Cybersecurity will account for almost a quarter of the AI ​​software market until 2025

By 2025, the artificial intelligence (AI) software market will grow from $33 billion to $64 billion in 2021, according to a new report. And cybersecurity is the fastest growing AI spending category, with spending increasing by 22.3% in compound annual growth rate (CAGR).

This is according to Forrester Research’s “Global AI Software Forecast 2022”. “Cybersecurity is the fastest growing category of AI software, with a focus on real-time monitoring and attack response,” the report said. The next two categories, customer and human capital management (22%) and process optimization, knowledge and data intelligence (18.3%), also have elements of cybersecurity, so the he impact on security tool makers could be even greater.

This aligns with companies’ focus on their AI-enhanced software and services. For example, credit giant Visa revealed that it had spent half a billion dollars on data analytics and AI over the past five years. It uses these tools, along with conventional cybersecurity measures, to keep the fraud rate at what Visa calls historic lows despite the growth of e-commerce.

Organizations can deploy AI for cybersecurity anywhere there are repetitive actions and expected behavior, including attack surface management, extended detection and response (XDR), and behavior analysis of users and entities (UEBA). Forrester cites SentinelOne as a great XDR success story, pointing out the 120% year-over-year revenue growth in fiscal year 2022. In March, SentinelOne added identity threat detection and response to its platform with the acquisition of Attivo Networks.

An AI tool can learn what is normal activity for a particular device or account and then report when that endpoint is acting outside the norm. Such automated detection is invaluable, given the impossibility of having enough staff to have human eyes monitor every part of the network. And researchers are finding ways to apply large language models like GPT-3 to practical tasks, such as tracing networks of mining forums. To provide some perspective on these developments, Dark Reading published a report in September, “How Machine Learning, AI & Deep Learning Improve Cybersecurity”, on how to assess a vendor’s AI claims and define their success criteria.

One of the hurdles in the gallop of AI is the challenge of setting up a system so that it signals what human analysts need to assess without creating alert fatigue. A survey conducted earlier in 2022 found that nearly half (46%) of IT security personnel said their AI systems had created too many false positive alerts for them to deal with. An optimist would see the problem of false positives as an opportunity for growth, yet opening up a new market for fine-tuning services.

For more information visit the Forrester Research blog entry on the report.

Margie D. Carlisle