Hyperautomation refers to the use of advanced technologies such as artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other automation tools to automate as many business and IT processes as possible. Unlike traditional automation, which focuses on automating specific tasks, hyperautomation aims to orchestrate a combination of tools and technologies to streamline entire workflows, enhance decision-making, and integrate processes across systems.
Key elements of hyper-automation include:
- Robotic Process Automation (RPA): Automates repetitive, rules-based tasks.
- Artificial Intelligence (AI) & Machine Learning (ML): Add intelligence to processes, enabling systems to learn, adapt, and make decisions.
- Process Mining: Helps identify automation opportunities by analyzing workflows.
- Integration: Connecting different systems, tools, and processes seamlessly to create a unified automation framework.
- Analytics: provides insights into business processes to continually optimize automation.
The goal of hyperautomation is not only to enhance operational efficiency but also to enable organizations to adapt quickly to changes and innovate by leveraging technology across all functions. It’s widely used in industries such as finance, healthcare, manufacturing, and logistics for things like automating customer service, back-office tasks, and even complex decision-making processes.