Security teams want automation but 96 percent face problems implementing it
A new survey of 750 senior cyber security professionals across the US, UK and Australia, carried out by Opinion Matters for ThreatQuotient, finds 97 percent now regard automation, increasingly powered by AI technologies, as essential to business operations.
However, despite 49 percent of respondents obtaining net new budget allocation for cybersecurity automation this year -- up from 39 percent last year -- 96 percent still face persistent challenges, particularly around technology limitations, lack of trust in the outcomes of automated processes, and insufficient time to implement solutions.
The report also finds key performance indicators for automation are evolving toward a new operational standard, with a marked shift away from its impact on employee well-being towards more quantifiable metrics. While previous reports identified employee satisfaction as the leading measurement criteria, this year 56 percent of respondents are prioritizing Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) as core indicators of effectiveness. This pivot reflects a growing emphasis on performance outcomes, as organizations seek tangible, data-driven improvements to validate rising investment levels in automation technologies.
"With automation firmly established, organizations are now working to implement autonomous AI-powered cybersecurity," says Leon Ward, chief transformation officer at Securonix. "However, deploying AI in cybersecurity is not without its challenges. We found that increasing productivity is the leading driver for AI implementation as organizations aim to respond faster to threats from adversaries who are also using AI to advance attack speed and complexity.”
Respondents say that pressure from the board is the dominant driver for both efficiency and productivity, with 71 percent saying their senior leadership team is driving AI adoption. But 28 percent of respondents also say gaining management buy-in is a top problem they encounter. This suggests that the strong focus on unlocking the competitive benefits of AI is being hindered by tactical uncertainty over specific use cases.
A lack of human skill, AI making incorrect decisions, and technology issues all present key challenges, and they echo many of the difficulties seen in automation adoption. However, organizations are also concerned about ethical issues (31 percent), such as data privacy and algorithmic bias. A lack of accountability also features in their top three concerns about using AI. Only 23 percent say being left behind by competitors was a top three concern.
The full report is available from the ThreatQuotient site.
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