Companies are quickly adopting cybersecurity products and systems that incorporate artificial intelligence (AI) and machine learning, but the technology comes with significant challenges, and it can't replace human analysts, experts say. In a Wakefield Research survey published this week, for example, almost half of IT security professionals (46%) said their AI-based systems create too many false positives to handle, 44% complained that critical events are not properly flagged, and 41% do not know what to do with AI outputs. In total, 89% of companies reported challenges with cybersecurity solutions that claimed to have AI capabilities. Not all AI-based projects are created equal, as some technology is more mature, says Gunter Ollmann, chief security officer at Devo, which sponsored the survey. "When they talk about rolling out AI for cybersecurity ... those are the projects that are commonly failing," he says.

Organizations have experienced "two years' worth of digital transformation in two months," Microsoft CEO Satya Nadella said earlier this year. Much of this change has centered on cloud adoption, which has been a key part of supporting the shift to work-from-home environments. Gunter Ollmann, chief security officer for Microsoft's Cloud and AI Security division, saw the redesign of access to corporate assets and the cloudification of on-premises assets as more businesses decided to work remotely in the long term. While end-user security has improved throughout the acceleration, a few security gaps remain that still need to be addressed. "The digital transformation has added a whole other layer to the environment that has to be managed and secured," Ollmann said in an Interop Digital keynote interview with Dark Reading executive editor Kelly Jackson Higgins.