How artificial intelligence and machine learning are advancing ITAM

It’s not uncommon for organizations to spend excessive amounts of time and energy cleansing their data.

The task of normalizing something as simple as the way “Microsoft” is presented and spelled within datasets can be laborious and exhausting. Coupled with how much data most companies have and the manual processes that many use to manage it all, it’s no wonder that businesses struggle to implement successful IT asset management (ITAM).

Fortunately, this tall order is going to get easier. Over the next few years, 80–90% of the manual processes involved in ITAM will be replaced by automation.

The driving forces behind this massive overhaul will be developments in artificial intelligence (AI) and machine learning (ML). Here’s how they’re going to make ITAM more efficient and less time consuming.

Automating processes through AI

AI technology allows you to automate processes. The financial world has taken advantage of AI technology for years, with analysts using various algorithms to predict future market trends.

AI can have a similar effect in ITAM practices.

By using AI algorithms to comb through ITAM data, you can discover previously unseen patterns and identify the broader organizational implications of each asset.

With this information, you can focus efforts on developing recommendations for improvement – particularly when it comes to return on investment (ROI). We’ve seen this firsthand.

For instance, SHI’s new 365 Cost Optimization Services use AI algorithms to help customers optimize their Microsoft estate cloud spend. We worked with an organization that had 106,000 Office 365 users, with E3 licenses across the board. Using AI algorithms, we examined the company’s consumption and identified nearly $1 million in savings per year.

By automating with AI, we helped the customer cut down on licenses needed, reduce costs, and make more informed IT decisions – all while using a process that took minutes as opposed to days.

ML predicts future states using data patterns

While sometimes conflated, ML is different than AI. Both remove the manual processes of ITAM while helping you improve everything from costs to compliance. But with ML, the “machine” picks up on manual processes and learns them without being explicitly programmed to do so. ML can predict future states and make recommendations based on data patterns.

Think about the software licensing market, for example – by teaching a machine to see certain patterns, you can determine the right number of licenses for your business at that moment. But that’s just one application.

You can also apply machine learning for compliance measures. In using the technology to analyze behaviors, you can determine if your environment is compliant from a security and licensing perspective.

By using data patterns to predict future states, you can take proactive steps to maintain the health of your company’s IT estate.

Having the right information to make informed decisions

As AI and ML technologies mature, reducing human dependence and eliminating human limitations, ITAM teams will be able to measurably increase the scale and speed with which they deliver their services to customers and their own organizations.

Despite certain misconceptions, AI and ML are not meant to make decisions for you. But, when applied to ITAM, both AI and ML enable you to identify and bring the relevant business intelligence efficiently and effectively to decision-makers. That way you can save money, right-size your deployments, and ensure compliance while also freeing up your staff’s time. Everyone wins.