Hyperautomation

Hyperautomation is a business strategy that seeks to rapidly identify and automate as many business and IT processes as possible using a combination of automation technologies. It extends beyond single-task automation by aiming for end-to-end process automation across organizational silos. The term was popularized by Gartner in 2019 to describe this broad approach.

Key technologies commonly involved include robotic process automation (RPA), artificial intelligence and machine learning, process mining, workflow and business process management (BPM) suites, analytics, and integration platforms. Organizations typically begin with process discovery and mapping, often using process mining, to locate high-value automation opportunities, then assemble an automation platform or "automation factory" to design, test, deploy, and monitor bots and AI components.

A core aspect is governance and change management, with a center of excellence coordinating standards, security, data privacy, and performance measurement. Hyperautomation emphasizes end-to-end workflow orchestration, human–machine collaboration, and continuous improvement rather than isolated task automation.

Benefits often include higher productivity, faster cycle times, greater accuracy, improved compliance and auditability, and potential cost savings. Risks include over-automation, security and data privacy concerns, integration complexity, vendor lock-in, and workforce disruption. Successful programs require skilled staff, robust data governance, and clear ROI tracking.

Adoption spans financial services, healthcare, manufacturing, telecommunications, and government, among others. Metrics commonly tracked include automation coverage, ROI, cycle-time reduction, defect rates, and automation velocity. Hyperautomation is viewed as a component of broader digital transformation and intelligent automation initiatives, with ongoing evolution as AI and process-mining capabilities mature.