65 Artificial Intelligence Statistics for 2021 and Beyond

Artificial intelligence today plays a massive role in strengthening and transforming industries around the world. Many businesses fear they will invest in technology that will do them no good. However, a business’s only path to technical progress is through risk and confrontation. 

If you had to choose between taking a risk or losing a competitive advantage in the market, what would it be? 

In this article, we’ll go over all of the newest artificial intelligence statistics to help you determine if AI is right for your business’s future. 

General Artificial Intelligence Statistics

1. The global AI market is predicted to snowball in the next few years, reaching a $190.61 billion market value in 2025. 
2. The wearable AI market size is predicted to reach $180 billion by 2025. 
3. The forecasted AI annual growth rate between 2020 and 2027 is 33.2%. 
4. The global AI chip market revenue is expected to reach $83.25 billion by 2027. 
5. Between 2018 and 2025, the Asia-Pacific region will experience the highest compound annual growth rate.
6. By 2030, China will be the world leader in AI technology, with 26.1% of the global market share.
7. A lack of trained and experienced staff is an expected restriction in the AI market’s growth. 
8. In 2019, the machine learning application industry received $37 billion of funding in the U.S.
9. By 2030, AI will lead to an estimated $15.7 trillion, or 26% increase in global GDP. 
10. The $15.7 trillion GDP estimated by 2030 will likely come from increased profitability (40%) and consumption (60%). 
11. A whopping 93% of automation technologists feel little prepared for upcoming challenges regarding smart machine technologies.
12. The top three most significant challenges companies face when considering the implementation of AI are staff skills (56%), the fear of the unknown (42%), and finding a starting point (26%).

How Businesses Adopt AI Statistics

13. In 2022, companies are expected to have an average of 35 AI projects in place. 

14. 20% of businesses say automating tasks such as invoicing and contract validation is the second most crucial use of AI. 

15. 80% of retail executives expect their retail companies to adopt AI-powered intelligent automation by 2027. 

16. Only 7% of companies don’t use AI but are looking into it. 

17. 86% of CEOs say AI is mainstream technology in their office in 2021. 

18. 48% of companies use data analysis, machine learning, or AI tools to address data quality issues. 

19. In 2020, 39% of large organizations planned to invest in AI technology. 

20. 75% of executives fear going out of business within five years if they don’t scale AI. 

21. Marketing and sales departments prioritize AI technology and machine learning for their success more than any other department (40%). 

Benefits and Results of AI Statistics 

22. Netflix’s recommendations engine (powered by AI) is worth $1 billion a year.

23. 54% of executives say that implementing AI in their workplace has increased productivity. 

24. 79% of executives think AI will make their jobs simple and more efficient. simplify their job and make it more efficient.

25. The major benefits of chatbots are 24-hour service (64%), instant responses to inquires (55%), and answers to simple questions (55%). 

26. The potential contribution to the global economy from AI could be $15.7 trillion in 2030. 

27. In 2019, the machine learning application industry received $37 billion of funding in the U.S. 

28. In 2021, the increase in AI usage across businesses will create $2.9 trillion of business value and 6.2 billion hours of worker productivity. 

29. AI startups got record funding of $7.4 billion in Q2 of 2019.

30. By March 2019, there were 279,145 AI patent applications in the U.S. 

31. The supply chain management industry saw the most considerable cost decrease (44%) from implementing AI technology in 2019. 

32. The AI use cases that mostly led to cost decreases within organizations are optimization of talent management, contact center automation, and warehouse automation.

How and Where Is AI Used Statistics

33. In 2019, nearly 40% of the U.S. population used voice search. 

34. Also, in 2019, 45% of households in the U.S. owned a smart speaker, and 26% were planning to purchase one soon. 

35. In 2020, there was 4.2 billion digital voice assistance in use worldwide. 

36. Digital assistant usage worldwide is expected to double to 8.4 billion by 2024. 

37. The most prominent use case for AI in the retail industry is customer engagement (chatbots, predictive behavior analysis, hyper-personalization). 

38. 52% of people are confident that cyber-security is not a threat when sharing personal information online because of robust AI technologies. 

39. Out of the 300 billion emails sent every day, machine learning detects at least half as spam. 

40. Researchers who used AI software could detect a plagiarized source code with 87% accuracy. 

How AI Impacts the Workforce Statistics

41. 38% of people expect technology to eliminate jobs at their workplace over the next three years, while 13% expect automation to eliminate a significant number of positions. 

42. As many as 20 million manufacturing jobs may be lost to robots by 2030. 

43. It’s forecasted that there will be a total workforce reduction of 16% in the U.S. by 2030 due to arising AI technology. 

44. While AI may cause some job losses, they are likely to be broadly offset by new jobs created due to a stronger and wealthier economy made by AI technologies. 

45. 63% of CEOs predict that AI will positively impact job openings as the internet did when it first became available. 

46. In 2020, it was predicted that AI would eliminate 1.8 million jobs and create 2.3 million new jobs. 

47. By 2025, growing job demand for 97 million people will be needed for jobs such as AI and machine learning specialists, process automation specialists, big data specialists, and more. 

48. 43% of manufacturers have added data scientists/data quality analysts in their workforces, and 35% want to do the same within five years. 

AI in Marketing, Customer Service, and Sales Statistics

49. 40% of businesses say that customer experience is their top motivator for using artificial intelligence. 

50. Most marketers are not yet confident in using their data to achieve business goals. 

51. 71% of marketers find AI could be useful for personalization. 

52. 80% of marketers in 2020 already had chatbots as part of their customer experience strategy. 

53. 48% of marketing leaders agree that digital and mobile technologies (such as chatbots) have caused the most significant difference in how their customers and prospects interact with them. 

54. 51% of eCommerce players have implemented automation technologies across sales, marketing, and customer service teams to ensure a seamless user experience for customers. 

55. When asked which technologies most improve customer experience, 34% of sales and marketing leaders believe AI is the biggest game-changer. 

56. In 2020, chatbots responded to 85% of customer service interactions. 

57. Only 27% of consumers think that AI can deliver equal or better customer service than humans. 

58. On the other hand, 43% of people think AI will harm customer satisfaction and cause more complaints.

How AI Helps the COVID-19 Pandemic Statistics

59. Governments across the world are using AI technology to enforce social distance requirements. 

60. In 2020, hospitals were trying to speed up COVID-19 testing and diagnosing by providing automated remote consultations to patients in isolation through chatbots. 

61. 16% of European countries think automation through AI, and other technologies can help reduce the impact of COVID-19. 

62. In 2020, screening through studies related to COVID-19 and other outbreaks in history was efficient due to machine learning. 

63. AI is being used in projects like MIT-IBM to detect sepsis in COVID-19 patients. 

64. AI is also used to develop mathematical models that study the transmission rate of COVID-19. 

65. Before the world was aware of COVID-19, AI systems had detected the outbreak of an unknown type of pneumonia.

What AI Will Bring In the Future

There have been many speculations that AI’s future has us all doomed by evil robots and destructive machines. 

However, in the 1990s, Ray Kurzweil, an inventor and futurist, shared his optimistic predictions. Out of the 147 predictions Kurzweil made, 87% were correct to the year. 

One of Kurzweil’s predictions highlighted that computers would beat the best human chess player by the year 2000. In 1997, Garry Kasparov, world chess champion, was defeated by IBM’s Deep Blue computer in a chess tournament. 

Another prediction made by Kurzweil suggested the internet and computers would play a large role in speech-to-text software, classrooms, and many other technological advancements that have already happened.

Below are Kurzweil’s predictions that have yet to come true: 

• Starting in the 2020s, 3-D printing will print clothing and modules to create houses. 

• In the 2020s, we will grow food with vertical agriculture, use hydroponic plants for vegetables and fruit, and use in vitro cloning for muscle tissue for meat. 

• By 2029, search engines will understand the meaning of a search inquiry rather than just digesting keywords.

• The turning test (machines can think at human levels) will be passed in 2029. 

These predictions provide food for thought. If Kurzweil’s predictions come true, businesses will have to adapt to new ideas more rapidly than ever. 

How will your business get ready to adopt new AI technology? Be open-minded to adjusting your business goals, focus on growth instead of cost reduction, and hire or train new talent that is skilled in artificial intelligence is a great place to start. 

We hope this list of artificial intelligence statistics has opened your eyes to the ever-growing market ahead of us. 

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We got our information from the following sources: 

MarketsAndMarkets Global Market Insights Fortune Business Insights Statista Allied Market Research PWC Forrester Gartner O’Reilly Adobe Forbes Fortune Business Insider The Economist Drift CB Insights McKinsey & Company eMarketer Microsoft Blumberg Capital Tech Talks Emerj Deloitte Oxford Economics World Economic Forum MAPI Foundation Everstring Oracle PEGA IDC Towards Data Science OECD TED