3 essential steps for private equity funds to use AI securely, unlock value for LPs, and comply with SEC regulations
Avoid nasty SEC fines related to AI use with these key measures.
AI is reshaping the private equity landscape overnight. Firms are already:
Ingesting and processing 10,000 complex documents in minutes.
Reducing time spent on deal sourcing by 50%-60%.
Driving disruption across portfolios.
The value gains that can be unlocked for limited partners (LPs) and other stakeholders are clear.
But there are risks.
Cyber criminals are as aggressive and resilient as ever.
Privacy- and AI-specific regulations are expanding.
The SEC is targeting AI-related infractions.
With a balanced and comprehensive approach, though, you can manage the risks responsibly.
Three key steps for AI governance
1. Inventory your AI
The SEC recently charged two firms with “AI washing.”
More regulations are coming on AI- driven conflict of interest.
Registered investment advisor cybersecurity rules are due soon.
And you can’t address any of these challenges with out knowing what AI systems you actually use. This inventory is not just a list; it’s the foundation for understanding your exposure to regulatory and security risks. Ensure this inventory is comprehensive and includes all systems, whether in-house or from vendors.
TIP: automate inventory updates to keep pace with changes and use the CycloneDX Software Bill of Material (SBOM) format for standardization and flexibility.
2. Put a policy in place
This should be a living entity within your organization, driving daily operations and decisions rather than gathering dust.
Compliance-as-code can let your policy adapt to evolving regulations and operational changes.
When the SEC decides to do some “regulation through enforcement,” make sure to zig where others zagged.
COMMON MISTAKE: treating policy development as a one-off task. Instead, view it as an ongoing process that integrates with your operational lifecycle.
3. Get into detail with procedures
This means establishing clear:
responsibilities
deadlines
methods
for AI system management.
By providing concrete steps and expectations, you ensure that every team member knows their role in maintaining AI security and compliance.
And the SEC has shown (through $750,000 in fines) that “paper tigers” are not acceptable: you can’t just have a policy on the books with no plans to enforce it with actionable procedures.
EXAMPLE PROCEDURES:
Onboarding a new tool
Applying technical controls
Responding to a data breach
Why this framework works
Comprehensive awareness
By inventorying systems, you develop a full picture of your AI landscape, enabling targeted risk management strategies. This is the bedrock of effective AI governance, ensuring no blind spots.
Adaptive compliance
A living policy, especially when implemented as compliance-as-code, evolves with the regulatory environment and your operational needs, ensuring continuous alignment with best practices and legal requirements.
Operational Clarity
Detailed procedures translate policies into actionable steps, creating a clear roadmap. This clarity eliminates ambiguity while fostering a culture of compliance and proactive risk management.
Ready to start managing cyber and compliance risk while delivering value?
StackAware is already working with one private equity fund to securely and responsibly drive value.
Want to be next?