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From the ancient Greeks to present-day sci-fi, mankind has always been fascinated with the idea of machines that attempt to replicate and extend beyond human capabilities. While popular media tends to focus on the dangers or ethical quandaries surrounding the development of intelligent machines, in actuality, artificial intelligence (AI) is already interwoven into our everyday lives.

What was once science fiction is quickly becoming our reality, and advances in AI have allowed for staggering progress and improvements in our lives. Whether it’s in health care, sports, manufacturing, or business, AI has permeated the very fabric of our existence.

No matter your view, artificial intelligence is here to stay. And these AI statistics, trends, and technologies will give you an understanding of the current scope of AI—as well as the trajectory of the future AI market.

What Is Artificial Intelligence?

In its simplest form, artificial intelligence is any intelligence demonstrated by man-made machines, in contrast to the natural intelligence displayed by humans and other living organisms. AI machines, systems, and algorithms mimic human intelligence to perform various tasks, and can even improve their performance based on the information they collect and process.

What Are the Origins of Artificial Intelligence?

Humans have been intrigued by the concept of machines that can imitate the human mind since antiquity. One of the best examples of this early interest in AI is Talos, a giant bronze automaton said in Greek mythology to protect the island of Crete.

However, the term artificial intelligence wasn’t used until the 20th century, when computer scientist John McCarthy coined it in 1956. The following year, McCarthy and other like-minded researchers organized a workshop at Dartmouth College, and the field of AI research was born.

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Why Is Artificial Intelligence Important?

artificial intelligence statistics data

The advance of AI technology has enabled the ability to absorb and process data at a rate that far exceeds human capacity. AI capabilities have made the laborious chore of interpreting large amounts of data efficient and have simplified the process of complex decision-making.

Simply put: Computers are extremely efficient at processing large amounts of data and making calculations to arrive at the best decision for a given problem, or the most likely outcome for a given scenario.

By removing the workload of analyzing data, AI technology has allowed humans to focus on applications for that data rather than the effort of processing it, which has greatly improved and simplified our existence.

How Is Artificial Intelligence Used?

AI technology has become mainstream in recent years, with thousands of applications, many of which are used every day by millions of people. Some of the more prominent and recognizable uses of artificial intelligence technology include:

  • Streaming: Streaming services like Netflix use artificial intelligence algorithms to process the things you watch and find patterns, allowing them to give you suggestions for what to watch next.
  • Education: Educational tools and plagiarism checkers such as Grammarly utilize machine learning and natural language processing to improve your writing and quickly check their databases for plagiarized content.
  • Self-driving cars: Visual recognition and machine learning combine to help autonomous vehicles understand their surroundings and react to them, including the ability to adapt to traffic patterns and signs.
  • Health care: AI technologies are increasingly being used in health care to create tools that diagnose diseases, monitor patients, and develop medicines for more efficient and accurate delivery of care.
  • Voice assistants: Digital voice assistants—think Siri, Alexa, and Google Assistant—are one of the biggest areas of AI adoption. These AI-powered digital voice assistants use machine learning to understand and adapt to your preferences and to instantly scour the internet for answers to your questions in voice searches.
  • Chatbots: Many companies now use AI to improve customer service through chatbots that interact with customers and answer generic questions.
  • Online shopping: Other AI trends can be found in online shopping. Retailers like Amazon are continually refining their algorithms to analyze customer data and better predict what you might be shopping for so they can put those items in front of you.

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Who Uses Artificial Intelligence?

Artificial intelligence is used by consumers, as well as corporations, sports teams, researchers, law enforcement, and anyone else who uses computers to analyze large amounts of data in order to find patterns and make predictions. In the modern era, almost everyone who uses the internet has interacted with some form of artificial intelligence at some point in their lives.

It should come as no surprise that the global artificial intelligence market is dominated in both use and development by tech giants like Amazon and Google.

How Is Artificial Intelligence Used in Business?

Artificial intelligence has a wide range of applications in business, but the top three are natural language processing, data analytics, and automation. In addition to the use of AI in customer support functions, AI is also increasingly being used by marketing and sales departments. Demand forecasting, lead prioritization, website user experience, and SEO optimization are just a few of the ways in which AI is improving business operations.

Additionally, AI is also being used to quickly and efficiently complete repetitive or relatively simple tasks such as analyzing job candidate profiles, as well as more complex tasks like processing payrolls.

Without further ado, let’s delve into some artificial intelligence facts, findings, and forecasts that demonstrate just how widespread the technology is—and how much runway it still has to grow.

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Artificial Intelligence Statistics: Market Size + Growth


1. Market Size

The global AI market is expected to grow to around $313 billion by 2025 and to over $1.6 trillion by 2030. (Source: Statista)1

2. Growth Rate

The artificial intelligence market is projected to deliver a compound annual growth rate of 37.3% between 2023 and 2030. (Source: Grand View Research)2

3. Contribution to the Global Economy

The AI industry is expected to contribute $15.7 trillion to the global economy by 2030. (Source: PwC)3

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Artificial Intelligence Statistics: Employment Opportunities

artificial intelligence statistics employment

4. Is AI Replacing Jobs?

The World Economic Forum (WEF) estimates that by 2025, 85 million jobs will be eliminated as a result of AI-powered intelligent automation and other applications. However, the WEF also estimates that in the same time period, 97 million new jobs will be created due to AI. (Source: CNBC)4

5. Future Occupations

One of the more interesting AI statistics? Artificial intelligence will eventually replace between 400 million and 800 million jobs, meaning around 30% of today’s occupations will no longer exist. While some of those unemployed will shift to other similar occupations or retire, 75 million to 375 million “may need to switch occupational categories and learn new skills.” (Source: McKinsey & Company)5

6. Employment Prospects

Jobs involving computer systems and operations will be especially important to implementing AI in the future. As such, the field of computer and information research science is expected to grow by 21% (“much faster than average,” says the Bureau of Labor Statistics) between now and 2031, while jobs in computer and information systems management are expected to grow by 16%. (Source: Bureau of Labor Statistics)6, 7

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Artificial Intelligence Statistics: Retail Industry

artificial intelligence retail industry

7. Optimization

A survey by Accenture found that 73% of business leaders say that incorporating AI will be key to how they price their products in the future. (Source: Accenture)8

8. Fraud

Billions are lost to fraud every year, but the widespread adoption of AI is hoping to change that. Around 75% of retail executives expect to use artificial intelligence to combat credit card fraud. (Source: Aiiot)9

9. Forecasting

According to Salesforce, 62% of high-performing sales departments now use AI to enhance the accuracy of their sales forecasts. (Source: Salesforce)10

10. Warehouse Efficiency

One of the most interesting artificial intelligence stats on its business uses comes from the giant of internet retail. Using a machine learning program called Kiva, Amazon was able to reduce its “click to ship” time from 60-75 minutes to just 15 minutes, representing a 75%-80% decrease in the time it takes to ship an item after it is purchased. (Source: McKinsey & Company)11

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Artificial Intelligence Statistics: Chatbots + Customer Service Interactions

artificial intelligence chatbot customer service

11. Chatbot Penetration

The global chatbot market was just $840 million in 2022. However, it’s expected to explode by 19.3% annually through 2032, when it should hit $4.9 billion. (Source: Precedence Research)12

12. Chatbot Preference

Chatbots are increasingly becoming a common AI strategy for the delivery of customer service … and it turns out some customers might actually prefer that. A 2022 survey found that a quarter of consumers in the U.S. are happy to use a chatbot when contacting a business. (However, given that the same survey showed 43% of consumers were not happy to use a chatbot, it’s clear that the technology will need further improvements to enable wider adoption.) (Source: Statista)13

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Artificial Intelligence Statistics: Machine Learning

artificial intelligence machine learning

Machine learning (ML) is a type of AI that involves the development of computer systems that can learn and improve their performance without explicit human instruction. These systems use models and data sets to find patterns and make predictions about future outcomes based on those trends.

13. Machine Learning Market

The machine learning market is expected to reach $210 billion by 2029. (Source: Fortune Business Insights)14

14. Machine Learning Applications

While one of the most prominent uses of machine learning is for autonomous vehicles (discussed below), this facet of the AI market is increasingly being used in a number of industries. One example is health care, in which ML is used to help in the identification of diseases, diagnosis, and in medical imaging. Another example is media, especially in streaming; machine learning is responsible for more than 80% of the content watched on Netflix via its recommendation system. (Source: Wired)15

15. Machine Learning Milestones

Machine learning predicted the mortality of COVID-19 patients with 92% accuracy in 2020. (Source: Nature)16

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Artificial Intelligence Statistics: Voice Search + Voice Assistants

artificial intelligence statistics voice assistants

One of the most widely utilized applications of artificial intelligence is the use of voice assistants like Siri, Alexa, and Google Assistant. They use artificial intelligence to recognize and respond to voice commands, as well as to quickly search databases to answer the user’s queries.

16. Mobile Use

Voice assistants are becoming far more ubiquitous in the U.S. For instance, nearly two-thirds (62%) of Americans age 18 and older use a voice assistant on at least one device—from smart speakers and phones to TV remotes and even in-car systems. (Source: NPR and Edison Research)17

17. Supported Devices

More than 90,000 types of smart home devices were supported by voice assistants as of 2019. Amazon Alexa supports (by far) the highest number of devices at around 60,000, followed by Google Assistant at around 30,000 and Apple’s Siri at around 400. (Source: Statista)18

18. Voice Assistant Accuracy

Google Assistant is the most accurate of the main voice assistants, with an average accuracy record of around 93%. By contrast, Siri is the least accurate with only a 78% average accuracy rating. (Source: Statista)19

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Artificial Intelligence Statistics: Self-Driving Cars

artificial intelligence self driving cars

A highly touted application of artificial intelligence is in autonomous vehicles (in other words, self-driving cars). These vehicles use machine learning to collect data on the vehicle’s surroundings, quickly analyze that data, and take appropriate action. Self-driving cars also take in information from traffic signs and other driver inputs to adapt to their environment.

19. Market Size

The self-driving car market is expected to surpass $133.4 billion by 2032, with a compound annual growth rate of 22.3% between 2023 and 2032. (Source: Market Research Future)20

20. Truly Autonomous?

Currently, there are no self-driving cars that are entirely autonomous. (Yes, not even Tesla’s “Full Self-Driving” is fully autonomous yet.) All cars with self-driving capability require a human driver at the wheel if needed to take over. (Source: MarketPlace)21

21. Safety

There are 9.1 accidents per million miles driven by autonomous vehicles, which is higher than the regular vehicle crash rate of 4.1 accidents per million miles driven. However, fewer severe injuries occur as a result of accidents in self-driving cars. (Source: The National Law Review)22

22. Milestones

As of July 2022, Tesla vehicles had driven more than 300 million autonomous miles as part of the Full Self-Driving (FSD) Beta. (Source: Tesla)23

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Artificial Intelligence Growth Prospects

artificial intelligence statistics growth

23. Growing Use

An IBM survey in 2022 showed that 35% of businesses use AI, up 4 percentage points from the previous year. (Source: IBM)24

24. Business Adoption

According to one executive survey, virtually all businesses (99%) have reported active investment in big data and/or AI to give themselves a competitive advantage, and nearly 92% have reported that the pace of their investment in these areas is accelerating. (Source: NewVantage Partners)25

What Types of AI Are There?

artificial intelligence types robot human

There are four types of artificial intelligence or AI-based systems. The first two can be found in abundance, while the second two currently exist either in theory only or are works in progress.

  1. Reactive machines: Reactive machines are the oldest form of AI systems and are very limited in their capability. They have no memory functionality, which means they cannot use previous experiences to inform new actions. In other words, these machines cannot “learn.” Instead, they automatically respond to a limited set of inputs.
  2. Limited memory machines (LMMs): In addition to having reactive capabilities, limited memory machines can also use previous experiences to help make decisions. These machines use training data to form a reference model that is used to solve future problems and continue to “learn” and adapt as more data are analyzed. Almost all existing AI technology falls under the category of limited memory machines.
  3. Theory of mind: Consider this the “next frontier” of artificial intelligence growth. This AI technology will be able to better understand the users it interacts with, allowing it to discern humans’ needs, thought processes, and emotions.
  4. Self-aware: Self-aware artificial intelligence technology is the final frontier of the AI industry and only exists in theory. This type of AI will not only have mastered the theory of mind, but will also have its own emotions, beliefs, needs, and ideas. While self-aware technology could potentially catapult our progress as a species, it could also have catastrophic consequences. Most dystopian portrayals of AI gone wrong have explored the dangers of machines that become self-aware.

In addition to the classification above, an alternate artificial intelligence classification system divides AI into the following three categories.

  1. Artificial narrow intelligence (ANI): This category covers all existing AI software, including those that use machine learning and deep learning to teach themselves. ANI systems cannot go beyond their programming, which allows them to perform a specific task autonomously. Reactive and limited memory machines fall under this category.
  2. Artificial general intelligence (AGI): AGI corresponds to the theory of mind category above. These more advanced AI machines would have the ability to learn, understand, and function just like a human mind.
  3. Artificial super intelligence (ASI): ASI machines would exceed general intelligence by not only replicating the human mind but going beyond it. This form of artificial intelligence would have superior memory, data-processing and analysis, and decision-making abilities.

(Source: Forbes)26

Where Is AI Most Commonly Used?

A global AI Readiness Index constructed by Oxford Insights and the International Development Research Center (IDRC) in 2022 found the U.S. to be the most prepared overall for the implementation of AI. Next came Singapore, the United Kingdom, Finland, and Canada. However, in two of the components that make up the index, Singapore actually ranks first. (Source: Oxford Insights)27

What Is the Future of AI?

Despite some misgivings about the creation of intelligent machines, AI market statistics make it clear: Artificial intelligence systems are already intertwined with our daily lives and will likely only continue to gain wider adoption.

As the AI market grows and AI usage increases, it is likely that artificial intelligence systems will improve in efficiency, productivity, and capability. It is also likely that AI services will expand into other industries and lead to developments that we can only imagine right now.

As I discussed in the section above on types of artificial intelligence, the end goal for many researchers is to create AI systems that are self-aware and possess superintelligence … but these machines are still a long way off from becoming reality. And as AI technologies advance, it will be imperative to consider issues of privacy and security to ensure individual users and businesses remain safe and in control of the machines we create.

As for the idea of machines taking our jobs? The advance of AI is expected to lead to the automation of many roles, but it should also result in the creation of new ones. Career opportunities will likely shift over the coming decades as a result, but there are many fields that will be largely immune to this AI evolution. Careers in health care, education, and business will still rely on human interaction and decision-making that cannot be replicated by computers.

At least, not yet.

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  1. Statista: https://www.statista.com/statistics/941835/artificial-intelligence-market-size-revenue-comparisons/
  2. Grand View Research: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market
  3. PwC: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
  4. CNBC: https://www.cnbc.com/2020/10/20/wef-says-machines-will-create-jobs-but-warns-of-pandemic-disruption.html
  5. McKinsey & Company: https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
  6. Bureau of Labor Statistics: https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm
  7. Bureau of Labor Statistics: https://www.bls.gov/ooh/management/computer-and-information-systems-managers.htm
  8. Accenture: https://www.accenture.com/us-en/services/applied-intelligence/solutions-ai-pricing
  9. Aiiot: https://www.aiiottalk.com/how-ai-help-retail-industry-price-prediction-and-optimization/
  10. Salesforce: https://www.datategy.net/2023/04/24/ai-sales-forecasting-how-to-predict-sales-with-accuracy-and-confidence/
  11. McKinsey & Company: http://www.mckinsey.com/~/media/McKinsey/Industries/Advanced%20Electronics/Our%20Insights/How%20artificial%20intelligence%20can%20deliver%20real%20value%20to%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx
  12. Precedence Research: https://www.precedenceresearch.com/chatbot-market
  13. Statista: https://www.statista.com/statistics/657148/united-states-consumer-satisfaction-with-chatbot-service/
  14. Fortune Business Insights: https://www.fortunebusinessinsights.com/machine-learning-market-102226
  15. Wired: https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like
  16. Nature: https://www.nature.com/articles/s41598-020-75767-2.pdf?origin=ppub
  17. NPR and Edison Research: https://www.npr.org/about-npr/1105579648/npr-edison-research-smart-speaker-ownership-reaches-35-of-americans
  18. Statista: https://www.statista.com/statistics/933551/worldwide-voice-assistant-supported-smart-home-devices/
  19. Statista: https://www.statista.com/statistics/1040539/digital-assistant-performance-comparison/
  20. Market Research Future: https://www.marketresearchfuture.com/reports/autonomous-vehicles-market-1020
  21. MarketPlace: https://www.marketplace.org/shows/marketplace-tech/self-driving-cars-might-never-drive-themselves/
  22. The National Law Review: https://www.natlawreview.com/article/dangers-driverless-cars
  23. Tesla: https://digitalassets.tesla.com/tesla-contents/image/upload/IR/TSLA-Q2-2023-Update.pdf
  24. IBM: https://www.ibm.com/downloads/cas/GVAGA3JP
  25. New Vantage Partners: https://c6abb8db-514c-4f5b-b5a1-fc710f1e464e.filesusr.com/ugd/e5361a_76709448ddc6490981f0cbea42d51508.pdf
  26. Forbes: https://www.forbes.com/sites/cognitiveworld/2019/06/19/7-types-of-artificial-intelligence/?sh=3ba3e870233e
  27. Oxford Insights: https://www.oxfordinsights.com/government-ai-readiness-index-2022
About the Author

Riley Adams is the Founder and CEO of Young and the Invested. He is a licensed CPA who worked at Google as a Senior Financial Analyst overseeing advertising incentive programs for the company’s largest advertising partners and agencies. Previously, he worked as a utility regulatory strategy analyst at Entergy Corporation for six years in New Orleans.

His work has appeared in major publications like Kiplinger, MarketWatch, MSN, TurboTax, Nasdaq, Yahoo! Finance, The Globe and Mail, and CNBC’s Acorns. Riley currently holds areas of expertise in investing, taxes, real estate, cryptocurrencies and personal finance where he has been cited as an authoritative source in outlets like CNBC, Time, NBC News, APM’s Marketplace, HuffPost, Business Insider, Slate, NerdWallet, Investopedia, The Balance and Fast Company.

Riley holds a Masters of Science in Applied Economics and Demography from Pennsylvania State University and a Bachelor of Arts in Economics and Bachelor of Science in Business Administration and Finance from Centenary College of Louisiana.