GITNUXREPORT 2025

AI In The Secondary Industry Statistics

AI in secondary manufacturing boosts efficiency, reduces costs, and drives innovation growth.

Jannik Linder

Co-Founder of Gitnux, specialized in content and tech since 2016.

First published: April 29, 2025

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Rigorous fact-checking • Reputable sources • Regular updatesLearn more

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1. The global AI in manufacturing market was valued at $502 million in 2020 and is projected to reach $4.8 billion by 2026, growing at a CAGR of 45.5%

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9. AI-enabled cognitive manufacturing could add $2.2 trillion to the global manufacturing value by 2030

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21. AI is predicted to contribute to reducing manufacturing emissions by 25% through optimized energy use by 2030

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22. 52% of secondary industry manufacturers plan to increase AI R&D expenditure in the next two years

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29. 48% of manufacturing executives believe AI will fundamentally change their industry within the next five years

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38. 50% of secondary industry companies are investing in AI training programs for their workforce, aiming to upskill existing employees

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39. AI is expected to boost secondary manufacturing productivity by an average of 20% across various sectors by 2027

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43. AI applications in secondary industries generated approximately $13 billion in revenue globally in 2022, with an annual growth rate of 50%

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44. 64% of manufacturing executives believe AI will significantly impact supply chain transparency by 2025

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50. By 2024, around 45% of maintenance tasks in manufacturing are expected to be fully automated with AI

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56. 67% of secondary industry firms plan to increase AI adoption for warehouse automation over the next three years

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59. The use of AI in secondary industry manufacturing is forecast to create over 1.3 million new jobs globally by 2030, mainly in technical maintenance and data analysis

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62. Accelerated AI integration in secondary industries is expected to boost manufacturing GDP contribution in rising economies by over 12% by 2030

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69. AI is predicted to fuel a $5 billion increase in secondary industry equipment exports by 2025, through improved manufacturing capabilities

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75. By 2027, AI solutions in secondary industry manufacturing are expected to contribute to a 23% reduction in overall production costs

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7. Manufacturing companies utilizing AI for supply chain optimization saw a 20% reduction in inventory costs

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19. AI-based inventory management systems have reduced stockouts by 40% in manufacturing settings

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41. AI-enabled demand sensing in manufacturing reduces forecast error by an average of 25%, leading to more accurate inventory planning

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52. AI-powered inventory optimization improvements have led to 18% reduction in stockholding costs, year over year

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74. AI-enabled inventory tracking systems enhanced traceability and compliance in secondary industries by 35%, ensuring better regulatory adherence

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6. The adoption rate of AI-powered robots in manufacturing reached 32% in 2022, up from 20% in 2019

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8. 80% of AI investment in the manufacturing sector is directed toward automation and robotics

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10. 54% of manufacturing firms reported increased productivity after integrating AI into their processes

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11. The number of AI patents filed in manufacturing increased by 30% annually between 2018 and 2022

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12. 60% of workers in AI-enabled manufacturing environments receive training in AI and digital tools

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14. AI applications in secondary industry manufacturing grew by 112% from 2021 to 2023

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15. 45% of manufacturing companies reported that AI has significantly improved their product development cycle

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16. AI-driven demand forecasting accuracy has increased by 35% over traditional methods

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17. Approximately 55% of secondary industry manufacturers are using AI for energy consumption optimization

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18. Manufacturing sectors incorporating AI saw an average 15% increase in revenue in the first year of implementation

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20. By 2025, 60% of secondary industries will implement AI-enabled cybersecurity solutions to protect manufacturing data

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24. AI-enabled customized manufacturing orders increased by 27% between 2020 and 2022, indicating growth in flexible production

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25. 68% of secondary industry companies see AI as critical to their digital transformation strategies

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26. Implementing AI-driven logistics management systems reduced shipping costs by 18% in manufacturing

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28. The secondary industry sector's adoption of AI for process design automation increased by 40% in 2022

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32. Secondary industry manufacturers utilizing AI for predictive analytics reported a 25% faster turnaround time on product launches

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33. The number of AI startups focused on manufacturing solutions increased by 150% between 2018 and 2023

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34. 62% of secondary industry sectors plan to expand AI investments to include worker safety monitoring

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36. 83% of manufacturing companies implementing AI report better compliance with safety and regulatory standards

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37. AI-driven supply chain resilience strategies have decreased lead times by approximately 15%

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40. Factories using AI for energy management reported a 12% reduction in utility costs

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42. 69% of secondary industry manufacturers are exploring AI for mass customization processes, driven by consumer demand

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46. 58% of secondary industry companies use AI to analyze customer feedback for product improvement

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48. 74% of secondary industry manufacturers see AI as a key enabler for Industry 4.0 initiatives

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51. 43% of secondary industry manufacturers are investing in AI-based worker safety systems, aiming for zero workplace incidents

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53. 52% of secondary industries employed AI to enhance their logistics route planning, cutting delivery times by 20%

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54. Investment in AI startups serving secondary industries grew by 140% in 2022, indicating strong market confidence

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58. 54% of manufacturing firms reported that AI improved their ability to meet customer delivery deadlines

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61. 55% of secondary industry manufacturers are utilizing AI to develop new materials with improved properties, accelerating innovation cycles

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65. 38% of manufacturing companies are leveraging AI for multilingual communication and coordination across global production sites

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72. 58% of secondary industry companies are exploring AI for enhanced customer personalization and tailored manufacturing solutions

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3. AI-driven predictive maintenance can reduce unplanned downtime by up to 50%

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4. 70% of factories implementing AI reported an increase in overall equipment effectiveness (OEE)

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13. AI-driven process automation in secondary industries has led to an average reduction of process cycle time by 25%

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23. Automation driven by AI has displaced approximately 8% of manufacturing jobs globally, but created 12% new roles in AI maintenance and oversight

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30. 77% of AI-related manufacturing investments are aimed at improving operational efficiency

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31. AI in secondary industry segment is expected to save approximately 600 million worker hours annually by 2030

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35. AI-based simulation tools have improved manufacturing process accuracy by up to 35%, reducing physical prototyping costs

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45. AI-based production scheduling tools reduced machine downtime by an average of 22% across secondary industries

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47. Deployment of AI in secondary industry manufacturing resulted in a 30% reduction in waste material over three years

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49. AI-driven process optimization tools contributed to a 15% increase in factory throughput

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55. AI-enabled predictive analytics improved maintenance scheduling efficiency by 35%, reducing maintenance costs significantly

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60. AI-driven systems in production lines decreased energy consumption by 10% on average, contributing to sustainability goals

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64. AI-powered digital twins in manufacturing have improved process planning accuracy by 30%, reducing prototyping costs

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66. AI has contributed to a 27% reduction in scrap rates in secondary industry manufacturing processes, optimizing material usage

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67. 49% of secondary industry companies revealed AI-assisted design tools cut time-to-market for new products by up to 25%

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68. The adoption of AI for real-time monitoring in manufacturing plants increases operational uptime by approximately 14%

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70. 71% of secondary industry manufacturers are investing in AI tools for workforce scheduling and labor optimization, aiming to improve efficiency

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71. Use of AI in secondary industries is projected to reduce product development costs by 20%, enabling faster innovation

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2. 65% of manufacturing companies have adopted AI technologies to improve production quality

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5. The use of AI for quality inspection in manufacturing has improved defect detection accuracy by up to 98%

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27. AI-based defect detection systems have decreased false positive rates by up to 70% compared to manual inspections

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57. AI-enhanced product defect detection systems reduced recall incidents by 25% in manufacturing environments

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63. 66% of secondary industries consider AI surveillance and monitoring as essential for maintaining manufacturing quality standards

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73. Implementation of AI for end-of-line quality inspection increased throughput by 18% in manufacturing plants, reducing bottlenecks

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Key Highlights

1. The global AI in manufacturing market was valued at $502 million in 2020 and is projected to reach $4.8 billion by 2026, growing at a CAGR of 45.5%
2. 65% of manufacturing companies have adopted AI technologies to improve production quality
3. AI-driven predictive maintenance can reduce unplanned downtime by up to 50%
4. 70% of factories implementing AI reported an increase in overall equipment effectiveness (OEE)
5. The use of AI for quality inspection in manufacturing has improved defect detection accuracy by up to 98%
6. The adoption rate of AI-powered robots in manufacturing reached 32% in 2022, up from 20% in 2019
7. Manufacturing companies utilizing AI for supply chain optimization saw a 20% reduction in inventory costs
8. 80% of AI investment in the manufacturing sector is directed toward automation and robotics
9. AI-enabled cognitive manufacturing could add $2.2 trillion to the global manufacturing value by 2030
10. 54% of manufacturing firms reported increased productivity after integrating AI into their processes
11. The number of AI patents filed in manufacturing increased by 30% annually between 2018 and 2022
12. 60% of workers in AI-enabled manufacturing environments receive training in AI and digital tools
13. AI-driven process automation in secondary industries has led to an average reduction of process cycle time by 25%

Artificial intelligence is revolutionizing the secondary manufacturing industry at an unprecedented pace, with projections indicating a tenfold increase in market value by 2026 and transformative impacts that boost productivity, reduce costs, and drive innovation across global factories.

Industry Projections and Future Trends

1. The global AI in manufacturing market was valued at $502 million in 2020 and is projected to reach $4.8 billion by 2026, growing at a CAGR of 45.5%
9. AI-enabled cognitive manufacturing could add $2.2 trillion to the global manufacturing value by 2030
21. AI is predicted to contribute to reducing manufacturing emissions by 25% through optimized energy use by 2030
22. 52% of secondary industry manufacturers plan to increase AI R&D expenditure in the next two years
29. 48% of manufacturing executives believe AI will fundamentally change their industry within the next five years
38. 50% of secondary industry companies are investing in AI training programs for their workforce, aiming to upskill existing employees
39. AI is expected to boost secondary manufacturing productivity by an average of 20% across various sectors by 2027
43. AI applications in secondary industries generated approximately $13 billion in revenue globally in 2022, with an annual growth rate of 50%
44. 64% of manufacturing executives believe AI will significantly impact supply chain transparency by 2025
50. By 2024, around 45% of maintenance tasks in manufacturing are expected to be fully automated with AI
56. 67% of secondary industry firms plan to increase AI adoption for warehouse automation over the next three years
59. The use of AI in secondary industry manufacturing is forecast to create over 1.3 million new jobs globally by 2030, mainly in technical maintenance and data analysis
62. Accelerated AI integration in secondary industries is expected to boost manufacturing GDP contribution in rising economies by over 12% by 2030
69. AI is predicted to fuel a $5 billion increase in secondary industry equipment exports by 2025, through improved manufacturing capabilities
75. By 2027, AI solutions in secondary industry manufacturing are expected to contribute to a 23% reduction in overall production costs

Industry Projections and Future Trends Interpretation

As AI accelerates from a $502 million startup in 2020 to a projected $4.8 billion industry by 2026, it’s clear that manufacturers who don’t embrace cognitive automation risk being left behind—unless they’re willing to see their cost savings, emissions, and productivity soar while creating over a million new jobs and adding trillions to the global economy by 2030.

Inventory and Supply Chain Management

7. Manufacturing companies utilizing AI for supply chain optimization saw a 20% reduction in inventory costs
19. AI-based inventory management systems have reduced stockouts by 40% in manufacturing settings
41. AI-enabled demand sensing in manufacturing reduces forecast error by an average of 25%, leading to more accurate inventory planning
52. AI-powered inventory optimization improvements have led to 18% reduction in stockholding costs, year over year
74. AI-enabled inventory tracking systems enhanced traceability and compliance in secondary industries by 35%, ensuring better regulatory adherence

Inventory and Supply Chain Management Interpretation

As AI infiltrates the secondary industry, manufacturing firms are slashing inventory costs by up to 20%, reducing stockouts by 40%, shrinking forecast errors by 25%, trimming stockholding expenses by 18%, and boosting traceability by 35%—proving that intelligent automation isn't just about cutting costs but also about smarter, more compliant, and more responsive supply chains.

Market Adoption and Implementation

6. The adoption rate of AI-powered robots in manufacturing reached 32% in 2022, up from 20% in 2019
8. 80% of AI investment in the manufacturing sector is directed toward automation and robotics
10. 54% of manufacturing firms reported increased productivity after integrating AI into their processes
11. The number of AI patents filed in manufacturing increased by 30% annually between 2018 and 2022
12. 60% of workers in AI-enabled manufacturing environments receive training in AI and digital tools
14. AI applications in secondary industry manufacturing grew by 112% from 2021 to 2023
15. 45% of manufacturing companies reported that AI has significantly improved their product development cycle
16. AI-driven demand forecasting accuracy has increased by 35% over traditional methods
17. Approximately 55% of secondary industry manufacturers are using AI for energy consumption optimization
18. Manufacturing sectors incorporating AI saw an average 15% increase in revenue in the first year of implementation
20. By 2025, 60% of secondary industries will implement AI-enabled cybersecurity solutions to protect manufacturing data
24. AI-enabled customized manufacturing orders increased by 27% between 2020 and 2022, indicating growth in flexible production
25. 68% of secondary industry companies see AI as critical to their digital transformation strategies
26. Implementing AI-driven logistics management systems reduced shipping costs by 18% in manufacturing
28. The secondary industry sector's adoption of AI for process design automation increased by 40% in 2022
32. Secondary industry manufacturers utilizing AI for predictive analytics reported a 25% faster turnaround time on product launches
33. The number of AI startups focused on manufacturing solutions increased by 150% between 2018 and 2023
34. 62% of secondary industry sectors plan to expand AI investments to include worker safety monitoring
36. 83% of manufacturing companies implementing AI report better compliance with safety and regulatory standards
37. AI-driven supply chain resilience strategies have decreased lead times by approximately 15%
40. Factories using AI for energy management reported a 12% reduction in utility costs
42. 69% of secondary industry manufacturers are exploring AI for mass customization processes, driven by consumer demand
46. 58% of secondary industry companies use AI to analyze customer feedback for product improvement
48. 74% of secondary industry manufacturers see AI as a key enabler for Industry 4.0 initiatives
51. 43% of secondary industry manufacturers are investing in AI-based worker safety systems, aiming for zero workplace incidents
53. 52% of secondary industries employed AI to enhance their logistics route planning, cutting delivery times by 20%
54. Investment in AI startups serving secondary industries grew by 140% in 2022, indicating strong market confidence
58. 54% of manufacturing firms reported that AI improved their ability to meet customer delivery deadlines
61. 55% of secondary industry manufacturers are utilizing AI to develop new materials with improved properties, accelerating innovation cycles
65. 38% of manufacturing companies are leveraging AI for multilingual communication and coordination across global production sites
72. 58% of secondary industry companies are exploring AI for enhanced customer personalization and tailored manufacturing solutions

Market Adoption and Implementation Interpretation

As AI's footprint in manufacturing has expanded by over 112% since 2021, industry leaders are confidently trading traditional processes for smarter, faster, and more resilient factories—proving that when it comes to Industry 4.0, AI isn't just an upgrade; it's the blueprint for staying competitive in a rapidly transforming world.

Operational Efficiency and Maintenance

3. AI-driven predictive maintenance can reduce unplanned downtime by up to 50%
4. 70% of factories implementing AI reported an increase in overall equipment effectiveness (OEE)
13. AI-driven process automation in secondary industries has led to an average reduction of process cycle time by 25%
23. Automation driven by AI has displaced approximately 8% of manufacturing jobs globally, but created 12% new roles in AI maintenance and oversight
30. 77% of AI-related manufacturing investments are aimed at improving operational efficiency
31. AI in secondary industry segment is expected to save approximately 600 million worker hours annually by 2030
35. AI-based simulation tools have improved manufacturing process accuracy by up to 35%, reducing physical prototyping costs
45. AI-based production scheduling tools reduced machine downtime by an average of 22% across secondary industries
47. Deployment of AI in secondary industry manufacturing resulted in a 30% reduction in waste material over three years
49. AI-driven process optimization tools contributed to a 15% increase in factory throughput
55. AI-enabled predictive analytics improved maintenance scheduling efficiency by 35%, reducing maintenance costs significantly
60. AI-driven systems in production lines decreased energy consumption by 10% on average, contributing to sustainability goals
64. AI-powered digital twins in manufacturing have improved process planning accuracy by 30%, reducing prototyping costs
66. AI has contributed to a 27% reduction in scrap rates in secondary industry manufacturing processes, optimizing material usage
67. 49% of secondary industry companies revealed AI-assisted design tools cut time-to-market for new products by up to 25%
68. The adoption of AI for real-time monitoring in manufacturing plants increases operational uptime by approximately 14%
70. 71% of secondary industry manufacturers are investing in AI tools for workforce scheduling and labor optimization, aiming to improve efficiency
71. Use of AI in secondary industries is projected to reduce product development costs by 20%, enabling faster innovation

Operational Efficiency and Maintenance Interpretation

AI in the secondary industry is transforming manufacturing from reactive repairs to predictive precision, slashing downtime and waste while simultaneously creating new specialized roles, proving that smart automation isn't just an efficiency boost—it's a strategic revolution.

Quality Control and Inspection

2. 65% of manufacturing companies have adopted AI technologies to improve production quality
5. The use of AI for quality inspection in manufacturing has improved defect detection accuracy by up to 98%
27. AI-based defect detection systems have decreased false positive rates by up to 70% compared to manual inspections
57. AI-enhanced product defect detection systems reduced recall incidents by 25% in manufacturing environments
63. 66% of secondary industries consider AI surveillance and monitoring as essential for maintaining manufacturing quality standards
73. Implementation of AI for end-of-line quality inspection increased throughput by 18% in manufacturing plants, reducing bottlenecks

Quality Control and Inspection Interpretation

With over two-thirds of secondary industries embracing AI for quality control—raising defect detection accuracy to nearly 98%, slashing false positives by 70%, and boosting throughput by 18%—it's clear that AI isn't just an upgrade, but the new standard for manufacturing excellence.