The global market for hyper-automation was valued at US$ 6.11 billion in 2021, and Adroit Market Research projects that it will grow by 30.6% yearly to US$ 98.6 billion by 2031.
The term “hyper-automation” refers to the use of cutting-edge technology to automate a variety of business processes and jobs above and beyond what is currently possible with standard automation. Examples of such technology include artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other automation tools. In order to increase production, efficiency, and decision-making, it strives to establish a highly automated and networked ecosystem. Hyper-automation integrates several automation technologies to automate complex operations that need cognitive ability, judgment, and decision-making in addition to repetitive and rule-based duties. Utilizing AI and ML algorithms to manage unstructured data, learn from patterns, and make intelligent judgments, goes beyond simple job automation.
To construct end-to-end automation workflows, hyper-automation requires orchestrating and integrating a variety of automation technologies, systems, and processes. It uses technologies like chatbots, sentiment analysis, computer vision, and natural language processing (NLP) to automate jobs that call for human-like comprehension and intelligence. Hyper-automation uses data analytics, AI, and ML to automate decision-making processes. Systems can now analyze huge amounts of data, spot trends, anticipate the future, and offer suggestions for better decision-making.
Hyper-automation can be used to meet the specific issues and procedures faced by various sectors. There is a chance to create hyper-automation solutions that are industry-specific and catered to the requirements of industries like healthcare, finance, manufacturing, logistics, and retail. Through focused automation and optimization capabilities, these systems may address particular pain areas, regulatory needs, and process complexity within each business. In a variety of sectors, intelligent process automation may boost productivity, lower mistakes, and produce better results.
The adoption of hyper-automation is being driven by the continuing digital transformation activities in businesses all around the world. Hyper-automation is essential for integrating processes, systems, and data across the organization. There is an increasing focus on education and training programmes to develop internal competencies as organizations become more aware of the advantages and possibilities of hyper-automation.
The development of hyper-automation has been significantly aided by developments in AI and ML technologies. RPA has become a crucial part of hyper-automation in recent years and has seen substantial growth. RPA enables businesses to automate rote, rule-based processes across systems and apps. RPA solutions are a popular choice for businesses wanting to start their automation journeys because of their simplicity of setup and scalability. The market for hyper-automation has grown as a result of RPA’s expanding acceptance.
Hyper-automation is being actively explored by sectors including banking, healthcare, manufacturing, and retail to improve their operations and obtain a competitive advantage. The creation and deployment of hyper-automation solutions are supported by a robust ecosystem of technology vendors, research organizations, and consultancy companies.
