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Artificial Intelligence (AI): 3 Everyday IT Tasks Where Automation Fits In

If I asked someone why they chose a career in information technology, I doubt they would answer with “I love data entry!”, “I could debug code all day!” or “Managing tickets is so much fun, I would do it even if I didn’t get paid for it.

3 IT tasks that can be automated with AI

Fortunately, AI can help. Here are the top three ways AI can help automate manual IT tasks, freeing up valuable resources and benefiting your teams, businesses, and customers.

1. Debug software

Grace Murray Hopper was a Navy rear admiral and computer programming pioneer who worked on the Mark II computer at Harvard in the 1940s. On September 9, 1947, Hopper traced an error with the Mark II to – of all things – a dead butterfly in the relay. The insect’s remains were recorded in the team’s logbook with the caption “First real case of insect discovery”.

Although Hopper and his team weren’t the first to use the term “bug” to describe a system problem, they certainly helped popularize it. Of course, software bugs are decidedly unpopular. IT departments and software engineers have all felt the pain of working through lines of code trying to reproduce and locate problems.

[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]

To be as good as human engineers, an AI tool should possess levels of reasoning and creativity that it simply hasn’t yet reached. But AI can still be extremely effective at detecting exceptions and anomalies. You train it for normal use and it detects when something is off.

Another advantage of AI over humans is its pattern detection. Suppose a system crashes at the same time every week or after memory usage reaches a certain level. An AI tool could easily connect the dots. The AI ​​can learn which behaviors of your developers and which code patterns that are checked in your repository correlate to bugs. This can be used to notify developers that they have done something that is likely to break and ask them to check again.

If you had an infestation of moths in your home, you could definitely crush them one by one. But wouldn’t it be much easier to find out where they are hiding and set traps?

2. Predict future problems

The adage “an ounce of prevention is better than a cure” is as true in computing as it is in medicine. Monitoring operations and taking proactive action instead of just reacting to problems as they arise can prevent unexpected downtime and costly outages.

CIOs and IT professionals know to some extent the value of preventive maintenance, whether it’s installing software updates or creating backups. This type of maintenance is performed after a certain amount of time has passed or usage has been logged. It’s like eating vegetables or exercising – these are good business practices.

[ Read also: 4 Robotic Process Automation (RPA) trends to watch in 2022. ]

Predictive maintenance, on the other hand, is individualized and tailor-made. It monitors the equipment and its environment, performs tests and receives feedback from the equipment to generate individualized predictions. It’s like having a blood test that shows you’re pre-diabetic and in response you design a low-sugar diet.

People can be uncomfortable with the idea of ​​machines watching over them all day. But with AI-based predictive maintenance, you monitor machines – together with other machines.

Dealing with IT tickets can feel like playing a perpetual game of Whack-A-Mole, but with all the exhaustion and none of the fun carnival music and prizes.

3. Filtering lower level incidents

Dealing with IT tickets can feel like playing a perpetual game of Whack-A-Mole, but with all the exhaustion and none of the fun carnival music and prizes.

As we all know, some incidents deserve your attention and others not at all. And without a proper way to triage incidents, IT departments are overwhelmed. Enter smart filters. They have been around for years in search engines and email inboxes, distinguishing between the good and the bad, the important and the unimportant. For IT departments, they can distinguish between real incidents and noise.

Learn more about artificial intelligence

Using AI techniques such as case-based reasoning can help decide which solution to explore first or what additional information to request from a customer to make a quick and accurate diagnosis. Case-based reasoning systems learn from successes and failures, apply sophisticated probabilistic reasoning to identify promising solutions, and build a valuable knowledge base.

With smart filters and case-based reasoning, IT managers can better allocate resources to incidents that require human intervention.

While there are plenty of AI applications out there that help IT departments — and many more to discover — debugging, predictive maintenance, and smart filtering are three essential AI applications for any large IT department. today.

As AI becomes more integrated into our work, any organization that does not actively explore automating its more manual IT tasks is wasting valuable financial and human capital — and possibly falling behind.

[ How does AI connect to hybrid cloud strategy? Get the free eBooks, Hybrid Cloud Strategy for Dummies and Multi-Cloud Portability for Dummies. ]