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5 Industries That Reveal Jump From Automation to Hyperautomation

Automation is reshaping the various complex facets of business models and value chain, including layers of data modeling, Cloud modernization, remote workplace collaboration, and employee experience. However, there are challenges in making the jump from automation to hyperautomation. One of them is the robotization of human tasks. The most heard misconception about AI is its ability to take away human jobs. However, the truth couldn’t be farther than that. As there are so many definitions of AI in the news and media, what AI can do for an enterprise can be misleading. In fact, a World Economic Forum study illustrates that 58 million new jobs will be added in the next few years because of machines and algorithms. Hence, in the business world, it is crucial to understand how AI can create value for businesses, and where it cannot. 

Big Data, AI, ML, and Automation are some fine examples that have received the same treatment. In the case of automation, many companies were hesitant about it initially. Rather than taking advantage of automation, business pioneers feared change and employees stressed the loss of their jobs. Eventually, they did come around and automation became a top priority for most businesses. And now, we are yet again on the verge of another technological update, i.e. Hyperautomation, which has captured everybody’s attention.

Some Quick Facts About the Implementation of Automation in Industries from Deloitte.

  • Under productivity, 47% of CEOs consider technology as one of their top two ways to improve productivity 
  • In progress, 82% of CEOs report that they had a digital transformation initiative underway in 2019 
  • For a digital business, 30% have digitized their core business, 32% developed an alternative model to replace their core business, and 43% launched a new digital business
  • For the tech evolution, 80% of business leaders in the UK want to change how employees work and which technology they’re using 
  • For Robotic Process Automation (RPA), 53% of business leaders in the UK have already started their RPA journey, which is expected to increase to 72% in the next two years

What is Hyperautomation and Why Does it Matter? 

Recognized as one of the year’s Top 10 Strategic Technology Trends, Gartner has reported Hyperautomation to be the next major thing for the industries. It is meant to take automation to the next level and automate the automation.

According to McKinsey, an assessment of available automation technologies shows that a typical retail grocery store can save up to 4-5 days of work in terms of man-hours.

In the words of Gartner, “RPA enriched by AI and ML becomes the core enabling technology of hyperautomation.”

Combining RPA and AI technologies offer the power and flexibility to automate where automation was never possible before: undocumented processes that rely on unstructured data inputs.”

Hyperautomation is a technology that uses advanced automation technology ecosystems to increase the use of human knowledge by a business. The goal is to automate business processes where companies can leverage data and insights to make effective decisions. These innovations include the automation of robotic processes, artificial intelligence, machine learning, decision management, process mining, and natural language processing.

Gartner notes that RPA enriched by AI and ML is the central hyperautomation technology. It is a means for true digital transformation through a variety of technologies such as RPA, ML, and AI, which operate in harmony with dynamic business processes. The combination of RPA and AI technology offers control and versatility to automate processes that have never been automated previously.

The Working Methodology

As per Gartner’s Top 10 Strategic Technology Trends for 2020: Hyperautomation, “By 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes.”

The primary objective of the hyperautomation is to include more intelligence and to implement a wider range of tools than before. As hyperautomation cannot replace humans with a single technology, it needs to be combined with other tools to urge companies to consider key approaches to determine the fullest benefits of technology in their business.

Why Adopt Hyperautomation?

Hyperautomation also provides an organization’s digital twin (DTO). A DTO, virtually representing a workflow throughout its life cycle, enables companies to visualize its performance and capabilities to drive value. The DTO offers real-time, continuous information about the company and leads to enormous business opportunities as an important aspect of the hyperautomated process.

For example, if a company launches a product, and DTO metrics show a high customer demand, the product can be rapidly scaled to increase sales. On the other hand, if advanced analysis shows that the product cannot attract customers, its production can be reduced with minimal losses.

The technology can be placed at the top of the working pipeline of the organizations. Another increasing concept of hyperautomation is RPA, which uses AI programming, and ML functions for high-volume, repetitive tasks that people do repeatedly. 

Hyperautomation in Action

Banking and Finance Industry

The banking industry has a strong potential for hyperautomation implementation. Certain ideal places include regulatory reporting, marketing, sales & distribution, banking service, payment transactions, loan transactions, back-office transactions, enterprise support, and so on.

Hyperautomation ensures that financial teams stay up-to-date and centralize their data. The RPA manages low-level tasks and financial institutions spend more time providing strategic decision-making advice. It improves accuracy and allows CFOs to report live data, identify risks and opportunities, and make quick decisions using the latest data.

For example, an Intelligent Character Recognition solution allows manually written KYC forms to form electronically in the right KYC portions in the eKYC process. All other relevant systems are further complemented by this information. According to Thomson Reuters, banks spend around $384 million per year on this KYC compliance. Hence, automation can save time, money, and human intervention.

Moreover, intelligent automation solutions can proactively identify fraudulent activities. Machine-based predictive models based on advanced modeling can forecast the likelihood of fraudulent transactions. Many solutions for anti-money laundering today use hyperautomation technology stack for prediction and prevention.

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Hyperautomation potential in insurance is pegged at 75%.

The insurance industry entails many routine, repetitive, and manual workforce. Herein, advanced analytics can gain significant insight from data collected from sensors, wearables, geographical and other sources. Further, predictive modeling techniques can help insurers calculate the probability of risk for certain customer segments and policy premiums.

According to Mckinsey, hyperautomation not only reduces human error but also helps develop better policies and lead the way in the highly volatile market. The general advantages of hyperautomation can be sum up as:

  • Reduces the cost of automated job functions by 30–40%
  • Achieve 80–90% accuracy 
  • Optimizes the resources and their time 
  • Provided faster delivery by nearly 80%
  • Boosts overall productivity by about 50%
  • 100% regulatory compliance


The core purpose of adopting hyperautomation is to modernize the existing digital process in fewer steps and with lesser resources. Currently, Healthcare is predicted to have a 60% automation potential.

For example, take the case of the healthcare industry. Robotic Process Automation (RPA) in healthcare is a raging trend.

Hyperautomation streamlines back-office operations in the healthcare industry to improve overall operational efficiencies. This gives medical practitioners more time to enhance clinical outcomes and better patient experience.

Automation allows intelligent billing by collecting and consolidating bill details from each department in a healthcare institution with no manual interference. For instance, AI and RPA automation can identify medical policy coverage and conditions, and an intelligent virtual assistant/chatbot can support with automated bill submission procedures.

Furthermore, machine learning-based voice recognition systems enable speech-to-text transcription. An ML model can be trained to derive desired results and accuracy on several thousands of samples with various speech requests.

UiPath, a leading RPA software company, worked with a large European hospital to assist with RPA transformation. The hospital operating with 2,000 staff was struggling with 70,000 emergency visits, and 300,000 outpatients annually. The working pipeline was manual, with almost every process being paper-based.

Their process of transition to the digital system wasn’t fruitful either. The manual input of paper files into a digital database was taking too much time. Other than that, the hospital struggled with updating digital records every time the information was upgraded. It also conflicted with inventory management with 20-30 percent of the hospital’s supplies went used.

However, once the hospital implemented RPA, it was able to:

  • Streamline workflows and activities
  • Benefit from single-point access to their information. Medical histories, billing information, appointments, and reminders were rendered easily
  • Maintain quality inventory and with analytics, optimized it with previous needs and patterns
  • Minimized claim processing costs up to 75 percent by automating 80 percent of the process 


In the US alone, online sales are expected to double by 2023, reaching 20 to 25 percent of the overall retail sector. RPA in retail can boost productivity, enhance customer care, and deliver accurate results. As per Accenture, “43% of CPG Executives Automate tasks primarily to cut costs and increase efficiency.”

Advancing further to hyerautomation technologies, the retail sector can uplift in the areas of order management, payments, transport, warehousing and inventory, supplier management, risk management, acquisition, data monitoring, etc.

Another useful way to remain competitive in the market is pricing analytics. For instance, digital personnel can be assigned to track competitiveness sites to report fluctuation in prices on the market and prices in real-time, 24/7. Furthermore, data from various sources such as social media can help customers analyze their feelings to improve decision-making.

BPO and Customer Service

BPO is a critical service for most companies or the industry that uses products and services. Agents spend more time collecting and manually uploading information from multiple systems to the order management system to allow less time for customer problem solvers. Caller information can be transmitted and processed seamlessly with smart automation. The average call handling time and efficiency can be reduced.

IPsoft’s virtual service desk robot Eliza, for example, can respond to 62,00 calls in a month and resolve two out of three questions without human supervision. 

AI can also monitor the call quality and help CSRs in critical calls, such as insurance claims to understand their customers’ experience. Based on its importance, AI can also help filter calls to reduce the cycle time for customer problems.

Furthermore, companies can use advanced analytics to identify customers at risk and improve customer retention rates. With the correct use of state-of-the-art analytic technologies, companies can actively maintain customer relationships and reduce the risk of customer attrition.

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