Market Trends of Hyperautomation Industry
This section covers the major market trends shaping the Hyperautomation Market according to our research experts:
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.
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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.
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