The study of computer algorithms that learn by analyzing data is referred to as machine learning. Artificial intelligence includes machine learning, which is considered a subset of AI. Surveys and market research are the most effective ways to comprehend the entire picture of the machine learning market since data may provide metrics ranging from the industry’s value to its difficulties.

This article is a compilation of 30 current machine learning-related data culled from reliable organizations’ surveys and research. However, AI, AutoML, and even chatbots are related markets with data that overlaps with machine learning. If you’re interested in these themes, feel free to look at the following articles:

You’ll discover machine learning statistics in this article:

Market Predictions

  • During the projection period, the machine learning market is anticipated to expand at a CAGR of 44 percent, from $1 billion in 2016 to $9 billion by 2022.
  • The global machine learning market was valued at $8 billion in 2021 and is anticipated to reach USD 117 billion by 2027, growing at a 39 percent CAGR.

Adoption in the Market

More organizations are adopting machine learning models as C-level executives become more aware of the benefits that machine learning investments may provide:

According to the Refinitiv AI/ML Survey,

  • 46% of respondents have used machine learning in several areas and consider it essential to their organization.
  • ML has been deployed in pockets by 44% of respondents.
  • 10% of those polled are experimenting and putting money into infrastructure and people.
  • North America (80 percent) is the most advanced in terms of machine learning usage, followed by Asia (37%), and Europe (37%). (29 percent )
  • A machine learning model isn’t used by 55% of organizations.
  • During the first quarter of 2021, a total of $29 billion was allocated to machine learning throughout the world.
  • Budgets for machine learning projects are typically increasing by 25%, with the banking, manufacturing, and information technology industries seeing the most significant increases this year.
  • For 20% of C-level executives, machine learning is a critical component of their business (across 10 countries and 14 sectors)
  • The external investment was anticipated to amount between $8 and $12 billion in 2016. Machine learning was responsible for around 60% of the entire investment. Machine learning is a critical enabler for a wide range of other technologies and applications, such as robotics and speech recognition.

Talent for Machine Learning

  • Job titles dedicated to machine learning are already commonly employed in firms with substantial expertise in machine learning, according to O’Reilly: data scientist (81%), machine learning engineer (39%), and deep learning engineer (20 percent ).
  • According to Kaggle, just 4.5 percent of self-identified data scientists or data researchers in the United States work exclusively as machine learning engineers. (Kaggle)
  • According to Thinkful, the average yearly income of a full-time data scientist in the United States will be $120,000 in 2021.
  • On, the three most in-demand talents are machine learning, natural language processing, and deep learning.
  • Between one and ten data scientists are employed by half of the respondents’ firms. This is a decrease from 2018 when 58 percent of businesses reported to employ one to ten data scientists.
  • In 2018, 18% of businesses had 11 or more data scientists on staff. However, by 2021, that figure will have risen to 39%, indicating that firms are increasing their hiring efforts in order to develop a larger data science team.
  • The number of data scientist positions on LinkedIn rose by more than 650 percent between 2012 and 2021.

Netflix has saved $1 billion as a result of its machine learning system, which helps customize content suggestions for its customers.

In today’s contemporary world, machine learning, automation, and artificial intelligence are gaining traction by the minute, especially as corporations invest significant sums of money in deploying these disruptive technologies.

The proven accuracy of machine learning in identifying COVID-19 patient death was 92 percent.

Machine learning is quickly becoming a standard part of how businesses operate, and over the next decade or two, it may be as accessible as smartphones are now.

Machine Learning Statistics in General

The global machine learning market is booming, owing in large part to all of the money being put into it by the world’s biggest corporations.

Machine learning has a 62 percent success rate in predicting stock market highs and lows.

When consumers and businesses realise that machine learning can help them make a lot of money on the stock market, this technology will see a surge in new financing and investments.

Google Translate witnessed a 60% reduction in error rates after using a machine learning-powered translation engine.

GNMT is a translation algorithm used by Google Translate to eliminate 60% of all errors.

Google’s Deep Learning ML machine learning engine is 89 percent accurate in detecting breast cancer.

It’s no surprise that machine learning is fast intruding on many sectors of the healthcare business, given its wide range of applications.

Around 80% of those who have used machine learning and artificial intelligence say their income has increased as a result of their use of these technologies.

Machine learning and AI will almost likely become mainstream in the corporate sector if the numbers continue to increase.