Agentic AI is accelerating task automation through systems such as Athena from Athena Intelligence and Devin from Cognition. In April 2025, Anthropic’s chief information security officer stated that AI-powered ‘virtual employees’ could begin appearing on corporate networks within about a year — a prospect that raises major questions about digital identity, access control, and accountability. But what are these virtual employees and what are they capable of?

Several times in our past there have been fundamental shifts in the way humans work. The first was when we graduated from hunting and gathering to farming with the advent of agriculture. The transition to agriculture dramatically increased productive capacity and reshaped how most societies organized labor.

The next big shift was much more recent in history: the Industrial Revolution. Again, increased productivity allowed a huge boom in population. By the early 19th century, around the same period industrialization accelerated, world population crossed roughly one billion for the first time. Even more recently, the Information Revolution, starting with the development of the transistor at Bell Labs in 1947, changed how we work at every level. Now we are going through a revolution in intelligence. With artificial intelligence, we are changing how we think, and more specifically, how we approach thought work. We are already seeing the effects on knowledge work—but how far will this shift go?

What Is Agentic AI?

To understand virtual employees, we first need to understand the concept of agentic AI. Traditional AI tools respond to prompts. You ask a question, the system provides an answer. Agentic AI goes further. It can plan, reason, use tools, execute multi-step workflows, and autonomously pursue goals with minimal human oversight. Instead of acting as a lookup tool, agentic AI acts as a collaborator. It can take initiative, adapt to changing conditions, and handle the kind of complex, context-dependent tasks that previously required human judgment.

This shift from reactive to proactive AI is what makes virtual employees possible. When an AI system can browse the web, write and execute code, manage files, communicate via email, and chain these capabilities together toward a broader goal, it stops being a tool and starts resembling a worker.

Devin: The AI Software Engineer

When Cognition introduced Devin in March 2024, it positioned the product as the world’s first AI software engineer. At launch, Devin’s significance was not just coding assistance, but its ability to plan, test, debug, and iterate across an end-to-end engineering task. Unlike AI coding assistants such as GitHub Copilot, which help programmers write code faster, Devin can tackle entire software projects from start to finish. Given a task description, Devin plans the approach, writes the code, tests it, debugs failures, and iterates until the job is done. It operates inside its own sandboxed development environment, complete with a shell, browser, and code editor.

Cognition demonstrated Devin completing real freelance software engineering tasks sourced from Upwork, fixing bugs in open-source repositories, and even training and deploying small AI models. In internal benchmarking on the SWE-bench dataset, which tests the ability to resolve real GitHub issues, Devin resolved 13.86% of issues unassisted, compared to 1.96% for the previous best AI model. That may sound modest, but it represented a seismic leap in autonomous capability.

Since launch, Devin has evolved from a headline-making prototype into a broader engineering workflow platform. Devin 2.0 added an agent-native IDE, parallel Devins, Interactive Planning, Devin Search, and Devin Wiki; more recent releases added managed Devins, scheduled sessions, stronger review workflows, and richer enterprise controls.

What makes Devin significant is not just its technical performance, but what it represents architecturally. It is not just a single model generating code, but rather a system that orchestrates planning, tool use, memory, and self-correction over an extended period. In other words, it works the way an engineer works: imperfectly, iteratively, and persistently.

Athena: The AI Knowledge Worker

While Devin targets software development, Athena Intelligence is building virtual employees for a broader class of knowledge work. Athena is designed to function as an AI analyst and researcher, capable of consuming large volumes of information, synthesizing insights, producing reports, and executing research workflows at a speed and scale that would be impossible for human teams alone.

In practice, that can include automating recurring research and reporting tasks such as downloading financial filings, summarizing legal documents, or generating competitive intelligence updates.

Athena is aimed at organizations that need to turn large volumes of enterprise data and documents into operational insight. Its focus is less on chat-style assistance and more on repeatable research, reporting, and analysis workflows. It specializes in tasks that require more than just information retrieval, but also synthesis, pattern recognition, and contextual reasoning. Athena aims to perform these tasks continuously, helping teams scale research, reporting, and analysis workflows more quickly and consistently.

What distinguishes Athena from a search engine or a dashboard is its capacity for goal-directed reasoning. It does not simply retrieve; it decides what information is relevant, how to frame the question, and how to present the answer in a way that drives decisions. Athena is better understood as an enterprise AI analyst / digital coworker that can execute repeatable analytical and operational workflows, especially in regulated environments where deployment controls, collaboration, and auditability matter.

What Virtual Employees Can and Cannot Do

The capabilities of today’s virtual employees are impressive but bounded. They excel at tasks that are well-defined, information-dense, and verifiable. Agentic AI can already automate or significantly augment portions of work in software engineering, research synthesis, analytics, scheduling, and document drafting—especially when tasks are well scoped and outputs are easy to verify.

However, they currently struggle with tasks requiring deep contextual judgment, genuine creativity, emotional intelligence, or physical-world interaction. Some domains are still best accomplished by human employees, such as managing a difficult client relationship, navigating organizational politics, designing an entirely novel product category, or responding to an unprecedented crisis.

There are also important questions of trust and oversight. Unlike a human employee whose motivations we broadly understand, an AI agent’s behavior must be carefully monitored, especially when it has access to sensitive systems and data. Companies deploying virtual employees must build robust safeguards — not just for the AI’s performance, but for its alignment with organizational values and legal obligations. In practice, that means defining clear permissions, approval checkpoints, and audit trails for any agent trusted with sensitive systems or decisions.

The Next Revolution Is Already Here

Each prior revolution in human work — agricultural, industrial, informational — was initially met with fear and skepticism but eventually transformed society in ways that were impossible to fully anticipate. The intelligence revolution is no different. In the near term, virtual employees like Devin and Athena will most likely function as force multipliers for human workers, handling the high-volume, time-consuming tasks that drain capacity and delay decision-making.

Over the next decade, as these systems grow more reliable and their capabilities expand, the nature of many white-collar jobs will shift fundamentally. The question will no longer be whether AI can do the work, but how humans and AI can divide it most effectively. New roles will emerge, such as AI supervisors, agent trainers, output auditors, just as new jobs emerged around machines during the Industrial Revolution.

In fifty years, historians may look back at this period the way we look at the invention of the printing press or the steam engine. Virtual employees are not a distant science fiction concept. They are here, they are improving rapidly, and they are beginning to clock in.