Can artificial intelligence strengthen your IT resilience?

Digital Delivery
8 min
Digital Delivery
Can artificial intelligence strengthen your IT resilience?

IT resilience goes beyond finding ways to prevent disruptions. A reliable IT resilience strategy should anticipate all possible disruptions and adapt to emerging situations before they cause an outage.

Recent improvements in artificial intelligence (AI) technology present several opportunities for businesses to improve their IT resilience. Given that criminals have started using generative AI tools like ChatGPT to write malware, it only makes sense for IT professionals to add more AI features to their systems.

Of course, IT resilience needs to address more than security threats. How will AI play a role in strengthening IT resilience? Our experience shows exceptional opportunities that could make AI critical to any system’s success.

AI excels at recognizing patterns

The human brain does a pretty good job of recognizing patterns. Our ability to notice patterns is one reason we can find Waldo on a crowded page of characters and anticipate when a song will shift from a verse to a chorus.

Artificial intelligence can also learn how to find patterns within chaotic environments. AI, however, can process massive amounts of data quickly, which means it can dig deep into information to recognize patterns humans can’t detect without help from technology. Since AI excels at pattern recognition, we can use it to strengthen IT resilience by anticipating threats and adapting over time.

Why does the amount of data AI can process make it so much more effective than the human brain at pattern recognition? Imagine you have a list of 30 numbers. Within that set, you see that the numbers 9, 4, 5, and 1 frequently cluster together. Upon closer inspection, you see that the four numbers repeat in a predictable way. Now, you know when to expect the repeating numbers as your data set grows.

AI’s ability to process big data means it could look at a much larger data set to find more complicated patterns. Perhaps it spots a 100-digit pattern within a data set with a billion numbers. Even the smartest person couldn’t see the pattern, but AI can do it within seconds.

Why resilient IT needs advanced pattern recognition

Resilient IT needs to anticipate potential threats so it can prepare defensive maneuvers. Since AI can find patterns within incredibly large data sets, it can find patterns and anticipate events much more accurately than people can.

By adding AI to IT resilience, we can detect changes and respond by adjusting asset allocation to match user needs or take a proactive defensive position to prevent a cyberattack.

AI can automate IT resilience tasks

Recognizing a potential problem is critical to IT resilience. It doesn’t help much, though, unless you have a way to implement changes within your system quickly. Even with a fault tolerance strategy in place, you might need a human to install a security patch to close a vulnerability, reallocate resources to meet increased user activity, or recruit more server space to accommodate large data exchanges.

Putting AI in charge of these decisions adds significant protection to your IT ecosystem.

With AI performing more tasks, you:

  • Lower the risk of human error.
  • Improve the system’s flexibility so it can adapt to changes.
  • React automatically to known and potential threats.

When every second counts and you can’t tolerate mistakes, you want AI in the driver’s seat.

AI increases observability in distributed systems

In some ways, distributed systems make IT easier to manage because it breaks down monolithic apps into smaller assets. As the number of distributed components grows, though, they start to boggle the human mind. Who could manage 100 microservices that each rely on diverse code components? Mapping these systems gets complicated very quickly.

AI can improve observability in distributed systems by keeping track of assets, measuring important metrics, and sending alerts when it finds a developing issue.

AI can also assist by tracing application lifecycles across systems. It doesn’t matter how many apps, components, and dependencies you manage. AI can track them and make small adjustments to improve performance.

AI already plays similar roles in DevOps. DevOps automates as many processes as possible to continually improve and test products. For example, we often use AI tools to test code before committing it to a repository.

The increased observability you get from AI means you can let your system monitor and repair itself. You might need to intervene when a major problem arises. As long as AI can observe metrics across diverse systems, though, it can make minor changes to prevent disruptions and improve user experiences.

What AI can’t do (at least not yet)

AI can’t strengthen every aspect of your IT resilience strategy. Some decisions still require judgment calls that only humans can make.

For example, inclement weather could strike at any time. AI might have access to information about local weather, but it probably doesn’t have information about the wind speed at an exact location.

A human, however, could see strong wind outside of a building, worry the wind might cause a power outage, and decide to protect the day’s work by updating local files to the cloud.

Will that change in the near future?

Potentially, but it would likely require location-specific sensors to detect things like wind, interior flooding, and smoke. For now, we like to use AI in ways we know it works very well. After all, we want AI to function as an assistant that makes work easier. It doesn’t need to remove people from IT resilience processes.

Start getting more from your IT resilience strategy

Have you already added AI to your IT resilience strategy? Or do you have concerns about how to properly strengthen your IT resilience with AI?

Contact our team to learn more about how AI could fit into your resilience plan. We’re always excited to discuss how new technologies influence how organizations operate!

Published on
April 5, 2024

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