What Is Robotic Process Automation (RPA)? Definition, use cases, and leading tools

Definition

Robotic Process Automation (RPA) is a technology that uses software robots (bots) to automate repetitive, rule-based tasks that were previously performed by humans interacting with computer applications. RPA bots mimic human actions such as clicking buttons, entering data into fields, copying values between applications, reading screen content, and navigating menus. Unlike traditional integration, RPA operates at the user interface level, which allows it to work with legacy applications that lack APIs.

RPA was first commercialized in the early 2010s by vendors including Blue Prism (founded 2001, coined the term "RPA"), Automation Anywhere (founded 2003), and UiPath (founded 2005). The technology gained rapid enterprise adoption between 2017 and 2022, driven by the need to automate back-office processes without modifying existing IT systems.

How RPA Works

An RPA bot executes a predefined sequence of steps against application interfaces:

1. Recording or scripting: A developer records interactions with applications (clicks, keystrokes, data entry) or scripts the steps using the RPA platform's development environment.
2. Object recognition: The bot identifies UI elements (buttons, text fields, dropdown menus) using selectors, coordinates, image recognition, or a combination of methods.
3. Execution: The bot replays the recorded actions, reading data from one application and entering it into another, following conditional logic where defined.
4. Orchestration: A central server schedules bot execution, manages bot licenses, distributes work across available bots, and monitors execution status.

Attended vs Unattended RPA

Leading RPA Platforms (as of March 2026)

Industry Adoption and Market Size

According to Gartner, the global RPA market reached approximately $3.4 billion in revenue in 2025, with projected growth to $4.1 billion in 2026. Adoption is highest in financial services (85% of large banks use RPA), insurance (78%), healthcare revenue cycle (65%), and manufacturing (55%). The average enterprise RPA deployment includes 30-50 bots, with large-scale deployments exceeding 500 bots.

However, RPA adoption has slowed compared to 2019-2022 growth rates. The primary factors are:

• API-based integration platforms (iPaaS) handling many use cases that previously required RPA
• AI-powered document processing reducing the need for screen-scraping bots
• Vendor consolidation (Blue Prism acquired by SS&C, numerous smaller vendors absorbed)
• "Bot maintenance burden" where organizations find that 20-30% of bot time is spent on maintenance rather than productive automation

Limitations of RPA

• UI dependency: Bots break when application interfaces change (button moves, field renamed, page redesigned). This creates ongoing maintenance requirements.
• Scalability constraints: Each unattended bot typically requires a dedicated virtual machine or runtime license, making large-scale deployments expensive.
• Limited decision-making: Traditional RPA follows explicit rules. Tasks requiring judgment, interpretation of unstructured data, or context-dependent decisions require AI augmentation (Intelligent Automation).
• Not a substitute for integration: When both source and target applications offer APIs, direct API integration is faster, more reliable, and cheaper than RPA.

RPA vs API Integration vs iPaaS