CISOs are now considered part of the organizational executive leadership and have both the responsibility and the opportunity to drive not just security but business success.
Navigating the AI Revolution: The CISO’s Crucial Role
In the midst of the artificial intelligence (AI) era, forward-thinking organizations are harnessing its transformative power to revolutionize their operations. As AI adoption gains momentum, Chief Information Security Officers (CISOs) play a vital role in ensuring a secure and successful implementation. To thrive as business enablers, CISOs must understand the priorities, tasks, and challenges associated with AI integration.
Introducing: The AI Committee
An AI committee, sometimes referred to as the AI governance committee, is a group within an enterprise, responsible for overseeing the safety, legal, and security implications of that organization’s AI use. Its main purpose is to ensure that AI technologies are developed, deployed, and used to boost business benefits like streamlined productivity, while making sure the organization considers the risks inherent in this use and takes active measures to safeguard the company’s assets, customers, brand, and reputation accordingly.
Who Sits on an AI Committee?
The AI committee ideally represents a diverse group of internal and external organizational stakeholders, including:
- Executive leadership: Representatives from senior management or executive leadership, such as the CEO, CIO, or CTO, who provide strategic direction and support for AI initiatives.
- General counsel: Legal counsel or compliance officers who advise on regulatory requirements, legal risks, and contractual obligations related to AI technologies.
- Security leadership: Specialists in data privacy, cybersecurity, and information security who ensure that AI systems adhere to privacy regulations and security best practices. (This blog post will mostly focus on the CISO persona.)
- Data scientists and AI engineers: Professionals with expertise in data science, machine learning, and AI technologies who are responsible for developing and implementing AI systems.
- External parties: External consultants, academics, or industry experts who provide independent perspectives and expertise on AI governance best practices. Other external parties can include stakeholder representatives, such as customers, partners, and advocacy groups who can provide input from the “outside” perspective.
How the CISO Can Become the AI Committee Champion
Here are three fundamentals CISOs can use as a guide to being the pivotal asset in the AI committee and ensuring its success.
1. Begin with a comprehensive assessment.
The age-old saying in security applies to AI as well — you can’t protect what you don’t know. Before you get started in building a strategy for how to secure AI use across your organization, first understand who, what, and how AI has already been adopted. An AI gap analysis will allow you to first identify all shadow AI apps and models used across the organization (without your prior knowledge or approval), including public GenAI apps, third-party large language models (LLMs) and software-as-a-service (SaaS), and internally developed models. This inventory will also give you insight into usage patterns to understand what sort of AI use is organically popular for the employees, so you focus your future security efforts where they are needed most. By the way, note that these kinds of insights are invaluable for business stakeholders as well, so use them wisely. As the CISO, remember that you hold the most valuable information on the committee — GenAI usage data from across the organization, aka ROI. Armed with data, take the lead in setting up smart, secure, and realistic GenAI policies across the org.
2. Implement a phased adoption approach.
CISOs often face the daunting challenge of balancing productivity and security. To harness the power of AI while ensuring robust security, a phased adoption approach is essential. This strategic method allows security to pace alongside adoption, assessing real-time implications and implementing parallel controls. By adopting AI in stages, CISOs can strike the perfect balance between acceleration and caution.
Phased Adoption: The Key to Secure AI Integration
Gradual Implementation: Roll out AI solutions in phases, starting with low-risk applications and gradually increasing complexity.
Real-Time Assessment: Continuously monitor and evaluate security implications, making adjustments as needed.
Parallel Security Controls: Implement security measures in tandem with AI adoption, ensuring robust protection.
Measured Success: Track the effectiveness of phased adoption, making data-driven decisions for future implementations.
Example in Action
Enterprise Chat: Introduce a chat option without integrating organizational data, testing security parameters before expanding.
LLMs: Trial Large Language Models that don’t learn from your data, ensuring secure AI interactions.
The Result
By adopting a phased approach, CISOs can:
Accelerate AI Adoption: Harness the power of AI while maintaining security vigilance.
Keep Security in the Fast Lane: Implement robust controls, ensuring protection without hindering progress.
Steer AI Integration: Make informed decisions, navigating the journey with confidence.
Best Practices for Phased AI Adoption
Assess Risk: Evaluate potential risks and prioritize security accordingly.
Collaborate: Engage stakeholders, ensuring alignment and effective implementation.
Monitor and Adapt: Continuously assess and refine security measures.
3. Be the YES! guy — but with guardrails.
Guardrails are a common security practice that enables security to engage controls for secure development, without slowing things down. How can CISOs adapt these same principles to the new GenAI frontier? The most common use case we see today is through contextual or prompt guardrails. LLMs have the capacity to generate text that may be harmful or illegal, or that violates internal company policies (or all three). To protect against such harmful threats, CISOs should set up content-based guardrails to define and then alert on prompts that are risky or malicious, or that violate compliance standards. Cutting-edge, AI-focused security solutions may also allow customers to set up and define their own unique parameters of safe prompts, and alert to and prevent prompts that fall outside of these guardrails.