The integration of AI models into business infrastructure is an undeniable boon to efficiency and innovation, but it comes with some inherent challenges, including security risks. As businesses embrace AI, particularly multimodal models, it’s critical to understand and address these constantly evolving hurdles.
Every AI model introduced into an organization’s digital framework expands the attack surface, meaning the models can become gateways for cyber attacks if not adequately secured. For instance, an attacker might exploit an unsecured data input channel or manipulate the model’s output. Securing a multimodal AI model is even more challenging due to its diverse data processing capabilities. Each data type—text, audio, code, images, video—introduces unique security requirements. Ensuring a comprehensive security approach that covers all potential vulnerabilities is a key consideration for protecting models against data breaches and cyber threats. In addition to these risks, compliance with evolving government regulations around data privacy has become a significant concern. AI systems now handle many types of sensitive data, from personal text records to biometric information.
Security teams must be able to know what is happening on the system in real time, which is a challenge when an organization’s digital infrastructure includes many diverse AI-driven and AI-dependent tools over and above the standard network-housed tools and applications. The most basic component of a wide-spectrum trust layer, therefore, is full observability: If no one knows what is happening on the system, malicious activity can’t be stopped.
CalypsoAI’s SaaS-enabled GenAI security, enablement, and orchestration platform is an external, non-porous system barrier with standard-setting features that enable organizations to anticipate and mitigate threats before they materialize, such as:
- The platform’s API-based design facilitates easy integration at the early stages of AI tool adoption, ensuring security considerations are embedded and accessible from the outset.
- Customizable, admin-established policy-based access controls enable enforcement of strict permissioning around who can interact with the models, preventing unauthorized use and data breaches.
- Admin-established criteria and thresholds provide organization-specific scanners and other guardrails that continuously review prompts and responses for anomalies and potential threats, allowing security personnel to take immediate preventative and responsive action.
The path to integrating AI into business operations is fraught with security challenges, but they are surmountable. By understanding the risks and implementing robust security measures, businesses can safely and securely leverage the power of AI to transform their operations.
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