Machine Learning (ML) Intelligent Process Automation Global Market Report 2024

The machine learning (ML) intelligent process automation market size has grown rapidly in recent years. It will grow from $16.6 billion in 2023 to $19.58 billion in 2024 at a compound annual growth rate (CAGR) of 17.9%. The expansion observed during the historical period can be attributed to several factors, including increased investment in optimizing business operations, widespread adoption of technology across various industry sectors, growing demand for intelligent process automation solutions and services, a focus on automation to reduce manual efforts, and an emphasis on enhancing 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 $38.19 billion in 2028 at a compound annual growth rate (CAGR) of 18.2%. The projected growth in the forecast period can be attributed to several factors, including the integration of emerging technologies into existing systems, the expansion and enhancement of product portfolios to meet evolving needs, the adoption of innovative automation solutions, increasing demand for automation technologies in developing countries, and a focus on automation to enhance the overall customer experience. Key trends expected during this period include the integration of cloud-based technologies for automation, increased utilization of machine learning algorithms to improve efficiency, a rise in the use of virtual agents for enhancing customer service, adoption of natural language processing to facilitate more seamless interactions, and a focus on AI-driven decision-making processes to drive business outcomes.

The machine learning (ML) intelligent process automation market is poised for growth, driven by the increasing demand for digital transformation. Digital transformation involves the integration of digital technologies into organizational processes, products, and strategies to enhance efficiency, productivity, customer engagement, innovation, and revenue. This demand stems from the necessity for heightened efficiency, agility, and competitiveness in an increasingly digitalized and interconnected business environment. Machine learning intelligent process automation plays a pivotal role in digital transformation initiatives, automating repetitive tasks, optimizing processes, and facilitating data-driven decision-making across various business functions, thereby enhancing efficiency and productivity. For example, as reported by the Central Digital and Data Office in November 2023, the UK government's digital and data profession witnessed a significant growth of 19% between April 2022 and April 2023, meeting essential requirements for digital expertise. Additionally, over 600 senior civil servants in the UK have undergone upskilling in digital and data essentials. Consequently, the burgeoning demand for digital transformation acts as a driving force behind the growth of the machine learning intelligent process automation market.

Key players in the machine learning intelligent process automation market are channeling their efforts towards the development of advanced solutions, including machine learning platforms, aimed at streamlining operations and enhancing productivity. Machine learning platforms facilitate efficient automation and optimization of business processes through intelligent data analysis and decision-making capabilities. For instance, in May 2021, Google introduced Vertex AI, a managed machine learning platform designed to simplify the building, training, and deployment of machine learning models at scale. Vertex AI consolidates various Google Cloud services into a unified UI and API, empowering data scientists and ML engineers to work more effectively. The platform grants access to Google's internal AI toolkit, encompassing tools for computer vision, natural language processing, conversational AI, and structured data analysis. This enables data scientists and ML engineers to leverage AI technologies efficiently, accelerate development productivity, and streamline the deployment of machine learning models.

In January 2023, McKinsey, a renowned management consulting firm, acquired Iguazio for an undisclosed sum. This strategic acquisition enables McKinsey to significantly accelerate and scale AI deployments. By leveraging Iguazio's MLOps Platform, McKinsey aims to expand its AI capabilities and deliver industry-specific AI solutions that are more productive, expedite the journey from proof-of-concept to production, and enhance reliability. Iguazio, an Israel-based software company, specializes in providing ML intelligent automation processes through its MLOps Platform, thus complementing McKinsey's offerings and bolstering its position in the AI-driven digital transformation landscape.

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.

North America was the largest region in the machine learning (ML) intelligent process automation market in 2023. 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.

The countries covered in the machine learning (ML) intelligent process automation market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Machine learning intelligent process automation (MLIPA) refers to the utilization of machine learning algorithms and artificial intelligence (AI) technologies to automate and optimize business processes across various industries. By leveraging algorithms to analyze data, make decisions, and execute actions, MLIPA enables more efficient and intelligent automation of complex workflows and business processes.

The primary types of MLIPA can be categorized as structured and unstructured. Structured MLIPA involves the application of algorithms to automate repetitive tasks and workflows using structured data. This encompasses various components such as solutions, software tools, platforms, and services including professional services, advisory or consulting, design and implementation, training, support, and maintenance. These solutions find applications across diverse domains including information technology operations, contact center management, business process automation, application management, content management, security management, and others. MLIPA is utilized by a wide range of end-users including those in 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, and human resource management.

The machine learning (ML) intelligent process automation research report is one of a series of new reports that provides machine learning (ML) intelligent process automation market statistics, including the machine learning (ML) intelligent process automation industry's global market size, regional shares, competitors with a machine learning (ML) intelligent process automation market share, detailed machine learning (ML) intelligent process automation market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning (ML) intelligent process automation industry. This machine learning (ML) intelligent process automation market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The machine learning (ML) intelligent process automation market includes revenues earned by entities by providing services such as automated data extraction, predictive analytics, anomaly detection, and natural language processing (NLP) for text understanding. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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