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What are the primary drivers fueling the growth of the machine learning (ml) intelligent process automation market in recent years?
The growing demand for digital transformation is expected to propel the growth of the machine learning (ML) intelligent process automation market going forward. Digital transformation refers to the incorporation of digital technologies into an organization’s products, processes, and strategies to enhance efficiency, productivity, customer engagement, innovation, and revenue. The demand for digital transformation is driven by the need for increased efficiency, agility, and competitiveness in an increasingly digital and interconnected business landscape. Digital transformation utilizes machine learning intelligent process automation to automate repetitive tasks, optimize processes, and make data-driven decisions across various business functions, enhancing efficiency and productivity. For instance, in November 2023, according to the Central Digital and Data Office, a UK-based government office, between April 2022 and April 2023, the government’s digital and data profession saw a significant growth of 19%, effectively fulfilling essential requirements for digital expertise. Additionally, in December 2023, according to the European Commission (EC), the Belgium-based executive body of the European Union (EU), the adoption of cloud-based solutions in 2023 in the European Union increased by 4.2 percentage points, with 45.2% of enterprises purchasing cloud computing services, showcasing a notable rise compared to 2021. Therefore, the growing demand for digital transformation is driving the growth of the machine learning intelligent process automation market.
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What is the projected market size of the machine learning (ml) intelligent process automation industry, and how is it expected to grow?
The machine learning (ML) intelligent process automation market size has grown rapidly in recent years. It will grow from $19.58 billion in 2024 to $23.19 billion in 2025 at a compound annual growth rate (CAGR) of 18.4%. The growth in the historic period can be attributed to increased spending on business operations optimization, technological adoption across various industry sectors, demand for intelligent process automation solutions and services, focus on automation to reduce manual efforts, and emphasis on improving operational efficiency.
The machine learning (ML) intelligent process automation market size is expected to see rapid growth in the next few years. It will grow to $45.09 billion in 2029 at a compound annual growth rate (CAGR) of 18.1%. The growth in the forecast period can be attributed to the integration of emerging technologies, expansion and enhancement of product portfolios, adoption of innovative automation solutions, increasing demand for automation technologies in developing countries, and focus on automation to enhance customer experience. Major trends in the forecast period include the integration of cloud-based technologies for automation, increased use of machine learning algorithms for efficiency, rise in virtual agents for customer service enhancement, adoption of natural language processing for improved interactions, and focus on AI-driven decision-making processes.
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Who are the key players driving competition in the machine learning (ml) intelligent process automation market?
Major companies operating in the machine learning (ML) intelligent process automation market are Alibaba Group Holding Limited, Accenture plc, International Business Machines Corporation (IBM), SAP SE, Tata Consultancy Services Limited (TCS), Capgemini SE, Atos SE, Wipro Limited, Xerox Holdings Corporation, NICE Ltd., Blue Prism Group plc, Pegasystems Inc., BlueHalo LLC, UiPath Inc., Automation Anywhere Inc., Appian Corporation, Kofax Inc., Bright Machines Inc., Cove.Tool Inc., Larc AI (Pty) Ltd., Cinnamon Inc., AutomationEdge Technologies Inc., AntWorks Global Limited
What key trends are expected to drive the machine learning (ml) in the pharmaceutical industry market during the forecast period?
Major companies operating in the machine learning intelligent process automation market are integrating their efforts into developing advanced solutions, such as artificial intelligence platforms, to streamline operations and enhance productivity. Artificial intelligence platforms are software solutions that enable the development and management of AI applications for improved decision-making and efficiency. For instance, in March 2024, Cognizant, a US-based global technology company, launched the Advanced Artificial Intelligence Lab. The Advanced Artificial Intelligence Lab refers to various research facilities dedicated to advancing the field of artificial intelligence through innovative research and development. This is aimed at accelerating AI research and innovation and will focus on advancing the science and practice of AI through innovation and development of intellectual property and AI-enablement technologies.
Which key geographies are driving the growth of the machine learning (ml) intelligent process automation market?
North America was the largest region in the machine learning (ML) intelligent process automation market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning (ML) intelligent process automation market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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What are the key segments driving growth in the machine learning (ml) intelligent process automation market?
The machine learning (ML) intelligent process automation market covered in this report is segmented –
1) By Type: Structured, Unstructured
2) By Component: Solutions, Software Tools, Platforms, Services, Professional Services, Advisory Or Consulting, Design And Implementation, Training, Support And Maintenance, Other Components
3) By Application: Information Technology Operations, Contact Center Management, Business Process Automation, Application Management, Content Management, Security Management, Other Applications
4) By End User: Banking, Financial Services, Insurance (BFSI), Telecommunications And Information Technology (IT), Transport And Logistics, Media And Entertainment, Retail And E-Commerce, Manufacturing, Healthcare And Life Sciences, Human Resource Management
Subsegments:
1) By Structured: Data Extraction, Data Classification, Data Processing, Data Integration
2) By Unstructured: Natural Language Processing (NLP), Image Recognition, Text Analytics, Speech Recognition
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How is the machine learning (ml) intelligent process automation market defined, and what are its core characteristics?
Machine learning intelligent process automation refers to the application of machine learning algorithms and artificial intelligence (AI) technologies to automate and optimize business processes across various industries. It utilizes algorithms to analyze data, make decisions, and execute actions, leading to more efficient and intelligent automation of complex workflows and business processes.
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