Who are public agents and how they fuel the AI boom

Understanding Public Agents

Public agents are emerging as a significant development in the evolution of artificial intelligence. Unlike traditional AI systems that primarily respond to queries, public agents can monitor data, follow instructions, and perform tasks within a specific environment. This shift marks a crucial step in transforming AI from a tool for information retrieval into a system capable of executing work.

This transition is not just about capability; it's also about how AI products are designed and marketed. As platforms integrate models with real-time data and user permissions, the next phase of the AI boom may focus more on automation that feels useful, visible, and controllable.

What Are Public Agents?

Public agents are AI-powered systems that go beyond text generation. These software agents can monitor conditions, follow rules, and take approved actions on behalf of users. This distinguishes them from simple chatbots, which only react to prompts in the moment. Instead, agents can continue working after the initial prompt is given.

This distinction is gaining importance across the tech industry. Agentic AI is characterized by multi-step actions, the use of tools, and autonomy within defined boundaries. The commercial value becomes evident when AI starts doing work rather than merely explaining it.

Public.com and AI Agents in Investing

Public.com is showcasing how AI agents can be practical tools in investing. Rather than requiring users to create complex rules from scratch, the platform allows users to describe their goals in natural language. This input is then translated into a setup that can track markets, manage account actions, and place trades based on specific conditions.

What makes this approach notable is its integration into the platform itself. These agents operate within Public’s brokerage environment, using real-time data and providing clear activity logs. Users have control over the agents, allowing them to approve, modify, pause, or stop them at any time. This makes the experience feel more like an actual product rather than a demo.

The Potential Impact on the AI Boom

The AI boom has been driven by factors such as chips, cloud spending, and large language models. However, agents could introduce a new layer of demand. They require more than just access to models; they need orchestration, live data, evaluation tools, security controls, and multiple model steps to complete tasks.

There is growing evidence that businesses are taking AI agents seriously. According to McKinsey, 62% of surveyed organizations are experimenting with AI agents, while 23% are scaling agentic AI systems. PwC reports even higher enthusiasm, with 79% of companies adopting AI agents and 88% planning to increase AI-related budgets due to agentic AI. If this momentum continues, agents could become a key driver of sustained AI spending.

Early Winners in the AI Agent Space

The first winners in the AI agent space are unlikely to be the most flashy products. Instead, they will likely be those that save time, reduce friction, and operate within environments where actions can be measured. Industries such as finance, customer support, internal operations, research, and software workflows are strong early candidates.

Investing, for example, is a rules-heavy environment with real-time signals and clear outcomes. This makes it an ideal testing ground for agentic software. If Public Agents demonstrate that users are comfortable delegating specific actions to AI in a high-trust setting, it could pave the way for similar models in other industries.

Challenges and Considerations

Not all agent projects will succeed. Gartner has warned that over 40% of agentic AI projects could be scrapped by the end of 2027 due to cost and unclear business value. This highlights the gap between impressive demos and dependable products.

Control, safety, and transparency will be critical in determining the success of AI agents. Platforms that provide clear visibility into what agents are doing, keep humans in charge, and minimize mistakes in sensitive environments are more likely to win. The future of public agents may depend on their ability to perform specific tasks well, safely, and clearly enough for people to trust them.

The Future of AI Agents

Public agents are still in the early stages, but they reflect the direction in which AI is heading. The next phase of the AI boom may not be defined by who has the most advanced models, but by who can turn AI into reliable action within real products.

Public.com’s approach offers a glimpse into how agentic AI could become easier to use, monitor, and trust. If more companies can make agents feel practical, the AI boom could shift from fascination to durable adoption.