Report

The hyperautomation market is expected to register a CAGR of 19.3% over the forecasted period. The key reason fueling the growth of the global hyperautomation market is the increase in digitalization worldwide. A digital process automation solution is most frequently used in firms that need effective back-end processing administration due to the rising demand for business automation. As a result, more enterprises are being founded, including BFSI businesses, industrial industries, and online retailers. The market is growing more due to companies adopting automation faster. An organization can significantly speed up operations while lowering errors by automating all of the repetitive manual tasks previously carried out by humans.

Key Highlights
The increasing implementation of automation in the manufacturing sector is expected to drive the hyperautomation market. Further, Cisco has predicted that by 2022, over half of the 28.5 billion connected devices on the planet will get connected via machine-to-machine (M2M) connections. The next generation of robotics and automation technologies represents a revolutionary opportunity for manufacturing to improve productivity, quality, safety, and cost metrics. It is something that manufacturers all over the world are aware of. Additionally, rising spending on robotic automation year over year is primarily broadening the study market's focus.
Moreover, applications of RPA and AI have enabled the rise of security standards at the national and regional levels. Companies use hyperautomation to spot safety lapses and avert catastrophic mishaps. Many industrialized economies' defense industries are now exploring hyperautomation to modernize their security protocols and procedures. The industry that stands to gain the most from incorporating RPA and AI in its protocols is aerospace. Due to the rising trend in strategic alliances among market participants, there is more potential for increased worldwide market growth. It is common to see businesses partnering with other organizations to expand their global reach and assist the development of the worldwide market.
Scaling automation through hyperautomation is rethinking patient care and improving health outcomes. Hyperautomation increases the value of human expertise and data by adding capabilities to existing operations. Through speech recognition and clever algorithms, voice biometrics technology analyzes patients' voices to verify their identities and compare them to the information they gave on their registration forms. It adds a layer of authentication to prevent patient impersonation during any contact.
Furthermore, several applications were noted for voice biometrics during the pandemic. Research studies have explored the use of voice biometrics in detecting COVID-19-affected patients. For instance, in September 2021, research undertaken by artificial intelligence company Biometric Vox, in collaboration with the Cruces hospital and Domingo Pascual-Figal, head of Cardiology at Murcia's Virgen de la Arrixaca hospital, outlined the use of voice recognition to help in the detection of COVID-19 cases with 80% success rate.
On the Flipside, since hyperautomation is relatively new, more institutions need to provide high-quality training in such advanced technology. The demand and the actual supply of skilled professionals need to be more balanced. Because it will take more time to train professionals before they can practically and effectively execute hyperautomation, this could significantly impact the growth of the global industry. For creating learning opportunities to develop qualified and skilled people in the hyperautomation industry, the global market needs additional investors in the educational sector.


Hyperautomation Market Trends

The Machine Learning Segment is Expected to Drive the Market's Growth


Machine Learning (ML) is a subfield of Artificial Intelligence (AI) that enables training algorithms to make classifications or predictions through statistical methods, uncovering critical insights within data mining projects. These insights drive decision-making within applications and businesses, ideally impacting key growth metrics. Since it revolves around algorithms, models, and computational complexity, skilled professionals must develop these solutions. The performance of automated machine learning has advanced due to data science and artificial intelligence improvements. Companies recognize the potential of this technology, and hence its adoption rate is likely to rise over the forecast period. Companies are selling automated machine learning solutions on a subscription basis, making it easier for customers to use this technology. Furthermore, it offers flexibility on a pay-as-you-go basis.
AI enables machines to reason independently of humans and comes to their conclusions. The main goal of AI is to create computer programs or robots capable of thinking similarly to humans. A branch of AI known as machine learning, or ML, uses learning algorithms to enable it to learn from the past and advance. People can program a car to follow traffic lights, but it can also learn from other vehicles and from its own driving experience to reduce the frequency of accidents on the road. So, as a part of hyper-automation, it will be one of the most crucial technologies required to help devices learn and think before performing according to the workflow.
According to the Society of Actuaries (SOA), nearly two-thirds of executives anticipate that predictive analytic tools will cut organizational costs by 15% or more by 2023. Future analytics will open up hyperautomation applications in this industry.?
The companies are developing new solutions or incorporating new features in their existing products to cater to a wide range of needs of different customers and to expand their market share. For instance, in March 2021, The Oracle Machine Learning AutoML User Interface made it simple for novice and experienced data scientists to design and deploy machine learning models. OML AutoML UI, a new component of Oracle Machine Learning on Oracle Autonomous Database, provides a no-code browser-based interface that automates machine learning modeling and reduces deployment to a few clicks. OML AutoML UI is an advanced, proprietary technology developed by Oracle Labs that uses Oracle Machine Learning's sophisticated in-database algorithms.
Further, the rise in the use case of machine learning for companies will create an opportunity for the hyperautomation market to grow. For instance, according to Algorithmia, the top use cases for artificial intelligence and machine learning in 2021, as per 57% of respondents, are for increasing customer experience. Using AI and ML can improve several business operations.


North America is Expected to Hold a Major Market Share


North America is one of the prominent regions for the global hyperautomation market because many essential market players are situated there. According to MAPI, US manufacturing production will increase by 2.8% from 2018 to 2021, further increasing the adoption of hyperautomation and control technologies in the country. Also, the recent increase in tariffs will likely force manufacturers in the US to produce goods at a lower cost, achieved through automation. Auto companies that invested in hyperautomation pre-tariffs are ahead of the game and are the cost-saving blueprint for other companies.
Auto dealers may anticipate what client wants with hyper-automation and outfit themselves with a well-functioning supply chain. With the aid of predictive analytics, people can expect any unforeseen changes in vehicle demands, and the system responds promptly. It offers advice on reducing errors and overhead expenditures. The system analyses the sales history and forecasts demand behavior using pertinent criteria to keep the warehouse current.
Further, the rise in automotive production is expected to drive the studied market in the region. For instance, according to OICA, In 2021, over 13.43 million automobiles were made in North America. The North American economy is heavily dependent on the production of vehicles. The further point is that in 2021, the US car sector produced about 9.17 million vehicles.
In the US, over the last two years, the UPMC Health Plan abstractors found they can work around 38 times faster with the new implementation of Astrata's NLP-assisted tools. As a 40-hospital health system, it serves millions of patients across three states. In February 2021, UPMC Enterprises announced the launch of Astrata, the newest company incubated in UPMC Enterprises. Further, Astrata aims to increase its workforce by 30% over the coming year, and it joined a UPMC in recent years. Data scientists at the new company use cloud-based NLP to build tools enabling the payers to understand unstructured EHR data better, paving the way toward more accurate assessments of quality and population health measurements against Healthcare Effectiveness Data and Information Set.
Moreover, the rise of the developments towards biometrics in North America will drive the studied market over the forecasted period. For instance, in April 2021, Microsoft Corp. and Nuance Communications Inc. announced they reached a definitive deal for Microsoft to buy Nuance. Nuance is a Burlington, Massachusetts-based multinational computer software technology firm that sells speech recognition and AI software. Nuance provides AI expertise and consumer engagement solutions to enterprises worldwide. The solutions include Interactive Voice Response (IVR), virtual assistants, and digital and biometric solutions. To create next-generation customer engagement and security solutions, companies will combine this knowledge with the breadth and depth of Microsoft's cloud, including Azure, Teams, and Dynamics 365.


Hyperautomation Market Competitor Analysis

The global hyperautomation market is moderately fragmented, with the presence of many companies. The companies continuously invest in strategic partnerships and product developments to gain more market share. Some of the current events in the market are:

June 2022 - Tray.io, a low-code automation and integration player, announced new capabilities designed to accelerate enterprise hyper-automation initiatives. With Connector Builder, Tray.io provides end-to-end connectivity for all user types, enabling low-code developers to create reusable connectors on-demand fast, efficiently, and visually. Additionally, the integration of hundreds of underlying endpoints into only three API calls is made simpler with a new Connectivity API experience for developers.

May 2022 - A global player in digital payments, Visa, and Phrasee, a player in brand language optimization, announced the establishment of an exclusive agreement for Europe. The three-year contract is a component of Visa's strategic investment in its customers, including the top B2B financial services companies in Europe. Phrasee will make its advanced machine learning and natural language generation technologies available to Visa customers through its reseller program.

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