After building the privacy and cybersecurity programs at Hulu and serving as Nike's Chief Privacy Officer, I've seen firsthand that the greatest barriers to effective technology governance aren't technical—they're human and organizational. Tools that help people work together to manage risk while approving AI systems can serve your company immediately, while building the foundation for automating approval processes in the future.
Let me share five challenges that make AI risk management ripe for automation:
"When there are many owners, there are no owners." This old management wisdom perfectly describes the AI risk management challenge. Responsibility is fragmented across legal, compliance, data science, tech, and audit teams, resulting in unclear accountability.
The problem gets worse with "shadow AI" initiatives—when teams activate AI features without detection or proper risk assessment. Without clear ownership, governance becomes inconsistent and ineffective.
I've witnessed this scenario countless times: data science teams feel trapped in endless review cycles with legal that slow speed to innovate and adopt emerging technology. Meanwhile, lawyers attempt to manage risks without adequate technical expertise, all while executives demand faster AI deployment to remain competitive.
This tension between rapid technology adoption and governance can undermine cross-team collaboration and slow important initiatives.
For multinational companies, impact assessments become a brutal compromise—documentation that's too detailed for some jurisdictions while insufficient for others.
The reality? No in-house lawyer masters all AI regulations spanning contract law, IP, cybersecurity, privacy, and anti-discrimination frameworks. The documentation burden alone can paralyze AI initiatives.
Standard model and data testing tools can create damaging evidence if problems are discovered. Without privileged platforms, many organizations avoid thorough testing altogether—creating dangerous blind spots and potential liability.
This creates the worst of both worlds: either avoid testing (and miss problems) or test thoroughly (and create potential evidence of issues).
As your business adopts AI across more departments and use cases, manual governance processes simply cannot keep pace. When AI technology is automating business operations, why are we still using spreadsheets and emails to manage AI risks?
Our platform was built to address each of these challenges through automation:
While US federal AI regulation continues to evolve, DOJ rules regarding AI and China already create significant obligations for multinationals, and the EU AI Act is coming into effect over the next 3 years. State-level requirements like the Colorado and Utah AI Acts and existing anti-discrimination laws already apply to algorithms today—companies simply can't afford to wait for AI-specific regulations. And they won't wait long, with over 40 states introducing laws impacting AI in 2024.
The organizations that thrive in the AI era won't just have advanced AI technologies but balanced, automated governance that scales with innovation.
To learn more about how Luminos can help establish scalable AI risk management at your company, contact anne@luminos.ai.
