3 Ways Machine Learning Can Make Your IT Team More Efficient

Featured article by Calvin Paige, Independent Technology Author

Business adoption of machine learning is accelerating rapidly. Sixty percent of businesses of all sizes had already implemented machine learning strategies last year, with one-third describing themselves in the mature phase of implementation, an MIT Technology Review and Google Cloud survey found. Organizations that haven’t yet adopted machine learning see it as a way to better understand their customers, gain a competitive advantage, attain more insight into data and improve operational efficiency. Organizations that are already using machine learning report that they are already seeing benefits in these and other areas.

Natural language processing, text data mining, emotional and behavioral analysis and image recognition are the four top current applications of machine learning. Top applications in the future are expected to be automated agents and chatbots, predictive planning, sales and marketing and smart assistants. Here’s a closer look at three ways IT professionals can use these applications of machine learning to achieve their business goals.

More Efficient Data Analysis

One benefit machine learning delivers IT departments is the ability to better organize data, says business consultant Robert Cordray. Today’s IT department collects an overwhelming amount of data. But raw data that isn’t organized isn’t useful. Machine learning enables computers to more efficiently cluster and categorize data into meaningful subsets for practical deployment.

For example, network administrators can use machine learning to categorize network traffic patterns and identify trends and potential problems. Similarly, IT personnel assisting marketing departments can use machine learning to more efficiently categorize market research data collected from large customer samples, generating insights into trends that might otherwise go overlooked.

Data-driven Operational Efficiency

By making the analysis of large sets of data easier, machine learning makes it possible to empower greater operational efficiency. Factors causing operational lags can be identified, and adjustments can be split-tested to generate measurable improvements.

For example, Prodapt Solutions used machine learning to assist a client who provided cloud hosting services and wanted to reduce downtime and backup failures in order to boost customer satisfaction. The result of applying machine learning was a 56 percent reduction in downtime due to acceleration, a 90 percent reduction in backup failures, and a 50 percent increase in customer satisfaction as measured by Net Promoter Score. IT professionals can use machine learning to increase both internal efficiency within their own department as well as the efficiency of other departments within their company.

Stronger Security

Security is another area where machine learning can deliver tremendous benefits. With the emergence of the Internet of Things, company networks potentially expose more points of vulnerability than ever before. Machine learning can make shielding these vulnerabilities easier by drawing on historic data to identify attack patterns and by applying analysis to detect current anomalies.

Mobile devices that incorporate machine learning likewise provide superior security. For instance, the built-in machine learning capacity of the Snapdragon 835 Mobile Platform enables biometric facial, eye and voice identification authentication, while also providing on-device, zero-day malware detection.

Enhancing data analysis, improving operational efficiency and strengthening security illustrate three of the many ways that machine learning can assist IT departments and their companies. IT departments that successfully integrate machine learning into their standard operational procedures can expect to enjoy deeper business insights and a smoother workflow, translating into greater success for their teams and their employers.