Ai Boosts Efficiency But Exposes Critical Infrastructure To New Cyber Threats
The Intersection of Artificial Intelligence and Cybersecurity: Shaping the Future of Critical …
31. July 2026
Artificial Intelligence Fuels Global Cyber Crisis As Breaches Skyrocket
The Rise of AI-Enabled Cyberattacks: A Growing Concern for Organizations Worldwide
In a recent report by IBM, the cost of data breaches has skyrocketed, with organizations worldwide paying an average of $6 million per incident. The increasing use of artificial intelligence (AI) and machine learning (ML) in cyberattacks is a major contributor to this trend.
According to the Ponemon Institute study, which examined 602 organizations between March 2025 and February 2026, AI played a role in one in four malicious breaches, resulting in significant financial losses. The report highlights the growing imbalance between security teams and attackers, with many organizations relying on traditional security measures rather than leveraging AI to proactively identify vulnerabilities.
The Economics of Cyberattacks Suja Viswesan, vice president of IBM Security Software, notes that “AI is making attacks faster and cheaper, while breaches keep getting more expensive.” The study found that organizations that used AI and automation extensively in security operations reported breach costs averaging $1.93 million less than those that did not use the technologies.
However, the widespread adoption of AI in cyberattacks is a concern for many organizations. While some companies are using AI to detect attacks already underway, far fewer are deploying it to find vulnerabilities before attackers can exploit them. This lack of proactive AI deployment is leaving security teams scrambling to respond to breaches after they occur.
The Most Common Causes of AI-Driven Breaches IBM found that more than 20% of organizations experienced breaches involving AI models or applications. The most common causes were weaknesses around AI systems, including:
- Compromised APIs, applications, or plug-ins: Many organizations are using third-party services or plugins to support their AI initiatives, which can leave them vulnerable to attacks if these services or plugins are compromised.
To mitigate this risk, organizations should ensure that they have a clear policy on the use of AI tools or systems and monitor their adoption closely. This is known as “shadow AI prevention.”
- Cloud misconfigurations affecting AI workloads: Cloud providers often offer a wide range of services and features that can be used to deploy AI applications. However, if these configurations are not properly set up, they can create security vulnerabilities that attackers can exploit.
To address this issue, organizations should implement strong identity management and access controls to prevent unauthorized access to AI systems.
- Insufficient identity management and access controls: Many organizations are struggling to control how AI tools or systems are used internally. Shadow AI – the use of AI tools or systems without organizational approval or oversight – was involved in 43% of the incidents IBM studied.
To prevent shadow AI, organizations should establish clear policies on the use of AI tools or systems and ensure that all employees understand their roles and responsibilities.
Critical Industries Face Higher AI-Related Risks Critical infrastructure organizations, financial services companies, and energy providers are experiencing a high concentration of AI-related attacks. Financial services breaches averaged $6.3 million, while energy breaches averaged $5.2 million. These industries are particularly vulnerable to cyberattacks because they often rely on complex systems and networks that can be exploited by attackers.
The Importance of AI Governance While companies are increasing their adoption of AI, many are struggling to control how the technology is used internally. The lack of proper governance and oversight is leaving AI systems unnecessarily exposed.
To mitigate this risk, organizations should implement robust AI governance measures, including:
- Proper access controls: Organizations must implement strong identity management and access controls to prevent unauthorized access to AI systems.
- Data protection: Organizations must encrypt sensitive data both at rest and in transit, as well as maintain a complete inventory of encryption keys, certificates, and other cryptographic assets.
The Future of Cybersecurity The report suggests that businesses cannot rely solely on traditional security improvements. AI is speeding up attacks, but it can also help organizations respond faster if deployed correctly.
However, the challenge is deciding where AI should be applied, with many companies using AI to investigate alerts after suspicious activity appears, rather than proactively identifying vulnerabilities before attackers find them.
In conclusion, the increasing use of AI in cyberattacks is a growing concern for organizations worldwide. As attackers continue to accelerate their use of AI, it is essential that businesses implement robust security measures, including proper governance and oversight, to prevent breaches and minimize financial losses.
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