AI in Manufacturing Statistics By Industry, Fields, Usage, Platforms and Benefits

Introduction

AI in Manufacturing Statistics: Artificial Intelligence (AI) is changing how factories work worldwide. It helps machines learn from data, make smart decisions, and do jobs better and faster. In manufacturing, AI checks product quality, controls machines, and plans production more smoothly. This leads to safer workplaces, less waste, and lower costs.

Many businesses are now using AI to stay strong in the market. Because of this, the use of AI in factories is growing quickly. This article shares the latest numbers to show how AI is being used in manufacturing and the improvements it brings. Understanding these numbers helps us see the real impact of AI in modern manufacturing.

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• According to World Metrics’ reports, the global AI in manufacturing market will reach USD 16.7 billion by 2025.
• 2035 AI is expected to increase manufacturing productivity by up to 30%.
• Using AI for predictive maintenance can reduce maintenance costs by up to 40% and unplanned downtime by 50%.
• AI-powered quality control systems can reduce product defects by up to 90%.
• AI-driven energy management can cut energy consumption in manufacturing facilities by up to 20%.
• AI can reduce supply chain forecasting errors by up to 50%, resulting in more effective inventory management.
• AI in manufacturing Statistics also estimated that the market will create 2.3 million new jobs by 2025.
• Implementing AI could save the manufacturing industry up to USD 421 billion during the same period.
• Approximately 62% of manufacturers have implemented or plan to implement AI in their operations.
• AI-based quality control systems can detect defects with an accuracy of over 95%.

Current Market Statistics of AI in Manufacturing

• Statista survey reported that companies utilizing AI will likely experience an average income growth of 6% to 10%.
• Over the next decade, AI could help workers become more productive, potentially boosting productivity growth by 1.5 percentage points.
• According to a Gartner report (October 2023), 55% of businesses were already testing or using generative AI tools.
• A survey by Forbes Advisor revealed that 64% of companies believe AI will enable them to accomplish more work.
• According to IBM, approximately 1 in 4 companies (25%) now use AI to address labour shortages.
• 93% of companies believe AI is the most important technology for driving manufacturing growth and introducing new ideas.
• A recent survey by Pwc found that 54% of companies in India now use more artificial intelligence (AI) and data analytics.
• Deloitte’s survey revealed that 93% of manufacturers believe AI will be a key technology for generating new and innovative ideas in the future.
• According to a 2023 report by Rockwell, 59% of Indian companies plan to transition towards smart manufacturing.
• It also showed that manufacturers in India are allocating approximately 35% of their operating budgets to new technologies.
• McKinsey predicts that by 2030, AI in manufacturing could contribute to a nearly 19% increase in China’s economy.
• Many AI projects, ranging from 60% to 80%, are not working out as planned and fail to succeed.
• By 2035, AI could help factories become 40% more productive.
• Using AI for predictive maintenance may lower repair costs by up to 30% and reduce unexpected machine stops by 45%.
• AI tools can now take over tasks that currently use 60 to 70% of a worker’s time.

Types of AI in Manufacturing Statistics

AI in Manufacturing Market Share by Deployment

• By 2025, over 60% of new factory products will use generative AI to help with design and early ideas.
• The generative AI market in manufacturing could grow to USD 10.5 billion by 2033
• About 30% of big manufacturing companies (with more than USD 10 billion in yearly revenue) are already using generative AI and getting good results.
• Around 10% of medium-sized companies (earning between USD 500 million and USD 10 billion) have also adopted generative AI and seen positive impacts.
• On-premises deployment makes up 57% of the total market, while cloud-based deployment holds the remaining 43% share.

AI in Manufacturing Market Statistics

(Source: shortpixel.ai)

• The global AI in manufacturing market was valued at approximately USD 5.5 billion in 2024 and is projected to reach USD 80 billion by 2030.
• It is expected to grow quickly and reach nearly USD 156.1 billion by 2033, with a 45% yearly growth rate.
• The financial benefits of AI in manufacturing are growing rapidly. The market was valued at around USD 3.8 billion in 2023 and is expected to increase to approximately USD 24.4 billion by 2028.
• AI tools that aid decision-making can increase factory efficiency by up to 20%.
• When factories utilise AI for predictive maintenance, they can reduce maintenance costs by approximately 25% and experience 70% fewer machine breakdowns.
• Additionally, AI-powered quality checks can increase factory productivity by up to 50% and detect product defects with 90% accuracy.
• In 2023, the software segment of the AI market led the way, accounting for more than 47.3% of the market.

By Region

(Reference: precedenceresearch.com)

• North America was the leading region for AI in manufacturing, with a significant market share of over 34%.
• Furthermore, the market shares of other regions are as follows: Europe (30%), Asia Pacific (26%), Latin America (6%), and the Middle East and Africa (MEA) (4%).

By Offerings

(Reference: precedenceresearch.com)

• As of 2024, the hardware segment is predicted to hold the largest share, 48%, over AI in the manufacturing industry.
• Meanwhile, the software and Services segment captured almost 32% and 20%, respectively.

United States AI in Manufacturing Market Statistics

(Reference: precedenceresearch.com)

• The Precedence Research report shows that in 2024, the size of the U.S. AI in manufacturing market is estimated to be USD 1.41 billion and will reach USD 2.04 billion by the end of 2025.
• It is expected to grow sharply to around USD 56.17 billion by 2034, with a fast yearly growth rate of 44.55%.

By Fields

(Reference: labelyourdata.com)

• AI is widely used in smart manufacturing, particularly for tasks such as automation, order handling, and work scheduling. It now accounts for 51% of these activities, with robotics playing a significant role in this proportion.
• Approximately 25% of businesses have incorporated AI into their products and services. They primarily use it to accelerate design, enhance customer satisfaction with their service, and increase the effectiveness of their marketing efforts.
• Most companies using AI today focus on energy and employee management, and use it in finance. Further growth is anticipated in these areas.
• AI is slowly growing in supply chain work, with a share of just 4%. It facilitates delivery tracking, demand management, and future predictions.
• In factories, AI helps with informed decisions about customer service and reduces costs, but its current usage accounts for only about 4%.

By Adoption Rate

• According to a Forbes Advisor survey, 64% of businesses think artificial intelligence will boost productivity.
• By 2030, it’s predicted that 10% of all vehicles will be driverless.
• The global market for self-driving cars is projected to grow from 20.3 million units in 2021 to 62.4 million units by 2026.
• According to Grand View Research, artificial intelligence (AI) is transforming numerous industries and is projected to grow 36.6% annually from 2023 to 2030.
• Almost 72% of businesses utilise AI for at least one aspect of their operations.
• India has the highest AI adoption rate, with 59% of manufacturers using it.
• The United Arab Emirates follows closely at 58%. Singapore (53%) and China (50%) also lead in AI adoption.
• On the other hand, countries such as Australia (29%), Spain (28%), and France (26%) are slower to adopt AI in their businesses.
• The healthcare and automotive industries have the highest long-term adoption rates for AI, with 40% in healthcare and 18% in automotive.

By Usage

• Over 70% of respondents say they have implemented some form of AI into operations, with top applications.
• Organisations currently using AI in manufacturing include production (31%), employee training (24%), customer service (23%), engineering (20%), production planning (19%), cybersecurity (18%) and inventory management (17%).
• Automation is the most commonly used type of AI manufacturing, with a share of 60%, followed by predictive AI (37%) and generative AI (35%).
• The top 5 benefits of using AI in manufacturing are improved efficiency (44%), improved productivity (42%), production efficiency (29%), greater uptime (20%), and quality assurance.

By Regional Analyses

(Reference: allaboutai.com)

• The United States leads with 266 mentions, showing its strong position in AI-powered manufacturing due to advanced research and industry.
• India comes next with 182 mentions, highlighting its fast digital growth and interest in automation.
• Australia had 17 mentions, focusing on innovation and efficiency.
• The UK, with 12 mentions, is using AI for smart and eco-friendly production.
• Germany received nine mentions, proving its strategic use of AI to stay ahead globally. Canada (8 mentions) is moving toward greener and smarter manufacturing.
• The UAE (6 mentions) is building itself as a centre for high-tech AI factories.
• Nigeria (5 mentions) shows Africa’s AI push.
• Taiwan (4 mentions) leads in chip-making AI.
• Singapore (2 mentions) uses AI in targeted factory roles.

Who Will AI Help or Harm in Manufacturing?

(Reference: statista.com)

• Half of the employers (50%) think AI will help workers with disabilities, while only 12% believe it could hurt them.
• Low-skilled workers might get help from AI (37%), but 25% of employers worry it may harm them too.
• Older workers could benefit from AI (36%), but 27% of employers think AI might make things harder for them.
• Female workers are seen as likely to benefit from AI, with 35% saying it will help them and only 4% saying it will harm them.
• Migrant workers may see some support from AI (29%), while 11% could face challenges.
• Workers from ethnic minorities are expected to benefit from AI (25%), and only 7% of employers think AI will harm them.

Top Platforms Driving AI in Manufacturing Conversations

Key Statistics on AI Implementation in Manufacturing by Function

• A study of four manufacturing areas found that most AI use is focused on maintenance (29%) and improving product quality (27%).
• Currently, 57% of manufacturers are testing or trying out AI tools in different parts of their operations.
  Although many companies are working on AI in specific teams or departments, only 29% have made AI part of their official company-wide strategy.

Benefits of Adopting AI in Manufacturing

(Reference: allaboutai.com)

• Forbes Advisory says 56% of companies already use AI tools to boost their operations.
• In 2023, 35% of manufacturers were using AI, especially for quality checks and predicting machine issues.
• AI in Manufacturing Statistics states that around 41% use AI to track supply chain data better.
• Meanwhile, 27% have seen real benefits, and 56% believe they’ll see results within 2 to 5 years.
• About 60% of big U.S. car makers use AI differently.
• Using AI, manufacturers have cut production time by 50%, and General Electric has lowered machine downtime by 10 to 20%.
• By 2024, AI may cut maintenance costs by 25% and prevent 30% of sudden breakdowns.

Sustainable Impact of AI in Manufacturing Statistics

• AI-driven predictive maintenance can reduce energy consumption by up to 15% in industrial settings.
• Implementing AI in production processes has led to a 4% decrease in material waste, enhancing resource utilisation.
• AI applications in manufacturing have contributed to significant CO2 emission reductions, with examples like ADNOC abating up to 1 million tonnes between 2022 and 2023.
• Data centres supporting AI operations are projected to consume up to 6.6 billion cubic meters of water by 2027.
• AI-enhanced supply chains have reduced excess inventory by up to 30%, minimising waste and emissions from overproduction.
• Integrating AI and Iot in manufacturing has led to an 18% reduction in energy consumption and a 22% decrease in machine downtime.

Conclusion

AI is transforming the way manufacturing works by making machines smarter and processes more efficient. It helps reduce mistakes, saves time, and improves product quality. With AI, companies can find problems early and fix them quickly, resulting in lower costs and improved customer service. As technology advances, more factories will utilise AI to remain competitive. Overall, AI is becoming a big part of making things better and smarter.