ChatGPT Agents Push AI Boundaries—But at What Cost to Security?

OpenAI recently launched a new feature that’s shifting how we interact with artificial intelligence: the ChatGPT Agent. This powerful tool represents a leap beyond traditional chatbots, introducing the potential for AI-driven personal assistants that don’t just talk—they act.

“This isn’t just another chatbot. It’s an AI that takes real actions. It can book flights with your credit card. It can read your confidential files and make decisions without asking permission,” says Jon Nordmark, CEO of Iterate.ai.

The agent model promises convenience and automation on a new scale. Unlike legacy chat interfaces, which offer information and generate text-based responses, these new AI agents can perform real-world tasks—like managing calendars, sending emails, retrieving documents, and even making purchases. They do all this by using tools, memory, and plug-ins that allow them to execute commands independently.

The upgrade is part of a broader push in the AI world to make large language models (LLMs) not just conversational tools, but autonomous assistants that learn, adapt, and act over time. But as this shift unfolds, so too do significant concerns around security, privacy, and infrastructure vulnerability.

Nordmark cautions that this development, while impressive, is not without major risk.

“Agents built by all big public LLM builders—OpenAI (ChatGPT), Google (Gemini), Anthropic (Claude), DeepSeek (China), Manus (China)—all run on a massive cloud platform. Each request (i.e. prompt) is processed across hundreds (or thousands) of GPUs or TPUs to support tools, memory, and real-time actions,” he explains.

This architecture, while necessary for the scale and complexity of AI agents, also creates a shared environment that could expose sensitive data across platforms. Every prompt, every action, every file accessed by an AI agent travels through these high-powered but centralized systems.

“When agents live on shared infrastructure, one weak link becomes everyone’s risk,” Nordmark warns.

In other words, if an AI agent can access confidential business documents or execute financial transactions on your behalf, the underlying infrastructure must be airtight. A single misconfiguration, API flaw, or overlooked vulnerability could lead to a domino effect, compromising not just individual users, but potentially millions of accounts and companies all at once.

These risks aren’t just theoretical. AI agents are already raising new questions about consent, memory, and transparency. If an AI assistant can remember personal details, including medical history or private messages, does the user have visibility or control over what’s being remembered, or who can access that data?

As AI agents begin to make decisions autonomously, the accountability gap becomes harder to close. If an AI agent schedules a meeting with a competitor, sends an unauthorized payment, or pulls sensitive internal documents into a workflow, who is responsible—the developer, the platform, or the user?

For businesses, the stakes are even higher. While some companies are eager to adopt AI agents for increased efficiency, many remain hesitant. Enterprise systems often contain trade secrets, confidential client data, and financial records—making any breach of access potentially catastrophic.

Still, the innovation is impossible to ignore. AI agents could redefine productivity by taking over routine tasks, surfacing key information instantly, and personalizing workflows at scale. But this future hinges on solving a paradox: the more powerful these agents become, the more trust they require, and the more damage they can do if that trust is misplaced.

Industry leaders and policymakers alike are now grappling with how to regulate and secure these tools. Some experts are calling for stricter controls over agent access to personal files and financial systems, while others are pushing for full transparency in how agents store and recall user data.

In the meantime, Nordmark’s advice is clear: be aware of what these tools can do—and what they can see.

As AI agents like ChatGPT continue to evolve, users, whether individuals or enterprise clients, must weigh the extraordinary potential of AI-driven action against the very real security challenges that come with giving machines the keys to the digital kingdom.