What is Hyperautomation?
Hyperautomation uses cutting-edge technology, such as robotic process automation (RPA), machine learning, and artificial intelligence (AI), to automate tasks previously performed by humans. Hyperautomation is a key factor in digital transformation as it frees workers from menial, low-value tasks to concentrate on higher operational value jobs. Hyperautomation and human interaction work together to help businesses deliver great customer experiences while lowering operating expenses and increasing profitability.
Adopting hyperautomation technologies enables businesses to reinvent their services or work together to create cutting-edge solutions to support their clients. In essence, hyperautomation services have redefined the flow of information and data throughout an organization, enabling efficiency for decision-making, producing innovative services and solutions, boosting the quality of work, and giving the organization flexibility by adding a digital workforce.
Hyperautomation helps businesses boost agility and streamline operations while also helping to systematize business-wide processes. It aims to take advantage of the data gathered and generated by digitized processes and reduce costs, increase productivity, and improve efficiency.
Difference between Automation and Hyper Automation
In many aspects, it is still determined what distinguishes automation from hyperautomation. The accomplishment of repetitive tasks without the involvement of a human being is known as automation. It usually occurs on a small scale and results in a solution tailored to the specific goal. On the other hand, Hyperautomation is the extension of automation initiatives using various automation techniques that support intelligent automation, including machine learning and robotic process automation.
Key components of Hyperautomation
Hyperautomation is built on integrating a multitude of technologies rather than just one, such as:
- Robotic Process Automation (RPA) makes it feasible to set up software that enables robots to carry out routine, structured operations in digital systems.
- Machine Learning: It uses an algorithm to train computers to perform difficult tasks, allowing them to complete complex jobs without extra human programming.
- Artificial Intelligence:Its goal is to build machines that can emulate logical human cognition to make decisions and solve complex issues.
- Big Data is a group of technologies that enables the storage, analysis, and management of enormous amounts of data generated by devices to spot trends and provide the best solutions.
- Advanced Analytics: Hyper automation works with structured and unstructured data, enabling firms to access and analyze previously inaccessible data to acquire crucial organizational-level insights.
- Chatbots employ cognitive intelligence and adapt their responses to users’ emotional states. This type of automation can be strong enough to handle most problems without requiring human interaction when combined with RPA.
Benefits of Hyper Automation
- Accelerating complex work
- Improved employee productivity
- Integrated environment
- Increase in ROI
- Reduction in operating costs
- Creates digital twin of organization
Тhе Glоbаl Hyper Automation Mаrkеt is estimated to be UЅD 9.7 Bn іn 2022 and is projected tо rеасh UЅD 33.4 Bn bу 2032 аt а САGR оf 21.6%.
Key Market Insights of Hyperautomation:
- Based on Technology Type: The machine learning (ML) segment is estimated to dominate the market.
- Based on End-Use Industry: The BFSI segment is anticipated to witness a significant increase in the forecast period. Since the banking industry is constantly changing and embracing new technologies to add value and redefine itself into a highly efficient and resilient sector, many banks have started using advanced analytics, which is useful for screening and assessing the repayment capacity of customers. It is more useful than manual screening.
- Based on Region: Regarding revenue, Asia Pacific is expected to dominate the hyperautomation market. It is related to the rapid transformation of conventional production facilities to automated facilities.
Factors driving the growth of this market:
- Increase in demand for cloud-based technology globally
- Increase in AI investment
- Rising use of smart business solutions
- Need for operational cost reduction