Cyber threats are an ever-present danger to global economies and are projected to surpass the trillion dollar mark in damages within the next year. As a result, the cybersecurity industry is investing heavily in machine learning in hopes of providing a more dynamic deterrent. ABI Research forecasts machine learning in cybersecurity will boost big data, intelligence, and analytics spending to $96 billion by 2021.
ABI Research finds the government and defense, banking, and technology market sectors to be the primary drivers and adopters of machine learning technologies. User and Entity Behavioral Analytics (UEBA) along with Deep Learning algorithm designs are emerging as the two most prominent technologies in cybersecurity offerings, especially in innovative hot tech startups. Established antivirus (AV) players in the market, such as Symantec, continue to transform some of their solutions from highly trained supervised models to unsupervised and semi-supervised ones in preparation of the constantly shifting threat variables.
IDC says that worldwide revenues for big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%. In addition to being the industry with the largest investment in big data and business analytics solutions (nearly $17 billion in 2016), banking will see the fastest spending growth.
IDC also predicts that by 2018, 75% of enterprise and ISV development will include cognitive/AI or machine learning functionality in at least one application, including all business analytics tools.