Dublin, October 2, 2025 (Globe Newswire) – “There are global forecasts for artificial intelligence (MPUs, GPUs, FPGAs, ASICS) in the manufacturing market by processors, software (on-premises, cloud), technology (contextual awareness computing, computer vision, generative AL), and applications. ResearchAndMarkets.com Provided.
With a CAGR of 35.3%, the global AI in the manufacturing market is expected to increase from USD 3.418 billion in 2025 to USD 15.504 billion by 2030.
This report will help this market leader/new entrant to provide information on the closest approximation of the overall market and sub-segment revenue numbers. It also helps stakeholders understand competitive situations, position their business better, and gain more insight into planning the right off-the-shelf strategy. The report also helps stakeholders understand AI in the manufacturing market pulse and provide information on key market drivers, constraints, challenges and opportunities.
This robust growth is driven by the rapid adoption of AI technology to streamline production workflows, enhance real-time decision-making, and support predictive maintenance across diverse manufacturing operations. As manufacturers strive to improve agility, cost-effectiveness and quality assurance, AI solutions help unlock new levels of operational intelligence and productivity.
Industry such as automotive, electronics, aerospace and consumer goods are leveraging machine learning, computer vision, and natural language processing to optimize production scheduling, reduce downtime and detect anomalies early in the process. AI-enabled robots, digital twins and intelligent quality control systems allow manufacturers to scale their output with accuracy and adaptability.
Additionally, AI integration between industrial IoT platforms and cloud-based data analytics accelerates the transition to smart factories by enabling connected, data-driven ecosystems. With its focus on sustainability, customization and global competitiveness, AI is set to play a transformative role in shaping the next-generation manufacturing paradigm. As demand for intelligent automation and continuous process innovation intensifies, AI in the manufacturing market is experiencing sustained expansion across all regions and industries verticals.
Due to the application, the Forecast Maintenance segment held its largest market share in 2024.
In 2024, the predictive maintenance segment emerged as a major application for AI in the manufacturing market, leading to its focus on minimizing equipment failures, reducing operational downtime and optimizing asset performance. Manufacturers across the industry increasingly employ predictive maintenance systems with AI, analyzing sensor data, detecting abnormalities, and predicting equipment breakdowns before it can occur. This approach allows for timely and targeted interventions, avoiding costly disruptions for companies and improving overall production efficiency. Key sectors such as automobiles, heavy machinery, energy and power, semiconductor & electronics manufacturing prioritized forecast maintenance, particularly in large and capital-intensive operations where unpredictable outages could result in significant losses.
AI algorithms integrated with IoT and cloud platforms enabled real-time state monitoring and intelligent diagnostics, offering clearer benefits over traditional reactive or time-based maintenance models. The extensive use of AI-driven insights to predict failures, optimize maintenance schedules and reduce spare parts waste has contributed significantly to segment advantage. Additionally, improved return on investment uptime from forecast maintenance, increased lifespan of expanded assets, and reduced labor costs have made it a strategic priority for manufacturers. As factories continue to evolve towards smarter, data-centric operations, predictive maintenance as the most influential AI application in the manufacturing sector in 2024 has firmly maintained its position.
Technology has kept the machine learning segment the largest market share.
In 2024, the Machine Learning segment accounts for the largest share of AI in the manufacturing market, reflecting its central role in enabling data-driven decision-making, process optimization, and adaptation automation across the industry. Manufacturers are increasingly relying on machine learning algorithms to analyze the large amount of operational data generated by sensors, machines and enterprise systems, revealing patterns and trends that traditional methods could not detect. This allowed companies to improve production efficiency, improve quality control and respond quickly to changing market demand.
Industry such as the manufacturing of automobiles, electronics, metals and heavy machinery employs machine learning to drive a wide range of applications, from forecasting demand and predictive maintenance to anomaly detection and process optimization. The ability of the technology to continuously learn and refine models based on real-time data has been particularly valuable in dynamic environments with complex manipulation and high variability. Integrating machine learning with industrial IoT platforms, cloud computing, and edge devices has dramatically expanded its use in both individual and process manufacturing. Automate decision-making, reduce human error, reveal hidden inefficiencies, and enhance the advantage of machine learning as a fundamental AI technology. As manufacturers pursued greater agility, scalability and competitiveness, machine learning emerged as the most widely implemented and impactful technology within AI in manufacturing environments.
Regionally, Europe recorded significant AI growth in the manufacturing market during the forecast period.
Europe is expected to witness significant growth in AI in the manufacturing market, with a focus on industrial modernization, digital innovation and automation-driven competitiveness. Manufacturers will continue to receive AI technology to increase productivity, reduce operational inefficiencies, and meet evolving regulatory and sustainability standards. Government-led initiatives in various European countries have played a key role in accelerating AI integration within the manufacturing sector. Investment in research and development, along with support policies for smart factory development, created an environment that favors AI adoption.
Furthermore, the presence of a highly skilled workforce, sophisticated industrial infrastructure, and an established digital ecosystem has enabled the rapid deployment of AI solutions across the region. European manufacturers are increasingly using AI to enhance production intelligence, implement real-time monitoring and support autonomous decision-making. The focus on quality, accuracy and traceability further accelerated the demand for AI technology that enables continuous improvement and adaptive control. The region is expected to balance industrial innovation and environmental responsibility goals, and adoption of AI is expected to remain a key enabler of manufacturing transformation, strengthening Europe's position as a key contributor to global AI in the manufacturing market.
The key players featured in this report are:
Siemens (Germany), Nvidia Corporation (US), IBM (US), Intel Corporation (US), Ge Vernova (US), Google (US), Micron Technology, Inc (US), Microsoft (US), Amazon Web Services, Inc (US), Rockwell Automation (US), ABB (Switzerland), Honeywell International Inc (US), Cisco Systems (US), Cisco Systems, LP (US), SAP SE (Germany), Mitsubishi Electric Corporation (Japan), Oracle (US), Dassault Systems (France), Site Machine (US), Progress Software Corporation (US), Aquant (US), Bright Machines, Inc. (US), Avathon, Inc. (US), Zebra Technologies Corp. (US).
Important attributes:
| Report attributes | detail |
| Number of pages | 335 |
| Forecast period | 2025-2030 |
| Estimated market value for 2025 | 3.418 billion |
| Market value has been forecast by 2030 | 15.504 billion |
| Combined annual growth rate | 35.3% |
| Covered areas | global |
Market dynamics
driver
- Increased adoption of IIOT and connected devices across manufacturing plants
- Increasing trends towards AI-enabled decisions in manufacturing
- The growing role of expanding intelligence in increasing workforce productivity
Restraint
- Legacy systems have low data integrity and low data availability
- Barriers to enterprise-wide AI deployment in manufacturing
opportunity
- New trends to remotely manage global plants with AI
- Shifting the focus from mass production to smart customization
assignment
- The complexity of tuning AI outputs with dynamic manufacturing environments
- Maintain AI accuracy in dynamic production environments
Value Chain Analysis
- Ecosystem analysis
- Trends/Disruptions that Impact Customer Business
Case study analysis
- Eastman Chemical Company transforms equipment monitoring with AI-driven reliability programs provided by Ge Ververnova
- Harting Technology Group accelerates connector design with AI-powered engineering from Microsoft and Siemens
- Renishaw PLC uses Siemens's NX CAM software to improve accuracy and reduce scrap
- Mitsubishi Motors Corporation transforms operations with IBM for a more efficient and agile future
- Shell uses AI solutions provided by Microsoft and C3.AI to deliver predictive maintenance excellence and scalability
Technical analysis
- Important Technology
- Reinforcement learning
- Augmented, virtual, and mixed reality
- Complementary technology
- Internet of Things (IoT)
- Edge Computing
- Adjacent technology
- Manufacturing of additives
- Digital Twin
The future of AI in manufacturing
- Generated AI and simulation-driven design
- Autonomous and Cooperative Robotics
- Digital twins and AI-led factory plans
- AI-driven sustainability and energy efficiency
- Scaling AI across the manufacturing ecosystem
The company was introduced
- Nvidia Corporation
- IBM
- Siemens
- abb
- Honeywell International Inc.
- Ge Vernova
- Google LLC
- Microsoft
- Micron Technology, Inc.
- Intel Corporation
- Amazon Web Services, Inc.
- Rockwell Automation
- SAP SE
- Oracle
- Mitsubishi Electric Corporation
- PTC
- Schneider Electric
- Cisco Systems, Inc.
- Hewlett Packard Enterprise Development LP
- Dassault System
- Progress Software Corporation
- Zebra Technologies Corp.
- Ubtech Robotics Corp Ltd.
- Aquan
- Bright Machines, Inc.
- Avatton
- Site Machine
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Artificial Intelligence in the Manufacturing Market
