05 Nov How AI in Cybersecurity Can Reduce Costs and Increase Security
The impact of artificial intelligence (AI) on cybersecurity is complicated, creating both new threats and new opportunities. On one hand, AI is increasingly utilized by malicious actors to enhance the sophistication and scale of cyberattacks. On the other hand, government agencies and private organizations are leveraging AI to bolster their defenses against these evolving threats.
Despite its double-edged impacts, one clear advantage of AI in cybersecurity is its potential to significantly reduce costs associated with cybersecurity. According to a survey conducted by IBM, organizations that extensively employ AI in their cybersecurity strategies report an average data breach cost of $3.6 million, compared to $5.4 million for those without AI—a whopping 33% cost savings. Even limited use of security AI leads to lower costs, with breaches costing an average of $4.0 million with only limited AI deployments. These figures highlight the substantial financial benefits of integrating AI into cybersecurity frameworks.
But how does AI enable these cost savings? Let’s dig in.
Faster Detection and Response Times
One primary mechanism by which AI reduces cybersecurity costs is through faster identification and response to security breaches. The IBM survey found that organizations using AI extensively identified breaches an average of 88 days faster than those without AI. Speed is critical in cybersecurity, as the longer a breach goes undetected, the more damage it can cause.
“Time is the new currency in cybersecurity, both for the defenders and the attackers,” writes IBM in its 2023 Cost of Data Breach report. “As the report shows, early detection and fast response can significantly reduce the impact of a breach. Investments in threat detection and response approaches that accelerate defenders speed and efficiency – such as AI and automation – are crucial to shifting this balance.”
Elie Bursztein, Google and DeepMind’s AI Cybersecurity Technical and Research Lead, suggests that AI could eventually enable real-time incident reporting and response. By automating the generation of incident reports and expediting response times, AI can significantly mitigate the damage caused by cyberattacks and reduce the associated costs.
Automation & Enhanced Efficiency of Cybersecurity Professionals
AI also enhances the efficiency of cybersecurity professionals, allowing them to manage the increasing volumes of data and threats more effectively. For most cybersecurity teams, there is simply too much data to keep up with. “We’re talking terabytes or petabytes of data on a daily basis, and the only way you can analyze that effectively is using the latest advances in AI and machine learning to crunch through all that data,” Shailesh Rao, president of AI-based security platform Cortex at Palo Alto Networks, told CSO Online. He’s far from alone in that assessment: 92% of security leaders say automation is critical to dealing with large volumes of alerts.
AI and automation solutions enable cybersecurity teams to process and analyze vast amounts of data swiftly, identifying potential threats that might have been missed otherwise. By helping human workers make better use of mountains of data, AI can make people more efficient. Cybersecurity professionals agree: 82% say that AI makes them more efficient, according to a survey by the International Information System Security Certification Consortium (ISC2).
Reduction in False Positives
AI can also reduce the number of false positives in threat detection, which can be both time-consuming and costly to investigate. “As the majority of the security assessments are performed manually, there are more chances for human errors, misinterpretation of alerts/data, or missing subtle signs of exploits leading to false negatives and positives,” writes ISACA, an international professional association focused on IT governance. Those false findings waste time, resources, and money to investigate.
AI and machine learning (ML) algorithms can differentiate between benign and malicious activities more accurately, ensuring that security teams focus their efforts on genuine threats. In fact, research shows that AI and ML can reduce false positives by as much as 86%.
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