50+ Machine Learning Statistics That Matter in 2024

If machine learning were a kid in school, it would be the most brilliant and coolest student.
We've all heard about how important machine learning has become, but what do we really know about its impact on how we make decisions daily?

Machine learning (ML) has transformed how we as humans interact with machines, technologies, and data. But it wasn't always so popular; what started out as a niche industry has grown into a billion-dollar market.

Today, machine learning is part of every industry you could think of: healthcare, finance, entertainment, retail, and manufacturing. It has become essential for businesses to adopt ML to boost revenue, cut costs, and automate operations.

In a world that thrives on disruptive technologies, these machine-learning statistics will help you navigate your way through this cryptic field.

Machine learning statistics

Machine learning is defined as the way in which machines learn from identifiable patterns to automate processes. It is a branch of artificial intelligence (AI) and aims to improve and automate data with little scope for human intervention.

Here are some fascinating ML statistics highlighting its vital role in our lives.

• 57% of companies and businesses use machine learning to improve consumer experience.
• 49% of the companies use machine learning and AI in marketing and sales.
  
• Netflix saved $1 billion due to its machine learning algorithm for the combined effect of personalization and content recommendations.
• The accuracy of machine learning in predicting stock market highs and lows is 62%.
• A 60% reduction in Google Translate errors was found when changed to GNMT—a translation algorithm powered by machine learning.

• The accuracy of Google's AI machine learning algorithm in predicting a patient's death is 95%.
• 97% of mobile users are using AI-powered voice assistants.
• Google’s lung cancer detection AI outperforms six human radiologists.
• AI could prevent 86% of cyber attacks and security threats.
• 43% of millennials would pay a premium for a hybrid human-bot customer service channel.

Machine learning adoption statistics

ML is being adopted by businesses, small and large, on a massive scale. With several tools flooding the AI market, companies run neck to neck to identify, analyze, and leverage data insights. ML adoption is higher than ever, with product/service development, operations, and sales and marketing witnessing the highest increases in ML use cases.

• Due to the adoption of AI, the Global GDP rate will grow by $15.7 trillion by 2030.
• The global machine learning market is expanding at 42.08% CAGR between 2018 and 2024.
• 65% of companies planning to adopt machine learning say the technology helps businesses in decision-making.
• North America (80%) leads in ML adoption and it is followed by Asia (37%) and Europe (29%).

• 20% of C-level executives (across ten countries and 14 different industries) report using machine learning as a core part of their business.
• 33% of IT leaders will adopt ML to improve business analytics.

• 25% of IT leaders plan to use ML for security purposes.
• 80% of people say that AI has helped increase revenue.
• 74% of data scientists and C-level executives use ML for performance analysis and reporting.

Machine learning and business statistics

If you've been around in the business world for a while now, you know that ML is the future. The rapid pace of changing technologies opens more opportunities for ML to drive innovation in conventional business processes. Investing in ML will become imperative for any business to survive in the digital age. 

• The estimated improvement in business productivity by using AI is 54%.
• 15% of organizations are advanced ML users.
•  $3.1B has been raised for machine learning companies with the investments of more than 4400 companies.
• 80% of businesses plan to adopt AI as a customer service solution
• 45% of end-users prefer chatbots as the primary mode of communication for customer service inquiries

• Investment in AI will increase by more than 300% in the coming years.

• 62% of customers are willing to submit their data to AI for a better business and user experience.
• 44% of organizations fear losing out to startups if they’re too slow to implement AI.
• Executives are using AI to cut out repetitive tasks such as paperwork (82%), scheduling (79%) and timesheets (78%)

Machine learning and sales statistics

Sales reps are often on the fence about adapting to new selling methods, or are they? As recent statistics show, more sales departments are taking to ML to help move customers quicker through the sales funnel. It is gradually becoming one of the most valuable sales enablement tools for better conversions.

• Companies using AI for sales increased their leads by more than 50%, reduced call time by 60-70%, and realized cost reductions of 40-60%.
• When AI is present, 49% of consumers are willing to shop more frequently, while 34% will spend more money.

• B2B companies that have leveraged AI in sales realized call-time reductions of up to 70% and a 50% increase in leads and appointments.
• Business leaders say chatbots have increased sales by 67% on average.
• 1 in 4 sales teams is using ML in their daily tasks.
• 47% of AI-led businesses said they could optimize sales and marketing, while 32% said they were able to reduce operating costs.

Machine learning and marketing statistics

Customers have changed, and so have their expectations. To market your product effectively, you will need access to highly personalized content and user experience along with intelligent campaigns. Machine learning will give you exactly that. 

• 87% of current AI adopters said they were using or considering using AI to forecast and improve email marketing.

• Over 56.5% of the organizations reported using artificial intelligence and machine learning to personalize their sales and marketing content.
• 61% of marketers say artificial intelligence is the most critical aspect of their data strategy.
• Amazon’s average ‘click to ship’ time has been reduced by 225% from 60-75 minutes to 15 minutes.
• Marketing leaders are more than 2x likely to report investments in ML technologies and automation for marketing activities.

Machine learning and healthcare statistics

• Japan plans to have 75% of the elderly care performed by AI.
• 70% of drug discovery costs can be cut by applying AI and ML.
• ML can help achieve up to 95% accuracy in predicting COVID-19-related physiological deterioration. 
• The global ML and AI healthcare market is expected to reach  $187.95 billion by 2030. 
• Google’s Deep Learning ML program has 89% accuracy in detecting breast cancer.
  

Machine learning job demand statistics

As the need for ML continues to grow across industries, there is a growing demand for data scientists, machine learning engineers, ML scientists, AI application engineers, data analysts, and more. This is quite literally the best time to make a career in the field; here's why.

• 82% of companies and businesses need employees with machine learning skills. 
• Artificial Intelligence is now the 2nd most in-demand job.
• More than 98,000 jobs posted on LinkedIn list machine learning as a required skill.
• Machine learning, NLP and deep learning are the three most in-demand skills on Monster.com.

• 74% of buyers choose the company that was the first to add value. 
• 39% of businesses are ramping up their hiring efforts to build a more extensive data science team.
• Only 20% of executives feel their data science teams are ready for AI.

Machine learning provides invaluable lessons

Machine learning is a fundamental part of artificial intelligence; it quite literally will teach itself and your business processes to get smarter. Adapting to and investing in machine learning is bound to reap valuable insights for your business and for the next online parcel you are waiting on. ML is changing a lot about our lives. The least we can do is give it more collective thought.

Want to delve deeper into the world of artificial intelligence? Read up on deep learning, the subset of machine learning that mimics the human brain’s functioning.