- Three in four organizations now use AI, 99% say it’ll influence their renewals
- AI can help boost speed and accuracy, but human oversight is crucial
- Many are still worried about data privacy and cost
Three in four (73%) organizations worldwide have now integrated AI into their cybersecurity strategies, with data-heavy industries like financial services (82%) leading the way with adoption, new research has found.
A study by Arctic Wolf added most companies (73%) are now using AI to automate their security operations for around-the-clock protection, but threat prediction and prevention (72%) and boosting detection capabilities (70%) are also high on the priorities list.
Looking ahead, virtually all (99%) of the 2,000 IT and security decision-makers surveyed said that AI would influence their cybersecurity purchases or renewals in the next 12 months.
AI and cybersecurity now go hand-in-hand
Arctic Wolf highlighted the continued importance of human oversight – but by combining it with AI tools, companies can, “cut through the noise, reduce alert fatigue, accelerate investigations and help security teams focus on stopping the threats that matter most.”
More than two-thirds agreed AI needs substantial human input for it to be highly successful, with half (52%) planning to upskill their cybersecurity teams for AI.
“The insights from this report give leaders the data they need to make smart, targeted investments, deploying AI where it can deliver measurable outcomes, cut through alert noise, and help security teams work with greater speed, accuracy, and confidence,” Technology and Services President Dan Schiappa summarized.
However, the same old challenges persist. We’re talking data privacy (33%), cost (30%) and concerns that AI doesn’t fully meet business needs (28%).
Arctic Wolf also worries that a misunderstanding of AI skills could cause further delays.
Thankfully, off-the-shelf products integrate AI directly into cybersecurity solutions so that there’s no need to learn new languages or query structures.
“Unless your organization is looking to build and develop their own in-house artificial intelligence and machine learning models, most are highly unlikely to be limited in their success due to a lack of AI expertise,” the report concluded.
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