Besides bad actors leveraging AI for social engineering and other cyberthreats, organizations’ use of AI can pose problems for their cybersecurity postures.

Heng Mok, CISO, APJ, Zscaler

Other than Zero Trust, there are several considerations for enterprises:

  • Comprehensive risk assessment: Before integrating AI tools, organizations need to conduct a thorough risk assessment, identifying potential vulnerabilities and security gaps. This assessment should encompass data privacy, regulatory compliance, and the specific security implications of AI implementation.
  • Data protection measures: Given the sensitivity of data processed by AI algorithms, robust data protection measures must be in place. This includes encryption of data at rest and in transit, access controls, and regular audits to ensure compliance with data protection regulations like GDPR and local data protection laws.
  • Employee training and awareness: Human error remains one of the biggest cybersecurity risks. Providing comprehensive training and awareness programs for employees, especially those involved in AI implementation and data handling, is essential to mitigate risks associated with phishing, social engineering, and inadvertent data exposure.
  • Regular ongoing threat and risk assessments: Conducting regular assessments to ensure that AI systems and security measures remain up to date to protect against the latest threats and vulnerabilities is essential. This includes patch management, vulnerability scanning, tabletop exercises, automated assurance and red teaming to identify and address any weaknesses proactively.