Cybersecurity and Generative AI: First Steps Toward Intelligent Protection

The relationship between CISOs and Generative AI (GenAI) is complex. While this technology features enormous potential for addressing cybersecurity challenges, a recent report by NTT DATA, "Cybersecurity and Artificial Intelligence: The Role of AI and Generative AI in Protecting Businesses," revealed that only one in four companies in Ibero-America is currently implementing use cases related to protecting data and digital assets.

There are multiple reasons behind this slow adoption. First, hackers utilize GenAI to refine and enhance their threats. Initially, this might seem unrelated to organizational security leaders. However, when surveyed, CIOs ranked "security and protection concerns" as the second most significant obstacle to adopting GenAI. However, CISOs viewed this issue as less critical, ranking it only eighth among their primary obstacles.

Another significant disparity lies in the perception between CEOs and CISOs regarding whether security risks associated with GenAI are properly recognized and managed within their organizations. Affirmative responses reached 96% among CEOs but dropped to 89% among CISOs.

Simultaneously, CISOs exhibit greater anxiety toward this innovation than other business leaders. Overall, 68% of respondents expressed "positive feelings" about GenAI, but this figure dropped to 49% among security managers. Moreover, CISOs reported negative emotions at a significantly higher rate than their peers: 45% indicated feeling pressured, threatened, and overwhelmed by the technology, compared to only 19% of other respondents.

However, 89% of CISOs remain highly satisfied with their investments in GenAI, even though 75% state that their teams lack the required skills. Additionally, 37% already foresee requesting external support to establish clear ethical and security frameworks and responsibilities for AI.

Recommendations: Align Strategies and Provide Training

Organizations adopting GenAI must manage numerous risk factors, including maintaining cybersecurity standards (threats, deepfakes, misinformation), legal considerations (intellectual property rights, regulatory gaps), transparency issues (explaining the reasoning behind complex models), privacy protection (user consent), ethical concerns (algorithm bias), accuracy challenges (poor data sources), and unclear ownership or accountability. Many of these responsibilities directly impact CISOs.

Can organizations capitalize on GenAI to enhance cybersecurity strategies while simultaneously reducing risks and overcoming the "fatigue" CISOs feel regarding these technologies?

The first step is fully aligning GenAI strategies with cybersecurity—a goal that more than half of companies have not yet achieved. It is essential to identify internal cybersecurity use cases for GenAI and ensure the organization provides the necessary tools to adopt the technology and manage associated risks.

Meanwhile, bridging the talent gap through upskilling and training opportunities becomes critical to keeping the cybersecurity workforce at the forefront.

The opportunity is valuable. Generative AI uses advanced machine learning algorithms and extensive datasets to detect patterns and anomalies overlooked by traditional methods, reduce false positives in threat detection, and automate routine tasks to accelerate incident response, among other benefits. We are experiencing a transformative era in data and digital asset protection, driven by innovations like GenAI.