Managing AI Risks: Strategies for Innovation and Security Part 2 with Alec Crawford

Ignoring generative AI isn’t an option—but in high-risk environments, a simple ChatGPT subscription won’t cut it. True enterprise adoption demands security, governance, and a platform built for compliance. In this episode of Innovation Tales, we welcome back Alec Crawford, founder of Artificial Intelligence Risk, Inc., for part two of our conversation on AI security. This time, we dive deeper into how businesses can deploy AI safely, from on-premise security to multi-tiered authorization and real-time compliance monitoring.

Key Takeaways

• AI Security and Governance Are Non-Negotiable – Enterprises handling high-risk AI applications (such as in healthcare and finance) must implement on-premise or private cloud solutions, enforce role-based access, and utilize encryption and activity logging to ensure compliance with strict regulatory requirements.
• AI Regulations Are Complex and Evolving – From HIPAA in healthcare to state-specific AI laws like Colorado’s AI Act, businesses must navigate a patchwork of AI regulations. The NIST AI Risk Management Framework is emerging as a widely accepted compliance standard that simplifies regulatory alignment.
• AI’s Ethical and Global Impact Matters – Beyond compliance, organizations must address AI’s broader societal implications, including job displacement and economic divides between wealthy and developing nations. The Global AI Ethics Institute plays a key role in shaping discussions around ethical AI governance and responsible innovation.