The artificial intelligence (AI)-dependent digital ecosystem is slowly, but steadily, becoming subject to greater regulation and oversight from bodies internal to the organizations deploying AI and external regulatory entities, such as the European Union and the U.S. Securities and Exchange Commission (SEC). Achieving and maintaining compliance within this continually changing landscape is not an option, but a painful reality for organizations that want to adopt and capitalize on this paradigm-shifting technology sooner rather than later. Meanwhile, squeezing the same companies from the other side of their expansion of AI-dependent tools in the workplace is the omnipresent threat of cyber attacks, which are rapidly increasing in volume and malicious effect, and easily outpacing most efforts to stop or mitigate them.
Living in this space between the rock of compliance and the hard place of cybercrime, AI- and cyber-security teams must adopt and implement proactive safeguards and strategies now. The list below presents five steps that will enable your organization to achieve and exceed compliance goals while ensuring the safety, security, and resiliency of your digital infrastructure.
Identify the Risks Your Organization Faces
Securing a digital infrastructure is the modern equivalent of finding your way through a labyrinth in ancient times: They’re both complicated and intricate, and making one mistake can really ruin your day. Identifying every potential risk your organization faces is truly akin to mapping out unknown territory. But scrutinizing every facet of the system for vulnerabilities, from the expansive known attack surfaces to the known unknowns of shadow AI to the networks with alternately protected and porous portals, is not enough.
It’s critical to know what data is stored, transferred, and manipulated by the different teams and tools, and to understand which policies and regulations apply to how and by whom that data is handled. Existing accountability measures must also be assessed. Assembling a cross-functional Risk team that includes representatives from Legal, Compliance, and AI Security, as well as other business functions, will provide the wide-angle perspective needed to ensure that preliminary risk assessments are executed with both security and compliance in mind.
Understand the Organization’s Risk Appetite
An organization’s risk appetite refers to the amount of cybersecurity risk it is willing to tolerate while pursuing its business objectives. It varies from company to company and is heavily dependent on the firm’s financial resources, market presence, organizational culture, and, more recently, its industry and government regulatory burdens. The Risk team must work with senior leadership to establish and identify the type and degree of risk the company will accept. That information establishes a risk hierarchy that can be translated into actionable policies and guidelines that comply with regulatory standards and requirements.
Create a Framework for Policy Management
Policies serve as the bedrock of any compliance framework, providing clarity and consistency when navigating complex regulatory landscapes. Establishing a muscular AI governance framework involves the Risk team and experts from other business units collaborating to craft, disseminate, and implement clear, robust guidelines that align to corporate values. These rules must set expectations for employee behavior, identify both technical and human controls that will support those expectations, and outline consequences for failing to meet or for flouting those expectations.
Transparency on the part of the company regarding the utilization of AI technologies can bolster trust and accountability internally and among external stakeholders. Assigning stewardship and oversight roles can help ensure compliance and alignment across the organization. Regular audits and updates will ensure that the policies remain agile and responsive to emerging threats and regulatory changes.
Deploy the Controls
Balancing rigorous behavioral controls, such as policy-based access controls, traceability mechanisms, and zero-trust authorization procedures, with productivity, efficiency, and ease-of-use is an ongoing challenge for AI and information security teams. Full visibility into user activities is critical to ensuring compliance with company, industry, and government rules. Technical controls that monitor the data flowing into and out of the AI-dependent tools and provide full observability across those tools at the system level are the other key components that form a secure and compliant digital infrastructure.
Train Your Team
Organizational resilience in the face of novel threats aimed at AI tools can only be accomplished by ensuring every model user understands the reasoning and regulations behind the company policies related to AI. Users must also have a practical understanding of what is acceptable to include in a prompt and when to question the content returned in a response.
Because the threats continue to evolve in terms of tactics, format, and severity, employee education and training cannot be a one-and-done event. It must be on-going, continually updated, tailored to the audience, and part of a larger organizational culture of security, continuous learning, and improvement.
The complexities of complying with emerging AI-related regulatory obligations are many, but they can be successfully managed. A dedicated, cross-functional Risk team that exercises diligence and forethought to identify exposure, understand the company’s risk tolerance, craft robust policies that support company values, deploy stringent controls, and prioritize continual staff training can be the difference between being an organization that is secure in its knowledge that it has met its due diligence requirements and one that is lost in the labyrinth, but doesn’t realize it.
Having the right team in place is critical. However, having the best tools in place is also a key element to achieving compliance and security without sacrificing productivity or efficiency.
CalypsoAI’s model-agnostic GenAI security and enablement platform provides a comprehensive suite of customizable protections across the enterprise. Our platform is the only solution on the market that can provide a secure, resilient environment where other AI compliance support and security defenses fall short. Policy-based access controls allow administrators the discretion to grant or deny teams and/or individuals access to models and specify the level of sensitivity each scanner should apply to model interactions with that team or individual. These controls also allow usage costs and traffic density to be monitored and managed via rate limits.
Every interaction with each model is retained in a detailed prompt history, meaning administrators can see who is doing what, how often, and on which models. This feature provides administrators with both wide and deep user and system insights, and an interactive dashboard enables comparative and analytic data and full auditability and attribution around activity, content, and resource allocation.
Automated, customizable scanners review and filter every user prompt and every model response for sensitive and personal data, toxic or biased content and content that otherwise does not meet acceptable use policies, as well as source code, prompt injections, and exploitable, malicious, or otherwise suspicious content; adverse content is blocked from leaving or entering the system.
As a scalable and “weightless” trust layer in the security infrastructure, CalypsoAI enables full observability across all models in use with no introduced latency issues. Administrators can see in real time when content that can lead to incidents of non-compliance, or worse, is appearing in the system.
Organizations that acknowledge and prepare to face existing and emerging threats are going to be better able to defend against and respond to them when—not if—they occur. Making robust safeguards and proactive strategies part of the organizational compliance and security infrastructure is not just good policy, it’s good business.
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