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Cyberattacks are evolving and becoming more sophisticated, making it critical for cybersecurity professionals to apply AI to their workflows. With the right training, AI can help reduce workloads and improve risk assessment, detection and response. But the potential to increase speed, accuracy and scalability of threat protection also makes AI an attractive target for malicious actors who seek to bypass or manipulate security systems.

In the case of generative artificial intelligence (GAI), attackers can tamper with input to make the model produce unintended outputs, such as offensive text or revealing confidential information. This is known as prompt injection attacks and is a growing threat, especially for large language models such as ChatGPT, which are used in phishing attacks. Additionally, AI systems can be tampered with to create malware or to gain access to sensitive data, leading to costly consequences for organizations and individuals.

To ensure that AI tools can be trusted, leaders must implement security protocols to protect the technology from unauthorized use or tampering. This includes adhering to standards such as ISO/IEC 27001 for information security management, and implementing roles, privileges and multi-factor authentication. Organizations can also take advantage of a range of existing data security and encryption technologies to secure AI from breaches, including cryptographic key generation, AES-CBC and DES encryption, and deploying cloud platforms that support encryption. Lastly, it’s important to regularly conduct security assessments and monitor and optimize data protection processes, such as encryption and tokenization, so that the organization can stay ahead of emerging threats.