Arctic Wolf this week revealed it has acquired the Cyclance endpoint security platform from Blackberry for $160 million.

Dan Schiappa, chief product and services officer for Arctic Wolf, said the addition of Cylance to the company’s portfolio extends the scope of the cybersecurity capabilities provided to include endpoints.

Arctic Wolf is best known for providing managed security services but has recently been building and deploying its own software. Cylance adds an endpoint security platform that aligns with the company’s ongoing efforts to embed artificial intelligence (AI) into its offerings, said Schiappa.

Acquired by Blackberry in 2018 for $1.4 billion, Cylance was an early pioneer of embedding machine learning algorithms into cybersecurity platforms. Arctic Wolf now intends to leverage those AI investments across a portfolio of platforms and services that will all have AI capabilities, noted Schiappa. For example, the Cylance platform as a result will further evolve into a more advanced endpoint detection and response (EDR) platform, he added.

Arctic Wolf will not require any customer to license both its platforms and service but organizations that do will be able to lower their total costs, he added.

In general, as the overall size of that attack surface continues to expand it’s not going to be feasible for cybersecurity teams to manually defend organizations from cyberattacks that are increasing in volume and sophistication. The need to augment cybersecurity teams with AI, however, is also a factor in a wave of consolidation as cybersecurity vendors look to be able to aggregate as much telemetry data as possible to train AI models.

It’s not clear at what rate cybersecurity teams are embracing AI. In a few short years, many cybersecurity teams have moved from initial skepticism to concluding that successfully defending organizations is no longer feasible without help from AI. Even if thousands of open cybersecurity positions could be filled, the cost of adding all that headcount is prohibitive. The only way to discover and thwart threats is to rely more on AI to automate tasks in a way that should provide analysts with the time needed to identify subtler attacks that usually prove to be more lethal. In general, cybersecurity teams are viewing AI much more positively, said Schiappa.

The issue is that training those AI models requires a significant amount of time and effort using telemetry data that most organizations are not going to be able to collect enough of at scale to train an AI model on their own. As a result, many of them are going to become more dependent than ever on managed cybersecurity services.

One way or another, however, it’s only a matter of time before AI is pervasively employed by cybersecurity teams. There may be a significant amount of trial and error involved, but like it or not, cybersecurity teams are locked in an AI arms race. Cybercriminals are already evaluating many of the same AI technologies for their own nefarious purposes.

Of course, there is already no shortage of cybersecurity platforms that make use of AI. The challenge, as always, is finding the funding required to adopt the one that best fits the needs of the organization.