Today, machine learning forms a part of every industry imaginable, from healthcare and finance, to entertainment and retail. It’s become so ubiquitous that machine learning is no longer a “nice-to-have” technology— it's essential.

Still, considering how prevalent this technology is, there’s still lots to learn.

We’ve curated, vetted, and categorized a list of up-to-date stats on machine learning, below.

Top Machine Learning Statistics

These are the top machine learning stats that we think are important for you, and your business, to know about.

• 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% compound annual growth rate.
• 36% of executives say that their primary goal for incorporating AI is to optimize internal business operations.
• 84% of global business organizations believe that AI will give them a competitive advantage.
• The proven accuracy of machine learning in identifying COVID-19 patient death was 92%.
• 72% of executives believe that AI will be the most significant business advantage of the future.
• AI use has increased high-level business productivity by up to 54%.
• A machine learning model can predict under-performing companies with 62% accuracy.

Machine Learning in Business Statistics

Machine learning is changing the way entire industries run. As the amount of data grows, so too will the need to understand it all, quickly. Machine learning can help unlock valuable insights from the mountains of data they possess.

• 98.8% of firms investing are in Big Data and AI initiatives.
• 74% of data scientists and C-level executives are using machine learning for performance analysis and reporting.
• Investment in AI will increase more than 300% in the coming years.‍
• 91.5% of leading businesses have ongoing investments in AI.
• 80% of all AI and machine learning projects are stalled between proof of concept and full-scale deployment. The main reason? Launching pilots has proven deceptively easy, but deploying them into production is notoriously challenging. ‍
• 72% of business leaders say AI can enable humans to concentrate on more meaningful work.
• 46% of respondents have used machine learning in several areas and consider it essential to their organization.
• The most profitable area to implement machine learning systems is sales and marketing.

Machine Learning Adoption Statistics

Machine learning adoption is increasing in many industries, but adoption rates vary by country as well as company size.

• 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.
• 1/3 of IT leaders are planning to use machine learning for business analytics. 
• By 2025, companies that have adopted AI will be 10 times more efficient and have twice the market share of companies that have not.
• 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%).
• Countries with the highest machine learning adoption rates include: Israel (63%), Netherlands (57%), and the United States (56%).

Machine Learning Career Statistics

McKinsey predicted the U.S. would experience a shortage of 250,000 data scientists by 2024.

In fact, the demand is so high that even individuals who have pursued computer science and technical programs at universities are being thrust into performing demanding data analytic positions in the workplace.

• On Monster.com, the three most in-demand talents are machine learning, natural language processing, and deep learning.
• The number of data scientist positions on LinkedIn rose by more than 650% between 2012 and 2021.
• The average yearly income of a full-time data scientist in the United States will be $120,000 in 2021.‍
• AI is now the 2nd most in-demand job based on Indeed’s 2020 Career Guide 
• 83% of businesses say AI is a strategic priority for their businesses today yet, there is not enough data science talent
• Machine learning engineers were cited as the second most sought-after AI job in 2021.

No-code Machine Learning Statistics

According to a recent survey by Appian, 82% of organizations cannot hire and keep as many qualified software engineers as they would want. Which is why so many businesses are turning to no-code and low-code platforms.

And it’s easy to see why: their purpose is to enable business users to turn data into actionable insights via predictive analytics in seconds, rather than weeks or months. 

• No-code/ Low-code platforms are 10X faster than traditional software development.
• An average business can increase in value by $4.4 million by using no-code applications.
• 70% of new applications developed by organizations will use low-code or no-code technologies by 2025, up from less than 25% in 2020.
• 41% of businesses have active citizen development initiatives.
• Low code and no-code solutions have the potential to reduce development time by 90%.
• 85% of people using no-code tools say that it adds value to their projects.

Final Thoughts

Machine learning and AI are no longer concepts that are “far off” into the future. They’re here. And they’re revolutionizing entire aspects of life as we know it. 

Not sure if you're ready for AI? You probably are, but here's one way to tell.

To learn more about machine learning—what it is, how it works, and why it’s so important - be sure to check out our Ultimate Guide to Machine Learning. 

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