AI is transforming how organizations create, manage and use data. Powerful additions to enterprise IT environments include generative AI (GenAI) tools, such as ChatGPT, and enterprise copilots. Workers might also use “”shadow AI”” tools that haven’t been vetted or approved by IT teams. What’s more, the rapid emergence of AI agents is giving rise to a new, agentic workspace, where both humans and agents interact with sensitive data.
In this complex new landscape, unsecure or ungoverned AI use can easily expose sensitive information. According to IBM, the average cost of a data breach neared $4.5 million in 2025. And regulatory consequences continue to grow. Organizations must proactively prevent AI-driven data loss before it leads to a costly and damaging business crisis.
Our guide to Securing and Governing AI in the Modern Enterprise gives you the insights and strategies you need to stay ahead.
In this timely guide, you’ll discover:
- The top data security risks introduced by GenAI, enterprise copilots and agentic AI
- How weak AI security governance opens the door to AI-driven data loss
- A framework for robust AI security governance, including roles, policies and technology-driven enforcement
- Practical techniques to secure both AI applications and the data they use
Download the guide now and start building a resilient foundation for AI adoption.