AI in Manufacturing Market Report 2025

This AI in Manufacturing market report provides a comprehensive analysis of the market’s characteristics, size, and growth, including segmentation, regional and country-level breakdowns, competitive landscape, market shares, trends, and strategies. It also tracks historical and forecasted market growth across various geographies.

The AI in manufacturing market size has grown exponentially in recent years. It will grow from $4.11 billion in 2024 to $5.82 billion in 2025 at a compound annual growth rate (CAGR) of 41.5%. The growth in the historic period can be attributed to energy efficiency and sustainability, customization and personalization, cost reduction measures, workforce upskilling and training, and supply chain optimization.

The AI in manufacturing market size is expected to see exponential growth in the next few years. It will grow to $25.23 billion in 2029 at a compound annual growth rate (CAGR) of 44.3%. The growth in the forecast period can be attributed to the adoption of edge computing, green manufacturing initiatives, focus on cybersecurity, enhanced human-machine collaboration, and supply chain resilience. Major trends in the forecast period include robotics and automation integration, quality control and defect detection, augmented reality applications, data-driven decision-making, and autonomous manufacturing processes.

The rising demand for automobiles is anticipated to drive the growth of AI in the manufacturing sector in the future. An automobile, often referred to as a car or motorcar, is a wheeled vehicle intended for transporting passengers or goods on roads. The automobile industry integrates AI (artificial intelligence) in manufacturing through various applications, including the development of autonomous vehicles, predictive maintenance, data collection and analysis, as well as quality control and inspection. By leveraging AI, manufacturers can enhance vehicle design and optimize the tools and robots used in production. Currently, AI is utilized across the manufacturing process, supply chain, post-production, and automobile design. For example, the European Automobile Manufacturers Association, a Belgium-based trade organization, reported in May 2023 that 85.4 million motor vehicles were produced globally in 2022, marking a 5.7% increase from 2021. Thus, the growing demand for automobiles is a key factor propelling the expansion of AI in the manufacturing market.

The increasing adoption of industrial robots is expected to drive the growth of AI in the manufacturing sector in the future. Industrial robots are mechanical devices designed to perform production-related tasks automatically in industrial environments. Artificial intelligence (AI) is transforming the manufacturing landscape; by incorporating AI capabilities into robots, manufacturers are achieving unprecedented levels of efficiency, flexibility, and safety. For example, the International Federation of Robotics, a Germany-based organization focused on robotics research, reported in September 2023 that factories around the globe installed 553,052 industrial robots in 2022, reflecting a 5% increase from the previous year. Therefore, the rise in the use of industrial robots is a significant factor contributing to the growth of AI in the manufacturing market.

A prominent trend in the AI in manufacturing market is the increasing focus on technological advancements by companies to maintain their competitive positions. In March 2023, Leela AI, a US-based software development company, introduced the Leela Platform, its inaugural 'commonsense' visual AI platform designed to enhance manufacturing output. This platform allows manufacturers to uncover insights into production processes that may not be evident through Industrial Internet of Things (IIOT) sensor analytics. Users of the Leela Platform can compare productivity across shifts, workstations, and locations, identify bottlenecks, and recognize best practices. Industrial engineers, CI officers, and line supervisors can leverage the platform, which functions as an ongoing time-and-motion study by monitoring frontline activities involving equipment, machines, parts, and products.

Major players in the AI in manufacturing market are actively engaged in developing technological innovations, such as AI platforms, to gain a competitive advantage. An AI platform is a comprehensive solution for constructing, deploying, and managing machine learning (ML) models at scale, offering tools and services to facilitate the development and utilization of AI applications. For example, in October 2023, Fujitsu Limited, a Japan-based information and communications technology equipment company, launched the Kozuchi AI platform. This platform is designed to simplify access to AI and machine learning (ML) solutions globally, providing pre-built AI and ML solutions that eliminate the need to start from scratch. This novel approach is anticipated to significantly reduce the man-hours required to create an AI model, particularly in addressing production scheduling optimization challenges, by up to 95%.

In June 2023, Accenture plc., an Ireland-based professional services company, completed the acquisition of Flutura, an Indian-based provider of industrial artificial intelligence (AI). This strategic move is expected to enhance Accenture's industrial AI services, enabling clients to expedite the achievement of net-zero goals. The acquisition of Flutura positions Accenture as a key player in leveraging industrial AI for sustainable and efficient solutions in various industries.

AI in manufacturing refers to the incorporation of artificial intelligence (AI) technologies into the manufacturing process, aiming to enhance efficiency, productivity, and product quality. This integration involves the utilization of machine learning algorithms, computer vision, robotics, and other AI tools to analyze data, automate processes, and optimize overall production. By leveraging AI in manufacturing, companies can achieve cost reductions, improve the quality of their products, and enhance overall operational performance.

The primary types of AI technologies applied in manufacturing include machine learning, natural language processing, context-aware computing, and computer vision. Machine learning, as a subset of AI, focuses on developing algorithms and statistical models that enable computer systems to learn from data, allowing them to make predictions or decisions without explicit programming. These AI technologies are available in the form of hardware, software, and services, with deployment options including cloud-based and on-premises solutions. Their applications span various areas such as predictive maintenance, machinery inspection, material movement, production planning, field services, quality control, cybersecurity, industrial robots, and reclamation. Industries benefiting from AI in manufacturing include automobiles, energy and power, semiconductors and electronics, pharmaceuticals, heavy metal and machine manufacturing, food and beverage, among others.

The AI in manufacturing market research report is one of a series of new reports that provides AI in manufacturing market statistics, including the AI in manufacturing industry global market size, regional shares, competitors with a AI in manufacturing market share, detailed AI in manufacturing market segments, market trends, and opportunities, and any further data you may need to thrive in the AI in manufacturing industry. This AI in manufacturing 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.

Major companies operating in the ai in manufacturing market report are Nvidia Corporation, The International Business Machines Corporation, Siemens AG, General Electric Company, SAP SE, Amazon Inc., Mitsubishi Electric Corporation, Rockwell Automation Inc., Robert Bosch GmbH, Google LLC, Intel Corporation, Micron Technology Inc., Oracle Corporation, Cisco Systems Inc., Microsoft Corporation, Hilscher Gesellschaft für Systemautomation GmbH, Beckhoff Automation GmbH, Phoenix Contact GmbH & Co. KG, Veo Robotics, Automation Anywhere, Machina Labs Inc., Advanced Micro Devices Inc., SoluLab, Keyence Corporation, LeewayHertz, Citadel Analytics, Omron Corporation, Yokogawa Electric Corporation, Cognex Corporation, Bosch Rexroth AG.

Asia-Pacific was the largest region in the AI in manufacturing market in 2024. It is expected to be the fastest-growing region in the global AI in manufacturing market report during the forecast period. The regions covered in the ai in manufacturing market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the ai in manufacturing market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

AI in the manufacturing market consists of revenues earned by entities by providing services such as quality assurance, warehouse automation, and robotic process automation (RPA). The market value includes the value of related goods sold by the service provider or included within the service offering. AI in the manufacturing market also includes sales of graphical processing units, tensor processing units, and optimized chips. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

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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