As South African businesses increasingly adopt Generative AI (GenAI) solutions, security technologists must be aware of critical factors to mitigate the risks. From regulatory compliance to data protection and adversarial threats, organisations need a comprehensive security strategy to safeguard AI solutions while maximising the benefits.

Key security challenges in GenAI adoption

Regulatory compliance and data sovereignty

The Protection of Personal Information Act (POPIA) regulates how businesses process and store personal data, imposing strict requirements on data handling and privacy. If employees input customer or internal data into GenAI models, there is a risk of non-compliance, potentially leading to regulatory penalties. A report by Webber Wentzel highlights that organisations using AI must implement strong data governance to remain compliant with POPIA, particularly when handling personal information.

To maintain data sovereignty, South African businesses should explore on-premises or locally hosted AI solutions rather than relying on international cloud-based GenAI models. This ensures POPIA compliance and minimises exposure to international data privacy risks.

Data integrity and security risks

Ensuring the integrity of data used by GenAI models is crucial to prevent biased or harmful outputs. Organisations must implement mechanisms to protect sensitive data from leaks and unauthorised access while ensuring compliance with local and global privacy regulations. 

According to the SANS Institute, GenAI applications are susceptible to various security risks, including data breaches, emphasising the need for robust data-protection measures.

GenAI models are also vulnerable to adversarial prompts, where malicious actors manipulate AI systems into generating misleading or harmful results. South African businesses must implement robust security measures, including adversarial testing, access controls, and real-time monitoring to detect and prevent AI manipulation attempts. Research from the SANS Institute highlights prompt injection attacks as a growing concern, demonstrating how threat actors can exploit AI vulnerabilities.

Expanding attack surface and cyber-threats

The use of GenAI expands an organisation’s attack surface, introducing new vulnerabilities that cybercriminals can exploit. According to IBM’s Cost of a Data Breach Report 2024, South African businesses have faced significant financial impacts from data breaches, with the average cost per incident reaching R53.10 million. 

The report highlights that stolen or compromised credentials were the most common initial attack vectors, accounting for 17% of breaches. AI-powered security measures have been shown to reduce breach costs by an average of R19 million.

A comprehensive cybersecurity strategy must cover the entire AI development lifecycle, incorporating threat modelling, penetration testing, real-time security monitoring, and continuous AI risk assessments. Proactive security testing, including red-teaming exercises, can help organisations identify and mitigate AI vulnerabilities before they are exploited by attackers.

Governance, risk management, and compliance

Establishing strong governance, risk management, and compliance policies is essential to secure and regulate GenAI applications. This includes defining acceptable AI use cases, implementing risk assessments, and ensuring alignment with local data protection laws. Organisations should also maintain documentation of AI interactions to facilitate audits and compliance verification.

To mitigate risks while leveraging the benefits of GenAI, businesses should adopt the following best practices:

To mitigate risks, businesses should establish clear AI usage policies that outline acceptable AI use cases, restrict sensitive data input, and implement governance protocols to validate AI-generated outputs. 

Ensuring that human oversight mechanisms align AI decisions with business objectives is crucial, particularly for compliance with POPIA. Strengthening data governance is another essential step, as recommended by the SANS Institute. This includes enforcing data anonymisation techniques to prevent sensitive data exposure, implementing access controls and Data Loss Prevention (DLP) solutions, and using middleware layers to filter AI training data and ensure only authorised information is used.

Security should also be embedded into AI development workflows to mitigate AI-related threats. This involves conducting regular security audits and vulnerability assessments, deploying AI-powered monitoring solutions like Security Information and Event Management (SIEM) systems to detect anomalies in real time, and implementing continuous monitoring tools to flag potential security threats. 

Additionally, cybersecurity awareness training is vital to educate employees on AI-related risks and safe usage practices. According to ENS Africa’s report on data breaches, AI can enhance cybersecurity by identifying patterns of malicious activity and detecting potential threats. Training should focus on recognising phishing attempts involving AI-generated content, understanding the risks of sharing sensitive data with AI tools, and implementing strong authentication measures to protect AI applications.

When selecting a GenAI vendor, businesses must prioritise data localisation and compliance, ensuring that all data is stored and processed within South Africa to align with POPIA and reduce exposure to international data privacy laws. Security and access controls should be a key consideration, with a focus on end-to-end encryption, multi-factor authentication (MFA), and role-based access controls (RBAC) to restrict AI access. 

Transparency and ethical AI practices are also crucial; vendors should provide clear AI audit mechanisms, bias detection and mitigation tools, and comply with security standards such as POPIA, ISO 27001, and NIST AI risk-management guidelines.

Preventing AI misuse is another critical factor, and reputable GenAI vendors must enforce policies that prohibit the generation of deepfakes, disinformation, and biased or misleading content. 

AI security is an ongoing process, requiring vendors to commit to regular security updates and patches, as well as continuous monitoring and support to detect and mitigate AI vulnerabilities. By adopting these best practices, businesses can harness the power of GenAI while maintaining security, compliance, and ethical integrity.

Much like cloud misconfigurations can expose sensitive data, GenAI presents similar risks that require proactive security measures. By implementing local AI governance frameworks, enforcing POPIA-compliant data protection protocols, and choosing secure, South Africa-aligned AI vendors, businesses can leverage GenAI’s benefits without compromising security or regulatory compliance. Ensuring responsible AI adoption will not only protect organisational data but also enhance trust and resilience in an evolving digital landscape.