Глобальный рынок интеллектуальной автоматизации процессов машинного обучения (ML) – тенденции отрасли и прогноз до 2030 года

Анализ и размер рынка интеллектуальной автоматизации процессов машинного обучения (ML)

Ожидается, что потребность в повышении производительности бизнеса и растущее внедрение технологий в различных секторах промышленности будут способствовать росту рынка интеллектуальной автоматизации процессов машинного обучения (ML). Решения для интеллектуальной автоматизации процессов предоставляют пользователям передовые инструменты и адаптируемые рабочие процессы, позволяющие им принимать решения быстрее и с большим объемом знаний. Эти решения управляют интерфейсами и устраняют узкие места в системах рабочих процессов. Ожидается, что этот фактор придаст рынку импульс в ближайшие годы.

Компания Data Bridge Market Research анализирует, что рынок интеллектуальной автоматизации процессов машинного обучения (ML), оцениваемый в 13,6 млрд долларов США в 2022 году, достигнет 41,03 млрд долларов США к 2030 году, увеличившись в среднем на 14,80% в прогнозируемый период с 2023 по 2030 год. Помимо таких аналитических данных о рынке, как рыночная стоимость, темпы роста, сегменты рынка, географический охват, участники рынка и рыночный сценарий, рыночный отчет, подготовленный командой Data Bridge Market Research, включает в себя углубленный экспертный анализ, анализ импорта/экспорта, анализ цен, анализ производства и потребления, а также анализ пестицидов.

Масштаб и сегментация рынка интеллектуальной автоматизации процессов машинного обучения (ML)  

Определение рынка

Программные приложения теперь могут делать прогнозы более точно с помощью МО, подобласти ИИ. Алгоритмы машинного обучения прогнозируют новые выходные значения, используя исторические данные в качестве входных данных. Технологии искусственного интеллекта (ИИ) используются в автоматизации когнитивных процессов для ускорения когнитивных процессов, таких как рассуждение, машинное обучение и обработка естественного языка. Благодаря пониманию автоматизации когнитивных процессов эти задачи будут выполняться быстрее и проще как людьми, так и машинами.

Динамика рынка интеллектуальной автоматизации процессов машинного обучения (ML)

Драйверы

• Растущее внедрение RPA стимулирует рынок

Businesses use RPA technology to automate manual data entry tasks, doing away with the need for human labor. The IPA workflow combines cognitive learning, RPA, ML, and AI. As a result, as RPA gains popularity, IPA demand increases as well. RPA offers effectiveness and quickness. Artificial intelligence (AI) is added to automation to analyze data in a way that a human could not, recognize patterns in data, and learn from previous decisions to make increasingly wise decisions. IPA reduces the time needed for tasks by doing away with the need for human data entry, information validation, and document sorting thus driving the market growth.

• Increase in demand for implementation and training services drives the market

A significant segment that shows growth is design and implementation. Therefore, the growth is attributed to a better understanding of the use of automation solutions to reduce manual labor. As intelligent process automation solutions are more widely used, there is an increase in demand for implementation and training services. The providers focus on providing a customized solution that satisfies business requirements. As a result, it is anticipated that demand for intelligent process automation services will rise over the forecast period.

• High acceptance ratio drives the market

Machine learning (ML) intelligence sees a rapid expansion of the scope and use of IT and automation globally with a high acceptance rate, minimizing human work and error with optimal resource utilization to earn greater business enterprise efficiency. Automation with artificial intelligence helps in better customer experience and faster decision-making across the organization, which drives market growth.

Opportunities

• Growing investment in the intelligent process automation market

Businesses are switching towards work-from-home policies, which has a significant impact on the amount invested in operational process automation. Through increased investment in application areas such as telemedicine, predictive maintenance, and virtual healthcare management, the market is growing. The adoption of IPA solutions has increased across most non-IT verticals, thus the market sees an expansion in the machine learning (ML) intelligent process automation market during the aforementioned projected timeframe.

• Advancement in technology creates a lucrative opportunity to grow

Emerging intelligent automation technologies such as virtual agents and natural language processing, among others, are bringing in opportunities to improve the customer experience, and machine learning solutions are significantly improving efficiency. Systems can automatically learn from experience and get better with machine learning, which eliminates the need for explicit programming, thus advancement in technology can create lucrative opportunities in the market.

Restraints/Challenges

• Lack of highly qualified and sophisticated labor restricts growth

Skilled labor is required to run a newly automated operational model, but it's crucial to find individuals with RPA and AI expertise. Technical proficiency, an understanding of the business procedures of the organization, and the ability to adapt management techniques are all part of machine learning intelligence. Assigning people to ongoing maintenance, support, and troubleshooting is equally important to develop automation, and the absence of such skills can limit growth.

• Increased cybersecurity threats restrain market expansion

Cybersecurity is one of the most significant concerns in the digital age. Malware and ransomware attacks are becoming increasingly organized forms of cybercrime. Every day, businesses receive an increasing number of security notifications. According to CERT-In, more than 6.07 lakh cybersecurity incidents were reported in the first half of 2021. As a result, using cybersecurity for IPA is necessary to create an efficient security architecture that shields the organization from rising risks. 77% of businesses intend to increase automation in their security ecosystems in the ensuing years, according to a Cisco survey, which restricts the market.

This machine learning (ML) intelligent process automation market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the machine learning (ML) intelligent process automation market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Recent Developments

• In 2021, Cisco and IBM worked together to coordinate and manage 5G networks.
• In 2021, Google Cloud Marketplace users can now purchase DRYiCE iAutomate, according to HCL Technologies.
• In 2021, the debut of IBM Cloud Pak for Network Automation was announced by IBM.
• In 2021, to continue working together, Atos and du extended the contract for an additional five years. The modernization of applications and the digital transformation will be aided by this collaboration for du.
• In 2020, The Pega Platform has received a new improvement, according to Pegasystems. Pega Process AI now has a new feature to assist businesses in real-time business and customer operations optimization.

Global Machine Learning (ML) Intelligent Process Automation Market Scope

The machine learning (ML) intelligent process automation market is segmented on the basis of components, type, technology, organizational size, application, business function, deployment mode, and end user. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Component

• Solutions
• Software Tools
• Platforms
• Services
• Professional Services
• Advisory/Consulting
• Design and Implementation
• Training
• Support and Maintenance
• Managed Services

Type

• Structured
• Un-Structured

Technology

• Natural Language Processing
• Machine and Deep Learning
• Neural Networks
• Virtual Agents
• Mini Bots
• Computer Vision
• Others

Organization Size

• Large Enterprises
• SMEs

Application

• IT Operations
• Contact Centre Management
• Business Process Automation
• Application Management
• Content Management
• Security Management
• Others

Travel and Hospitality

Business Function

• Information Technology
• Finance and Accounts
• Human Resources
• Operations and Supply Chain

Deployment Mode

• On-Premises
• Cloud

End User

• Banking, Financial Services, Insurance (BFSI)
• Telecommunications and IT
• Transport and Logistics
• Media and Entertainment
• Retail and E-Commerce
• Manufacturing
• Healthcare and Life Sciences
• Others
• Human Resource Management
• Incident Resolution
• Service Orchestration
• Education
• Government and Public Sector
• Utilities

Machine Learning (ML) Intelligent Process Automation Market Regional Analysis/Insights

The machine learning (ML) intelligent process automation market is analysed and market size insights and trends are provided by components, type, technology, organizational size, application, business function, deployment mode, and end user as referenced above.

The countries covered in the machine learning (ML) intelligent process automation market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America dominates the market and will continue to flourish its trend of dominance during the forecast period. The major factors attributable to the region’s dominance are Along with the prevalence of various market players in the area, process management and automation solutions are becoming more widely adopted across the enterprise. Additionally, regional growth is being fueled by the growing enterprise adoption of process management and automation solutions in the United States. The primary drivers of the segmental growth are increased spending on business operations optimization and widespread adoption of cutting-edge technologies such as AI, machine learning, and RPA.

Asia-Pacific will undergo the highest growth rate during the forecast period owing to the region's adoption of cloud-based technologies and growing awareness of automation, machine learning, and artificial intelligence. The demand for intelligent process automation solutions and services is also being further boosted by growing awareness of automation, machine learning, and artificial intelligence. The major drivers of the regional market growth are globalization, economic development, digitalization, and increased adoption of cloud-based technologies.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points such as down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.

Competitive Landscape and Machine Learning (ML) Intelligent Process Automation Market Share Analysis

The machine learning (ML) intelligent process automation market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to machine learning (ML) intelligent process automation market.

Some of the major players operating in the machine learning (ML) intelligent process automation market are:

• Automation Anywhere, Inc. (U.S.)
• UiPath (U.S.)
• Blue Prism Limited (U.K.)
• Pegasystems Inc. (U.S.)
• AntWorks (Singapore)
• NICE (Israel)
• Kofax Inc. (U.S.)
• SAP SE (Germany)
• AutomationEdge (U.S.)
• Larc AI (Pty) Ltd. (South Africa)
• Autologyx (U.K.)
• Sanbot Innovation Technology., Ltd (Китай)
• Корица (Япония)
• Wipro (Индия)
• Корпорация Xerox (США)
• TATA Consultancy Services Limited. (Индия)
• IBM (США)
• Atos SE (Франция)
• Капджемини (Франция)
• Accenture (Ирландия)

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