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The Global Market for Artificial Intelligence (AI) 2022

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Published February 2022 | 540 pages, 22 figures, 72 tables | Table of contents

The development of artificial intelligence (AI) technologies is growing rapidly and transforming the global economy. AI uses data and algorithms to replicate human decision/thinking ability and can optimise the efficiency, precision, and performance of many existing technologies.

AI and human‐machine interaction, in combination with other digitisation technologies, are being increasingly utilized in production and logistics as well as the analysis of markets, customer behaviour, and sales. Advances in machine learning and neural networks have completely changed the AI technology environment over the past decade and the he availability of huge datasets and technology advances in Big Data, the Internet of Things (IoT) and fast connectivity have enabled new AI systems and services, digital assistants, robots and drones.

The development and application of these technologies is an industry in its own right, but AI is also transforming business models across many sectors such as financial services, Information and Communication Technology (ICT), Life Science, Retail, Healthcare, Industrial Manufacturing, Automotive, Security, Oil & Gas, and Chemicals.

Report contents include: 

  • Artificial intelligence (AI) technology analysis. 
  • Analysis of the global market and technologies for artificial intelligence (AI). 
  • Artificial intelligence (AI) value chain, by industry. 
  • Revenues for artificial intelligence (AI) technologies and markets. 
  • Market outlook over the next 10 years and beyond. 
  • Discussion on market drivers, restraints, current trends and investments in the artificial intelligence market
  • Analysis of recent mergers & acquisitions, joint ventures, collaborations or partnerships, funding, investments and significant news, from 2020-2022. 
  • In depth market analysis of AI in manufacturing, automotive and transportation, construction, energy, education, chemicals, medical devices & healthcare, food & agriculture, financial services, smart homes, consumer devices, retail, sales & CRM, waste management, Information & communications technology (ICT), computer vision & facial recognition, AI processors, cybersecurity and electronic noses. 
  • Competitive landscape including key AI players
  • Global government AI initiatives, policy & regulations
  • In depth profiles of 400 companies. Profiles include technology focus, products, markets targeted, funding and investors. Companies profiled include Spectrum Labs, 6sense, 7bridges, Personetics, Scale AI, Cohere, Babylon Health, Hive, XtalPi, ASAPP, Aibee, SmartMore, BenevolentAI, iCarbonX, Globality, Intellifusion, Groq Inc, Entos, Holomatic, Covariant, AiFi, Nnaisense etc. 

1              EXECUTIVE SUMMARY   28

  • 1.1          What is Artificial Intelligence (AI)?            28
    • 1.1.1      Artificial Narrow Intelligence       31
    • 1.1.2      Artificial General Intelligence      32
    • 1.1.3      Artificial Super Intelligence          33
  • 1.2          Current market for AI     33
    • 1.2.1      Key trends in AI in 2021  35
    • 1.2.2      Maturity level of AI by industry  38
    • 1.2.3      Market revenues forecast by industry 2020-2030, billions USD     40
    • 1.2.4      Global AI software revenues 2020-2030, billions USD       41
    • 1.2.5      Global AI Hardware revenues 2020-2030, billions USD     42
  • 1.3          Market outlook five years             42
  • 1.4          Market outlook ten years and beyond    43
    • 1.4.1      AI players and target markets     45
    • 1.4.2      Publicly listed AI companies        46
  • 1.5          Market challenges           51

 

2              TECHNOLOGY ANALYSIS 52

  • 2.1          AI networks and tools     52
  • 2.2          Types of Artificial Intelligence     54
    • 2.2.1      AI Based on Functionality              54
    • 2.2.2      AI Based on Capability    56
  • 2.3          Key Technologies of Artificial Intelligence              58
      • 2.3.1      Machine learning             59
      • 2.3.1.1   Supervised learning        59
      • 2.3.1.2   Unsupervised learning   60
      • 2.3.1.3   Reinforcement learning 60
      • 2.3.1.4   Graph machine learning 62
      • 2.3.1.5   Tiny machine learning (TinyML) 63
      • 2.3.1.6   Deep learning    64
        • 2.3.1.6.1               Neural Networks              64
          • 2.3.1.6.1.1           Transformer neural networks     65
    • 2.3.2      Computer vision               66
    • 2.3.3      Natural Language Processing      67
    • 2.3.4      Robotics               69
    • 2.3.5      Knowledge-based systems           70
    • 2.3.6      Optimisation      70
    • 2.3.7      Hybrid AI Systems           71
    • 2.3.8      No-code AI         76

 

3              MARKETS AND APPLICATIONS    79

  • 3.1          Market trends and drivers            79
  • 3.2          Recent market developments in Artificial Intelligence 2020-2022                 81
  • 3.3          AI Funding and investments 2020-2022   87
  • 3.4          AI in Manufacturing        97
    • 3.4.1      Market drivers  97
    • 3.4.2      AI in the manufacturing value chain         98
    • 3.4.3      Applications       99
      • 3.4.3.1   Inspection systems and Predictive & Preventative Maintenance 100
      • 3.4.3.2   Worker safety   101
      • 3.4.3.3   Supply chain & logistics  102
      • 3.4.3.4   Robotics               104
      • 3.4.3.5   Quality control  104
    • 3.4.4      Companies         106
  • 3.5          AI in Automotive and Transportation       108
    • 3.5.1      Market drivers  109
    • 3.5.2      AI in the automotive value chain                109
    • 3.5.3      Applications       110
      • 3.5.3.1   AI in Automotive Manufacturing               111
        • 3.5.3.1.1               Companies         112
      • 3.5.3.2   Autonomous vehicles    112
        • 3.5.3.2.1               Deep learning-based image recognition for autonomous driving 114
        • 3.5.3.2.2               Hybrid AI             115
        • 3.5.3.2.3               Companies         115
      • 3.5.3.3   Vehicle fleet management           116
        • 3.5.3.3.1               Companies         116
      • 3.5.3.4   Rail         119
      • 3.5.3.5   Aviation               120
  • 3.6          AI in Construction            122
    • 3.6.1      Market drivers  122
    • 3.6.2      AI in the construction value chain              122
    • 3.6.3      Applications       123
      • 3.6.3.1   Resource and waste optimisation              124
      • 3.6.3.2   Supply chain management          124
      • 3.6.3.3   Health and safety            124
      • 3.6.3.4   Construction site analytics            125
    • 3.6.4      Companies         125
  • 3.7          AI in Energy        127
    • 3.7.1      Market drivers  127
    • 3.7.2      AI in the energy value chain         128
    • 3.7.3      Applications       129
      • 3.7.3.1   Renewables       129
      • 3.7.3.2   Oil and gas          130
      • 3.7.3.3   AI home energy management    131
      • 3.7.3.4   Smart grid           131
    • 3.7.4      Companies         131
  • 3.8          AI in Education  133
    • 3.8.1      Market drivers  134
    • 3.8.2      Applications       135
    • 3.8.3      Companies         135
  • 3.9          AI in Chemicals  136
    • 3.9.1      Market drivers  137
    • 3.9.2      Applications       138
    • 3.9.3      Companies         139
  • 3.10        AI in Medical devices and Healthcare       141
    • 3.10.1    Market drivers  142
    • 3.10.2    AI in the medical devices and healthcare value chain        144
    • 3.10.3    Applications       144
      • 3.10.3.1                Pharmaceuticals               144
        • 3.10.3.1.1             Drug discovery and development             145
        • 3.10.3.1.2             Companies         147
        • 3.10.3.1.3             Challenges of AI in pharmaceuticals         148
      • 3.10.3.2                Medical diagnostics-cancer detection     149
        • 3.10.3.2.1             Companies         151
      • 3.10.3.3                Medical diagnostics-cardiovascular disease          151
        • 3.10.3.3.1             Companies         153
      • 3.10.3.4                Medical diagnostics- respiratory disease 153
        • 3.10.3.4.1             Companies         155
      • 3.10.3.5                Medical diagnostics- retinal disease         155
        • 3.10.3.5.1             Companies         156
      • 3.10.3.6                Medical diagnostics- neurodegenerative diseases             157
        • 3.10.3.6.1             Companies         158
      • 3.10.3.7                Medical diagnostics- retinal diseases       159
        • 3.10.3.7.1             Companies         159
      • 3.10.3.8                Patient monitoring          159
        • 3.10.3.8.1             Companies         159
  • 3.11        AI in Food and Agriculture            160
    • 3.11.1    Market drivers  161
    • 3.11.2    AI in the food and agriculture value chain              161
    • 3.11.3    Applications       162
      • 3.11.3.1                Deep Learning in agriculture        162
      • 3.11.3.2                Agricultural drones         162
      • 3.11.3.3                Indoor farming  163
      • 3.11.3.4                Food production               163
        • 3.11.3.4.1             Traceability to manage waste     163
        • 3.11.3.4.2             Food identification and sorting   164
        • 3.11.3.4.3             Food packaging 164
        • 3.11.3.4.4             Food processing               165
      • 3.11.3.5                Self-Driving Tractors        165
      • 3.11.3.6                Companies         165
  • 3.12        AI in Financial Services   169
    • 3.12.1    Market drivers  169
    • 3.12.2    Applications       170
    • 3.12.3    Companies         171
  • 3.13        AI in Smart homes           175
    • 3.13.1    Market drivers  176
    • 3.13.2    Applications       176
      • 3.13.2.1                Home security   176
      • 3.13.2.2                Daily household activities             177
      • 3.13.2.3                Autonomous HVAC         178
      • 3.13.2.4                Household energy           178
    • 3.13.3    Companies         178
  • 3.14        AI in Consumer devices 179
    • 3.14.1    Market drivers  179
    • 3.14.2    Applications       180
    • 3.14.3    Companies         181
  • 3.15        AI in Retail, Sales and CRM           182
    • 3.15.1    Market drivers  182
    • 3.15.2    Applications       183
    • 3.15.3    Companies         185
  • 3.16        AI in waste management              189
    • 3.16.1    Market drivers  189
    • 3.16.2    Applications       190
    • 3.16.3    Companies         191
  • 3.17        AI in Information and communications technology (ICT) 193
    • 3.17.1    AI Processors     194
      • 3.17.1.1                Companies         194
    • 3.17.2    AI in computer vision and facial recognition          195
      • 3.17.2.1                Market drivers  195
      • 3.17.2.2                Applications       196
      • 3.17.2.3                Companies         197
    • 3.17.3    AI in Cybersecurity          197
      • 3.17.3.1                Applications       197
      • 3.17.3.2                Companies         198
  • 3.18        AI in Electronic noses     200
    • 3.18.1.1                Applications       200
    • 3.18.1.2                Companies         201

 

4              GOVERNMENT AI INITIATIVES, POLICY & REGULATIONS 203

  • 4.1          United States     203
  • 4.2          Canada 205
  • 4.3          Europe 206
  • 4.4          Asia-Pacific         207

 

5              ARTIFICAL INTELLIGENCE COMPANY PROFILES    209

 

6              DEFUNCT AI COMPANIES              534

 

7              RESEARCH SCOPE AND METHODOLOGY 535

  • 7.1          Report scope     535
  • 7.2          Research methodology 536

 

8              REFERENCES       537

List of Tables

  • Table 1. Narrow AI vs. General AI.             32
  • Table 2. Key trends in AI in 2021.               36
  • Table 3. Publicly listed AI companies.      46
  • Table 4. Market challenges for Artificial Intelligence.        51
  • Table 5. AI based on Functionality.           54
  • Table 6. AI Based on Capability.  56
  • Table 7. No-code AI players.        76
  • Table 8. Market trends and drivers in AI. 79
  • Table 9. Recent market developments in Artificial Intelligence 2020-2022                81
  • Table 10. AI Funding and investments 2020-2022.              87
  • Table 11. Market drivers for use of Artificial Intelligence in manufacturing.            97
  • Table 12. Applications of AI in manufacturing.     99
  • Table 13. Companies developing AI in manufacturing.     106
  • Table 14. Market drivers for use of Artificial Intelligence in automotive and transportation.            109
  • Table 15. Applications of AI in automotive and transportation.     110
  • Table 16. Companies developing AI for Automotive Manufacturing.          112
  • Table 17. Companies developing AI for autonomous vehicles.      115
  • Table 18. Companies developing AI for vehicle fleet management.            116
  • Table 19. Companies developing AI for vehicle fleet management vehicles             117
  • Table 20. Market drivers for use of Artificial Intelligence in construction. 122
  • Table 21. Applications of AI in construction.         123
  • Table 22. Companies developing AI for construction.        125
  • Table 23. Market drivers for use of Artificial Intelligence in energy.            127
  • Table 24. Application of AI in renewable energy. 129
  • Table 25. Applications of AI in the Oil and Gas sector.      130
  • Table 26. Companies developing AI in energy.     132
  • Table 27. Market drivers for AI in education.        134
  • Table 28. Applications of AI in Education.               135
  • Table 29. Companies developing AI in education.               135
  • Table 30. Market drivers for AI in the chemicals market. 137
  • Table 31. Applications of AI in the chemicals market         138
  • Table 32. Companies developing AI in the chemicals market.        140
  • Table 33. Market drivers for use of Artificial Intelligence in medical devices and healthcare.           142
  • Table 34. Applications of AI in medical devices and healthcare market.    144
  • Table 35. AI Methods in Drug Discovery and development.           146
  • Table 36. AI tools used in drug discovery,              146
  • Table 37. Companies developing AI in pharmaceuticals.  147
  • Table 38. Challenges of AI in pharmaceuticals.     148
  • Table 39. Companies developing AI for medical diagnostics.          151
  • Table 40. Companies developing AI for cardiovascular disease.    153
  • Table 41. Companies developing AI for respiratory disease.           155
  • Table 42. Companies developing AI for retinal disease.    156
  • Table 43. Companies developing AI for neurodegenerative diseases.        158
  • Table 44. Companies developing AI for retinal disease.    158
  • Table 45. Companies developing AI for Patient monitoring             159
  • Table 46. Market drivers for use of Artificial Intelligence in food and agriculture. 160
  • Table 47. Applications of AI in food and agriculture.          162
  • Table 48. Companies developing AI for agriculture.           165
  • Table 49. Market drivers for use of Artificial Intelligence in financial services.        169
  • Table 50. Applications of AI in financial services. 170
  • Table 51. Companies developing AI for the financial services.       171
  • Table 52. Market drivers for use of Artificial Intelligence in smart homes. 175
  • Table 53. Applications of AI in smart homes.        175
  • Table 54. Companies developing AI for smart homes.      178
  • Table 55. Market drivers for use of Artificial Intelligence in consumer devices.      179
  • Table 56. Applications of AI in consumer devices.              180
  • Table 57. Companies developing AI for consumer devices.             181
  • Table 58. Market drivers for use of Artificial Intelligence in retail, sales and CRM. 182
  • Table 59. Applications of AI in retail, sales and CRM.         183
  • Table 60. Companies developing AI in retail, sales and CRM.         185
  • Table 61. Market drivers for use of Artificial Intelligence in waste management.  189
  • Table 62. Applications of AI in waste management.          190
  • Table 63. Companies developing AI in waste management.           191
  • Table 64. AI Processors companies.          194
  • Table 65. Market drivers for use of Artificial Intelligence in computer vision and facial recognition.              194
  • Table 66. Applications of AI in computer vision and facial recognition.      196
  • Table 67. Companies developing AI in computer vision and facial recognition        196
  • Table 68. Applications of AI in cybersecurity         197
  • Table 69. Companies developing AI in cybersecurity.        198
  • Table 70. Applications of AI in electronic noses.  200
  • Table 71. Companies developing AI in electronic noses.  201
  • Table 72. Defunct AI companies.               534

 

List of Figures

  • Figure 1. History and development of AI.               29
  • Figure 2. Components, types and subfields of AI. 31
  • Figure 3. Global AI funding 2015-2021.    34
  • Figure 4. Maturity level of AI by industry.              39
  • Figure 5. Market revenues forecast by industry 2020-2032, billion USD.   40
  • Figure 6. Global AI software revenues 2020-2030, billions USD.   41
  • Figure 7. Global AI Hardware revenues 2020-2030, billions USD   42
  • Figure 8. AI players and target markets. 45
  • Figure 9. Method domains of artificial intelligence.           52
  • Figure 10. The structure and training of deep neural networks.   65
  • Figure 11. AI in the manufacturing value chain.   99
  • Figure 12. Computer vison based quality control.               105
  • Figure 13. AI in the automotive value chain.         110
  • Figure 14. Levels of driving automation. 113
  • Figure 15. Baidu self-driving car. 114
  • Figure 16. AI in the construction value chain.       123
  • Figure 17. AI in the energy value chain.   128
  • Figure 18. AI in the medical devices and healthcare value chain.  144
  • Figure 19. Applications of AI in pharmaceuticals. 145
  • Figure 20. Artificial intelligence (AI) in drug discovery.     146
  • Figure 21. AI in the food and agriculture value chain.        161
  • Figure 22. Mobileye EyeQ chip.  378

 

 

 

 

The Global Market for Artificial Intelligence (AI) 2022
The Global Market for Artificial Intelligence (AI) 2022
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