asset management, many tasks don't need AI in the first place. Traditional automation already works well for routine processes that follow clear rules.
So where could AI and AI agents be useful in IT asset management, and what could they do that traditional automation cannot?
Find information without building another report
Traditional reports are great for answering questions you already know you need answers to. But sometimes IT teams need to investigate something that doesn't fit into an existing report or requires information from several different systems. This is where AI could be useful.
For example, you could ask AI to find all devices assigned to employees who have changed teams in the past six months. You could then take it a step further and ask whether those devices still meet the employees' needs in their new roles, or whether there are more suitable alternatives available in the inventory.
It is still good to remember that regular and recurring questions should be handled with traditional reports. AI is more useful when you need to investigate a specific situation, combine information from different sources or ask follow-up questions without having to build a new report every time.
Recommend a device based on how it is actually used
Choosing a new device for an employee is often based on their job title, a predefined device category or simply what they ask for. This doesn't always mean they get the device that best suits their needs. Some employees end up with more powerful hardware than they actually need, while others may not know what kind of device would work best for them. The end result might be costly and it also impacts the employee experience negatively.
With enough data on past device usage, an AI agent could help employees choose the right device based on how they actually used their devices in the past. Instead of relying only on predefined device profiles, it could analyse usage data, compare available options and recommend a device that meets the employee's needs without unnecessary costs. This helps organisations make better use of their IT budgets while ensuring employees have the equipment they really need for their work.
Decide whether a device should be replaced now
Devices are often replaced according to a fixed schedule, usually after three or four years. This makes lifecycle management easier, but it also means that devices in perfectly good condition may be replaced unnecessarily, while others that are already causing problems remain in use until their scheduled replacement date. This can lead to unnecessary hardware costs, while devices that should have been replaced earlier can cause lost productivity and additional IT support costs.
This is another case where an AI agent could help organisations make better decisions. For example, it could review devices approaching their scheduled replacement date and check their performance, battery condition, support tickets and usage history. If a four-year-old laptop is still working well and has no reported issues, the agent could recommend keeping it in use for another year. At the same time, it could flag a newer laptop with recurring problems for earlier replacement.
Carry the process forward, but keep approval with IT
An AI agent could also help IT teams manage upcoming tasks and decide what needs attention first. Instead of IT teams just working through a task list with deadlines, the agent could help prioritise tasks based on their urgency and impact. It could also identify potential issues that might otherwise go unnoticed.
For example, the agent could identify laptops with warranties about to expire and check whether any of them have recurring hardware problems. It could then recommend which devices should be serviced before their warranties run out. Similarly, when an employee leaves the company, the agent could check which devices are assigned to them, prepare return instructions and suggest what should happen to the devices afterwards.
The idea here is not to automate the process itself but to provide additional support for IT teams. People would still review and approve the proposed actions as before, but with better information and recommendations to help them make decisions.
Where does AI actually add something?
Coming back to the original question of when AI should be used in IT asset management, the answer is quite simple. If a task can be described as “when X happens, do Y”, traditional automation is usually enough. AI becomes useful when there is no single rule to follow, and making a decision requires comparing several options, weighing different factors or identifying problems that traditional automation might miss.
In IT asset management, this could mean helping employees choose the right hardware, deciding whether a device really needs to be replaced, communicating with users or finding answers to questions that would otherwise require a lot of manual work.
Want to learn more about how AI could be used in IT asset management? Watch our How to use AI in IT asset management webinar here.