Akhilesh Tripathi comments in MIT Sloan Management Review:
25% to 30% of the typical IT environment changes annually; companies upgrade systems, apply software patches, move to new platforms, add new technologies, and certify new applications. In complex, dynamic systems environments, hundreds of thousands of incidents occur, generating overwhelming amounts of data. IT departments must improve efficiency. Doing so re- quires log analysis, performance optimizing, capacity planning, and infrastructure scaling. These tasks demand finding patterns in massive data sets and are often dull and repetitive. They are perfect, then, for AI automation(which) can enhance speed and accuracy.
Technology has become so deeply entwined in our personal and work lives that we have come to expect omnipresence and availability from a huge breadth of information and services. No one feels the pressure of this demand more than enterprise IT professionals, who must keep up with constantly evolving digital technologies. As much as 25% to 30% of the typical IT environment changes annually; companies update and upgrade systems, decommission others, apply software patches, move to new platforms, add entirely new technologies, and certify new applications. It’s little wonder that IT has been one of the earliest and most enthusiastic adopters of artificial intelligence.
IT Workers Face Endless, Repetitive Labor — Like Sisyphus
In today’s complex, dynamic systems environments, hundreds of thousands of incidents can occur in just minutes of business uptime, generating overwhelming amounts of data about operations. IT workers have to cut through this deluge to find and address problems like a credit card transaction mistakenly declined or a network crash that throws a crucial system offline. It’s become nearly impossible for even the best IT teams to respond quickly and effectively.
It’s absolutely necessary to resolve IT issues, but such fire-fighting does not contribute to the growth of the organization. Worse, an IT worker can start to feel like the mythical Sisyphus, pushing a stone up the hill to solve one problem only to see it roll down again when another ticket opens. Such an environment can drive even the brightest, most capable IT people to suffer burnout and leave.
Even as IT departments try to prevent revenue losses caused by unexpected downtime, they must also improve IT efficiency and continually transform customer experience. Doing so re- quires that IT workers engage in log analysis, performance optimizing, capacity planning, and infrastructure scaling. While IT infrastructure is dynamic, its problems are well defined. These tasks demand finding patterns in massive data sets and are often dull and repetitive. They are perfect, then, for AI automation. AI tools can enhance both the speed and accuracy of such work, reducing stress on IT employees.
Using AI to Improve IT Performance and Efficiency
Of course, there have been previous waves of automation in IT and business processes, and these have traditionally not scaled well in dynamic enterprise environments. Today’s AI-based automation is different. IT departments using off-the-shelf AI tools are already reducing unscheduled downtime of revenue-generating systems. In fact, AI tools are helping IT operations resolve problems within minutes instead of hours, and transforming customer experience for IT and the business overall.
We are seeing that AI is adaptive, scalable, and autonomous. It is capable of using multiple kinds of intelligence. As a recognition intelligence, it can find patterns in immense quantities of data. As a reasoning intelligence, it can tell what those patterns mean: Are they reflecting deviations in normal enterprise systems behavior that mean a system breakdown is looming or an attack from malicious sources is imminent? And as an operating intelligence, it can help manage the problem — both making recommendations for how to fix it as well as invoking automated, prescribed actions to fix it.
AI also improves how IT people see the connection between technology and the business. The IT environment features distinct towers of expertise: There’s the database, middleware, operating systems, storage, network, and so on. Each tower is staffed by people who know its area intimately but may have a limited view across the overall enterprise. AI can be a contextual engine that cuts across all of IT’s siloed towers; it is better able to pinpoint the source of a problem than any individual in the organization. Experience shows us that the most difficult part of fixing IT issues is identifying the source of the problem.
Considerations for Implementing AI in IT
New technologies can be idealized in ways that create difficult-to-meet expectations, and AI is no different. Indeed, AI’s prominence in popular culture has created a variety of perceptions about what it can do, from panacea to paranoia. It is crucial for CIOs to have a clear sense of how and why AI is going to be applied in IT. CIOs who do not carefully define how AI will be applied risk losing control of business expectations for the technology.
There are multiple ways for CIOS to bring AI into IT. The highest dollar value comes from using it for business assurance, keeping revenue-generating systems running and fixing whatever problems do occur more quickly. Another effective way to get buy-in for and payoff from AI is to apply it to specific issues such as improving customer experience issues or driving IT agility.
One plus for IT is that companies may not have to try to find and attract scarce AI talent. It doesn’t hurt to have IT staff with AI skills, but vendors are building intelligence into their systems, and IT-oriented AI-as-a-service offerings are available. From an enterprise perspective, IT AI should mean significantly less time putting out IT fires. That means CIOs can begin to redeploy their human capital, focusing their team more on the growth and transformation of the enterprise instead of keeping the lights on. Ultimately, that means AI will help the CIO be much more aligned to business needs.
Over the longer term, AI will develop in its ability to handle higher-level, more complex problems. As it does so, IT’s role in the enterprise and its ability to respond to business needs will change markedly. AI could usher us into a golden age for IT.
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