Concerns about AI’s use remain, however, including security risks and biases it could introduce into hiring and society as a whole as well as bad decisions it might make due to poor underlying data quality. Here’s a snapshot of the present and future of AI, told in 11 statistics:

$15.7 trillion--AI's boost to the global economy by 2030, according to PwC.

That’s a 14 percent increase, more than the current economic output of China and India combined, a PwC study projects. Some $6.6 trillion of the boost will come from increased productivity, while $9.1 trillion will arrive as a result of increased economic consumption. PwC concludes that AI is “the biggest commercial opportunity in today’s fast-changing economy.” The biggest global winners will be China and North America. China can expect a GDP increase of up to 26 percent by 2030, followed by North America with 14 percent. Together, they will account for $10.7 trillion, nearly 70 percent of AI’s global economic impact. By industry, the biggest winners will be retail, financial services, and healthcare, the report concludes, because “AI increases productivity, product quality, and consumption.”

Source: “Global Artificial Intelligence Study: Exploiting the AI Revolution,” PwC

58 million--Net new jobs that will be created worldwide by 2022 as a result of the increasing use of AI, including workplace robots, according to the World Economic Forum.

AI and robots also will take jobs away—75 million of them. But those job losses will be offset by the 133 million emerging roles created. The ratio of the total number of work hours performed by people compared with the total number of work hours performed by AI and robots will change significantly in that time as well. In 2018, the report says, 71 percent of work hours were done by people and 29 percent done by AI and machines. By 2022, the human hours will decline to 59 percent of the total, and the AI and machine portion will grow to 41 percent. By 2025, the report projects, AI and robots will be working the majority of hours: 52 percent compared with 48 percent for humans.

Source: “The Future of Jobs 2018,” World Economic Forum, based on data from a survey of chief human resources officers and top strategy executives from companies across 12 industries and 20 developed and emerging economies

4,400--Number of company earnings reports written by AI for the Associated Press (AP) every quarter, according to Automated Insights.

Human reporters have been able to write only 300 earnings stories per quarter because of the manual work involved. Automated Insights, which sells the AI-powered story-generating software used by the AP, Yahoo, CNBC, and other news outlets, says its service can write 2,000 articles per second. Other news organizations are using AI to write stories as well. Bloomberg uses a different AI-generating software, Cyborg, to write its earnings reports. And the Washington Post’s in-house robot reporter, Heliograf, wrote about the 2016 Olympics and 2016 presidential election. (Note: Not a single word of the article you’re reading right now was written or assisted by AI.)

Source: Automated Insights

That’s far more than the 47 million people who use voice assistants at home at least once a month. More than 114 million people out of the total adult U.S. population of 252 million have tried voice assistants in their cars, the survey claims.

Source: In-Car Voice Assistant Consumer Adoption Report 2019, a collaboration by Voicebot and Voice of the Car Summit analyzing data from a survey of 1,040 U.S. adults to better understand usage and attitudes toward voice assistant use in the car

54 percent--Companies that monitor for AI-created bias, according to an O'Reilly survey about machine learning in the enterprise.

Bias creeps into ML and AI when biased data or assumptions are used. As a result, injustices may be perpetuated in hiring, the criminal justice system, access to credit, and other areas. The survey concluded that the percentage of enterprises checking for AI-created bias will increase because the number of tutorials and training materials to help check are increasing. The survey also found that 53 percent of people who work for companies that have extensive experience in machine learning check for privacy issues, compared with 43 percent of those in all companies.

Source: “The State of Machine Learning Adoption in the Enterprise,” O’Reilly, 2018, based on data from a survey of 11,400-plus conference attendees and O’Reilly online content channel consumers

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$1 billion--Money Netflix saves per year thanks to its ML-based algorithm that personalizes the recommendations of TV and movies to its customers.

In the paper “The Netflix Recommender System: Algorithms, Business Value, and Innovation,” published in the journal ACM Transactions on Management Information Systems, Netflix executives and researchers say the savings from ML are due to increased customer satisfaction with the service, which cuts down the number of customers who cancel subscriptions. The paper says 80 percent of the videos its customers watch come as a result of Netflix recommendations, with only 20 percent coming from search. It says Netflix members lose interest in finding a video after 60 to 90 seconds of looking, and in that time, “the user either finds something of interest or the risk of the user abandoning our service increases substantially.” Helping customers find a video faster means they’re less likely to cancel Netflix.

Source: “The Netflix Recommender System: Algorithms, Business Value, and Innovation,” Netflix, 2015

225 percent -- Decrease in Amazon's "ship-to-click" time due to use of robots and AI-built algorithms, according to McKinsey Global Institute.

Inventory capacity has also increased by 50 percent while operating costs have been reduced by 20 percent, according to the study. Since the study was published, Amazon has been refining those techniques to power its Prime Now service, which delivers basic goods to households within hours of ordering. The algorithms predict at which geographic locations certain goods are likely to be ordered and prestocks those warehouses with the goods—and even determines where they should be located inside the warehouses for maximum efficiency, according to a National Public Radio report.

Source: “Artificial Intelligence: The Next Digital Frontier,” McKinsey Global Institute, 2017, based on data from a survey of more than 3,000 AI-aware companies around the world; “How Artificial Intelligence Can Deliver Real Value to Companies

67 percent--Large companies that will have live AI initiatives by 2021, up from approximately 14 percent in early 2019, according to venture capital firm MMC Ventures.

The company’s research also found that AI adoption tripled in the past year. It predicts, “In 2019, AI ‘crosses the chasm’ from early adopters to the early majority.” Because of this, MMC Ventures concludes, demand for AI talent has skyrocketed and companies are having a hard time hiring. Two sectors of the economy—financial services and technology—have the lion’s share of AI experts, together accounting for 60 percent of the AI workforce.

Source: “The State of AI: Divergence 2019,” MMC Ventures

$118.6 billion -- Annual revenue for AI software worldwide by 2025 vs. $9.5 billion in 2018, according to research firm Tractica.

The firm says growth will be driven by deep-learning technologies based on vision and language. Its report concludes, “The global AI market is entering a new phase where the narrative is shifting from hype to reality.”

Source: “Artificial Intelligence Market Forecasts,” Tractica, 2019

60 percent -- Decision-makers at companies using AI who say data quality is a top AI challenge, according to Forrester Research.

That’s not the only AI-related issue business leaders face, though. Forrester says two-thirds of the companies using AI encounter serious problems hiring AI talent and 83 percent of them struggle with retaining existing AI experts.

Source: “Predictions 2019: Artificial Intelligence,” Forrester Research, Nov. 6, 2018

23 percent -- Executives who say their main concern about AI is security risks, according to a Deloitte survey.

Security risks are the most-cited concern, followed by making wrong strategic decisions based on AI (16 percent), the failure of an AI system in a mission-critical or life-and-death context (13 percent), and several others. Among the cybersecurity risks the report cites are the use of hacked data to fool AI into making wrong decisions or to bypass biometric authentication systems. Thirty-two percent of companies say they have experienced a cybersecurity breach related to AI initiatives in the past two years. Further, 30 percent say they’ve slowed their AI initiatives to address cybersecurity concerns, 20 percent have decided not to start an AI initiative because of cybersecurity concerns, and 16 percent have halted an ongoing AI initiative due to cybersecurity concerns.

Source: “State of AI in the Enterprise, 2nd Edition,” Deloitte, 2018, based on data from a survey of 1,100 IT and line-of-business executives from U.S.-based companies