Generative AI holds immense promise for transforming businesses, but with that promise comes significant security and governance challenges. In a recent webcast for DM Radio, Oz Wasserman, co-founder of Opsin Security, sat down with Eric Kavanagh to break down how organizations can safely navigate this evolving landscape. From the power of RAG (retrieval-augmented generation) models to the importance of dynamic policy management, Oz shared actionable insights on how companies can stay ahead of the curve when integrating AI into their operations.
“How do you ensure appropriate data is shared?” Oz asked early in the conversation, underscoring a critical question facing every organization embracing AI. Generative AI introduces innovative capabilities, but without the right governance and security practices, organizations risk exposing sensitive data. The conversation centered on how RAG models bridge the gap by securely connecting AI systems to real-time data within the organization. “RAG models allow you to connect data easily,” Oz explained, emphasizing their role in unlocking the full potential of generative AI while maintaining data security.
One of the key points Oz highlighted was the critical need for security orchestration—managing who gets access to what data at the right time. Whether it’s in financial reporting or HR applications, orchestrating security policies dynamically ensures that organizations can leverage AI for productivity while staying compliant with ever-evolving regulations. “This technology enables a lot of innovation," Oz noted, "but only when proper governance and controls are in place.”
The discussion also touched on AI’s ability to reduce manual work and improve operational efficiency, specifically highlighting a customer of Opsin who deployed their solution in the financial reporting space. By automating time-consuming tasks like profit and loss reporting and reconciliation, this customer saw a significant reduction in manual effort, freeing up teams to focus on more strategic work. “Generative AI can cut down days of effort," Oz noted, "and that’s the kind of productivity gain organizations need today.” And while speed is important, so is trust: Oz spoke about the growing need for citation capabilities in AI responses, which help improve accuracy and boost confidence in AI-generated content.
As companies continue to adopt generative AI, Oz stressed that dynamic policy management is key to success. Flexibility in access control, combined with strong governance, ensures that businesses can adapt to new use cases while keeping their data secure. “Organizations must continuously adapt to changing regulations,” Oz warned, emphasizing the importance of proactive governance.
From HR applications to financial co-pilots, AI is already enhancing productivity across sectors. But as Oz concluded, the future of AI will require ongoing collaboration between data governance teams, AI engineers, and security professionals to ensure safe, compliant, and effective AI deployment.
Ready to dive into the full discussion? Watch the webcast at the top of this page.
