Rich Vibert is the CEO and cofounder of Metomic, a modern, human-centric DLP solution for SaaS and GenAI tools. getty AI agents seamlessly handling workflows, automating tasks and driving unprecedented productivity across organizations isn't just the future—it’s happening now. But here’s the catch: these agents, while powerful, come with risks that could cost your business dearly if left unchecked. Unlike generative AI, which focuses on content creation, AI agents go further. They make decisions, execute workflows and integrate with external tools autonomously. However, as organizations increasingly rely on AI agents to process vast amounts of sensitive data, they also open themselves to vulnerabilities. In this article, I’ll explore three critical dangers associated with AI agents and outline strategies to help businesses mitigate these risks while unlocking their full potential. Opening The Door To Unauthorized Data Sharing And Security BreachesHere’s a chilling thought: an AI agent, designed to streamline workflows, accidentally shares sensitive information with the wrong people. It’s not intentional, but without stringent safeguards, this can and does happen. AI agents operate autonomously, often without human oversight, making the risks of unauthorized data sharing and security breaches higher than ever before. The numbers speak volumes. A 2024 Verizon study found that 68% of data breaches involved internal actors, and AI agents could amplify these risks by unintentionally escalating insider threats. For instance, an agent summarizing project updates might include sensitive data in its output and send it to unintended recipients. Even worse, attackers can exploit large language model (LLM) vulnerabilities through methods like prompt injection, tricking systems into revealing confidential information. To address this, extending role-based access controls (RBAC) to AI agents is a must, limiting their ability to access and share data. AI-specific detection tools can flag unusual activity in real time, while robust tracking and auditing systems provide accountability by logging agent activity. These measures don’t just safeguard sensitive data—they help build a security-first foundation for your AI systems. The Risks Of Data Overexposure And Misuse AI agents need data to thrive, but too much access can be a double-edged sword. The problem is that LLMs lack built-in permissions for user roles, meaning they often index and process data without understanding who should or shouldn’t access it. This can lead to sensitive information—like financial records—being exposed unintentionally. Take collaborative platforms like Slack, Google Drive and CRMs; a study by my company, Metomic, revealed that 86% of files in shared environments hadn’t been updated in 90 days, 70% in over a year and 48% in more than two years. Stale data like this creates a breeding ground for inadvertent exposure. To fix this, organizations must classify and manage sensitive data across their environments, restricting AI agents’ access to only what’s necessary. Regular audits to remove outdated files are crucial for reducing risks. By setting precise access permissions at the AI layer, businesses can ensure agents only interact with appropriate datasets—minimizing the chance of misuse while safeguarding sensitive information. Potential Regulatory And Ethical Challenges As powerful as AI agents are, they don’t always play well with regulatory frameworks. Privacy laws like GDPR, CCPA and HIPAA demand strict controls over how data is accessed, processed and stored. But LLMs, which index vast amounts of data without user-specific permissions, can inadvertently breach these regulations. The consequences of breaches are well-documented and can come in the form of costly fines, reputational damage and loss of trust. For instance, an AI agent might unknowingly include personal customer data in a report, violating GDPR rules. According to a Salesforce report, 58% of UK customers say greater transparency in how companies use AI would deepen their trust in the technology. Mishandling AI agents doesn’t just invite legal trouble—it undermines your credibility with customers and stakeholders. To mitigate these risks, businesses must implement AI governance frameworks that map sensitive data, audit AI outputs for compliance and educate teams on best practices. Transparency is non-negotiable—organizations must clearly communicate how their AI systems process data to build trust and demonstrate ethical integrity. These measures not only protect businesses from regulatory penalties but also strengthen their reputation in an increasingly AI-driven world. Bridging AI Capabilities And Security Gaps The critical challenge businesses face when it comes to leveraging AI agents is visibility and control over sensitive data. Businesses must ensure AI agents access the right data while staying clear of sensitive or restricted information. Yet LLMs, with their inherent lack of role-based permissions, make this a daunting task. To manage this effectively, they need to ensure they have the right tools and processes in place so they can map and classify sensitive data across SaaS platforms to ensure it is handled appropriately. Aligning AI agent access with organizational permissions will also help ensure that they only interact with datasets necessary for specific tasks. Lastly, businesses should aim to reduce their threat surface as much as possible by regularly cleaning and organizing data to minimize their sensitive data footprint and therefore reduce the risk of inadvertent exposure. Striking The Balance Between Productivity And Security AI agents are going to be a paradigm shift in terms of how work gets done. While they have the power to revolutionize business operations, their implementation requires strong safeguards. Organizations need to find the right balance between fostering innovation and safeguarding sensitive data, ensuring their AI systems are secure, ethical and compliant. Only then can they unlock the full potential of AI agents, safely and securely. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? {Categories} _Category: Takes{/Categories} {URL}https://www.forbes.com/councils/forbestechcouncil/2024/12/23/think-ai-agents-are-safe-these-3-risks-could-put-your-business-in-jeopardy/{/URL} {Author}Rich Vibert, Forbes Councils Member{/Author} {Image}https://imageio.forbes.com/specials-images/imageserve/6765abd05ec4425200417e74/0x0.jpg?format=jpg&height=600&width=1200&fit=bounds{/Image} {Keywords}Innovation,/innovation,Innovation,/innovation,technology,standard{/Keywords} {Source}POV{/Source} {Thumb}{/Thumb}