Securing the Future: Navigating the New AI-Driven Security Landscape

The rise of AI is undeniable, but it's not without its challenges. As companies embrace the incredible productivity gains of AI-powered tools, a new and complex security landscape is emerging. We recently analyzed a survey of over 200 North American security leaders to understand how they're grappling with these changes. The results reveal a stark reality: security teams know the risks are multiplying, but they feel under-equipped to handle them.

Dave Lewis, Global Advisory Chief Information Security Officer at 1Password, has eloquently put it, "We have closed the door to AI tools and projects, but they keep coming through the window!" This sentiment perfectly captures the core issue: the rapid adoption of AI is outpacing our ability to secure it.

Here’s a look at the four biggest challenges facing security leaders today, and what you can do about them.

Challenge 1: The AI Visibility Gap

Only 21% of security leaders report having full visibility into the AI tools being used within their organizations. This lack of oversight is a serious problem. Employees, in their quest for efficiency, are often using unsanctioned AI tools, which can expose corporate data to public Large Language Models (LLMs). This creates a significant "Access-Trust Gap" where security teams can't mitigate risks they can't even see.

How to Fix It: To regain visibility, it’s crucial to understand how employees are actually using AI. Use tools for SaaS governance and device trust to identify unsanctioned usage and update your policies accordingly.

Challenge 2: The Enforcement Problem

Policies are in place, but enforcement is weak. Our survey found that 54% of security leaders believe their AI governance is weak, and they estimate that up to half of employees are still using unauthorized AI apps. The rapid pace of adoption means that even the best policies can become ineffective if they can't be enforced.

How to Fix It: Effective governance starts with collaboration. Work with business and legal partners to assess AI usage and define clear enforcement actions, from monitoring to blocking, to enable secure and responsible AI adoption.

Challenge 3: Unintentional Data Exposure

The biggest internal threat, according to 63% of security leaders, is employees unknowingly giving sensitive data to AI tools. This isn’t a malicious act; it's a gap in awareness. When corporate data is used to train public LLMs, companies risk losing control of that data and violating compliance standards.

How to Fix It: Create a clear, organization-wide framework for secure data usage with AI. Treat data shared with an unverified AI tool as if it were posted on social media. Implement training programs to help employees recognize the risks and design user-friendly guardrails that protect data without hindering productivity.

Challenge 4: Unmanaged AI Tools and Agents

Over half of security leaders estimate that up to 50% of their AI tools and agents are unmanaged. This is a huge problem. Many AI apps and agents are interacting with business systems without proper identity or access governance. This creates a compliance and security nightmare, as it's nearly impossible to audit their actions or revoke access when needed.

How to Fix It: You need to evolve your access governance strategy to include AI agents. Create clear guidelines for how AI tools are provisioned, tracked, and managed. This will ensure you can audit their actions to meet compliance requirements and maintain control over your systems.

The Path Forward: Enabling, Not Blocking, AI

The research makes one thing clear: security leaders are aware of the risks but need better tools to address them. The answer isn't to shut the door on AI; it's to build a security strategy that can keep pace with it. By improving visibility, strengthening governance, and extending access management to cover AI agents, you can enable your teams to get the benefits of AI productivity with minimal risk.

It's time to stop playing catch-up and start building security strategies that empower both humans and machines to work confidently and securely.