Growth of AI agents in corporate software drives automation and redefines professional roles

The presence of AI agents in business software is expected to grow rapidly in the coming months. Gartner predicts that by the end of 2026, 40% of enterprise applications will have AI agents capable of performing specific tasks. In 2025, this figure was estimated to be less than 5%.

This shift represents a significant advancement over traditional AI assistants, which typically rely on human commands to answer questions, generate text, or analyze data. AI agents can receive a task, make decisions within predefined rules, and execute process steps autonomously.

This growth doesn’t mean professionals will stop using applications. Gartner’s forecast suggests that some tasks will be performed by the software itself, while employees will take on roles focused on guidance, supervision, and validation.

What are AI agents?

An AI agent is a system capable of performing a task or a sequence of tasks with a degree of autonomy. Unlike a conventional chatbot, which typically responds to a request, an agent can plan steps and execute actions within a digital environment.

For example, an agent integrated into a customer service system could, instead of just suggesting a response for an employee, consult the customer’s history, identify the problem, verify information in other systems, and forward a solution following rules defined by the company.

Gartner distinguishes these agents from assistants embedded in applications. The company views assistants as an earlier stage, as they depend more directly on human interaction. Task-specific agents, on the other hand, can execute end-to-end processes.

How AI can transform work applications

The integration of agents can change how professionals use management, customer service, sales, human resources, and other software.

Currently, a task may require an employee to open different systems, copy information, perform an analysis, and record the result. With an agent connected to the necessary systems, some of these steps can be automated.

Gartner also predicts an evolution toward collaborative agents. By 2027, one-third of agentic AI implementations may combine agents with different skills to handle more complex tasks.

Companies are already expanding the use of AI agents

Gartner’s forecast comes in a context of technology expansion. A 2025 study by the IBM Institute for Business Value, conducted with 2,000 CEOs, found that 61% of executives interviewed said they were adopting AI agents and preparing to implement them on a large scale.

Microsoft’s data also indicates growth in usage. The 2026 Work Trend Index, based on productivity signals from Microsoft 365 and a survey of 20,000 workers using AI in ten countries, recorded a 15-fold increase in the number of active agents in the Microsoft 365 ecosystem over one year.

In the corporate environment, the discussion is therefore beginning to shift. Instead of asking only which AI tools an employee can use, companies are now evaluating which processes can be executed by agents.

Challenges and risks of adopting autonomous agents

Adoption also creates new risks. An agent with access to corporate systems can perform actions that affect data, customers, or internal processes. Therefore, permissions, supervision, and traceability become critical elements.

Gartner itself predicts that 40% of companies may downgrade or disable autonomous agents by 2027 due to governance failures identified after incidents.

Another critical issue is integration. To function properly, an agent needs to access reliable data and compatible systems. Without this infrastructure, automation can only accelerate poorly defined processes.

For professionals, this means that knowledge about working with AI will likely involve more than just knowing how to write good commands. It will also involve understanding which tasks can be automated, how to validate results, and which decisions still require human supervision.

Gartner projects that by 2029, at least half of knowledge workers will develop new skills to work with, govern, or create AI agents on demand.

The expansion of agents could also transform the software market. Another Gartner projection estimates that up to $234 billion in spending on enterprise applications will be exposed to the impact of agentic AI by 2030, as agents begin to execute tasks across different systems.

For professionals, the most immediate change is in how they interact with tools. Software is no longer just an environment where users perform each step manually; in some cases, it now executes part of the requested work. The speed of this transformation will depend on the integration of agents into systems, the quality of data, and the rules established by companies.