Machine Learning Statistics: Trends You Need to Know in 2024
Published on: 31 Aug 2023 | Author: Clara Gil
Marketing Statistics
In this Industry Report:
- General Machine Learning Statistics
- Growth of Machine Learning
- AI ML Statistics
- Marketing and Machine Learning Statistics
- Future of Machine Learning
- Conclusion
Machine learning is a key component of artificial intelligence and data science, which uses algorithms and statistical models to analyze and draw conclusions from patterns in data. It’s also considered one of the greatest innovations since the microchip. It started out as something out of science fiction and has slowly but surely become an important part of our daily lives. These +80 machine learning statistics will prove us right.
The goal of our research is to provide a broad understanding of what is happening in the field. We don’t cover areas like descriptive statistics, inferential statistics, or statistical analysis. We just want to help you understand the future of ML and how other companies and marketing teams are benefiting from the many uses it has.
General Machine Learning Statistics
N. America
currently leads machine learning adoption
51%
of organizations claim to be early adopters of ML
Impact
Business leaders believe that ML will have an impact on how business is run
- In 2022, North America accounted for 43% of the global AI market. This is partly due to the high demand for automated and technologically advanced solutions. (IDC, Precedence Research)
- China, India, Italy, and the United Arab Emirates are leading the AI adoption rates around the world. (IBM)
- North America (80%) leads in machine learning adoption, followed by Asia (37%) and Europe (29%). (G2)
- By 2030, all regions of the global economy will benefit from machine learning and artificial intelligence, with China and North America seeing the largest economic gains, with AI increasing GDP by 26.1% and 14.5%, respectively. (PwC)
- Northern Europe and Southern Europe will see estimated economic gains of 9.9% and 11.5%, respectively, from the adoption of ML and AI by 2030. (PwC)
- 48% of organizations are using machine learning, deep learning, data analytics, and natural language processing to make effective use of large data sets. (EarthWeb)
- 51% of organizations claim to be early adopters of ML, but only 15% are advanced ML users. (McKinsey)
- As of November 2020, IBM had the most machine learning patents with over 5,500. Microsoft had 5,400. (Thrive My Way)
- 62% of business leaders believe that by 2023, machine learning will have an impact on how business is run. (Thrive My Way)
- Machine Learning milestones:
- 95% accuracy in predicting a patient’s death. (Bloomberg)
- 62% accuracy in predicting stock market highs and lows. (Microsoft)
- 89% accuracy of Google’s deep learning program in detecting breast cancer. (Health Analytics)
- 92% accuracy in predicting mortality in COVID-19 patients. (AIM)
Growth of Machine Learning
Budgets
or ML programs are most likely to grow by 25%
Scaling
is the main challenge organizations face when deploying ML
C-level
executives oversee 75% of all A.I. projects at their companies
- 65% of companies planning to adopt machine learning say the technology will help the business make decisions. (G2)
- Budgets for ML programs are most likely to grow by 25%. The banking, manufacturing, and IT industries have seen the most significant budget growth this year. (G2)
- 74% of data scientists and C-level executives use ML for performance analysis and reporting. (G2)
- The top challenges organizations face when deploying and using machine learning are:
- Scaling: 43%
- Versioning and reproducibility of ML models: 41%
- Achieving organizational alignment and executive buy-in: 34%.
- Support for multiple programming languages and frameworks: 33%
- Duplication of effort across the organization: 28%.
- Other: 26% (Statista)
- 80% of organizations that have used machine learning say the technology has helped their bottom line. (Statista)
- It’s estimated that the U.S. deep learning and machine learning market will be worth $80 billion by 2025. (EarthWeb)
- C-level executives personally oversee 75% of all A.I. projects at their companies. (Fortune)
- 82% of risk management processes now use some form of AI or machine learning. (Thrive My Way)
- It is estimated that 85% of customer interactions occur without any human involvement. (Thrive My Way)
- Among companies that have already deployed AI across their business, 30% have seen significant economic benefits and 53% have seen moderate economic benefits. (Thrive My Way)
Machine Learning Industry Statistics
82%
of companies need employees with machine learning skills
12%
of organizations say the supply of ML skills is at an adequate level
44,000
jobs on LinkedIn in the US that list machine learning as a required skill
- 91% of top companies say they are making ongoing investments in AI and ML, and 91.7% say they are increasing their spending. (NewVantage Partners)
- 82% of companies need employees with machine learning skills. (Zippia)
- The US industries that will see the fastest growth in AI spending are professional services, media, securities, and investment services. (IDC)
- Retail and banking will account for nearly 28% of all AI spending in the United States in 2025. (IDC)
- 82% of organizations need machine learning skills, and only 12% of organizations say the supply of ML skills is at an adequate level. (Statista)
- The average salary of an ML engineer ranges from $112,342 to $145,688. The final number is determined by experience, industry, and geographic location. (Coursera)
- Employment of machine learning engineers is projected to grow by 22% between 2020 and 2030. (US Bureau of Labor Statistics)
- 73% of IT decision making leaders in the UK and 41% in the US say they lack the right AI talent in-house to execute their AI and ML strategy. (SnapLogic)
- There are more than 44,000 jobs on LinkedIn in the US that list machine learning as a required skill, and more than 98,000 jobs worldwide (Forbes).
- Global employment of machine learning engineers is expected to grow at a rate of 22% between 2020 and 2030. (Zippia)
Machine Learning Market Size
$500b
The AI market is expected to reach $500 billion by 2023
Europe
holds 44.87% of the global machine learning market share
Employees
The demand for employees with AI and machine learning skills will grow at a CAGR of 71%
- The global machine learning market has been growing steadily over the past few years. It was valued at $21.17 billion in 2022, and it’s expected to grow to $209.91 billion by 2029. (Fortune Business Insights).
- This year, the AI market is expected to reach $500 billion. (IDC, Precedence Research)
- $3.1 billion has been raised for machine learning companies, with investments from more than 4400 companies. (G2)
- By 2026, the global machine learning market is expected to be valued at $87.68 billion. (NeighborWebSJ)
- The compound annual growth rate (CAGR) for the machine learning hardware market is expected to be 37.60% annually from 2019 to 2026. (NeighborWebSJ)
- Europe holds 44.87% of the global machine learning market share. This is followed by North America (44.05%). (Zippia)
- The U.S. machine learning market is expected to grow from $100 million in 2018 to $935 million in 2025. (Zippia)
- The demand for employees with AI and machine learning skills will grow at a CAGR of 71% from 2020 to 2025. (Zippia)
- By 2019, the total funding allocated to machine learning projects worldwide will be $28.5 billion. (Statista)
- Machine learning budgets will increase by 25% in 2021 compared to 2020. (Thrive My Way)
AI ML Statistics
Profit
42% of companies said the profitability of their ML and AI initiatives exceeded their expectations
44%
of companies have deployed some form of AI and machine learning within their organization
75%
of companies using AI and machine learning have increased customer satisfaction by about 10%
- The top three drivers of ML and AI adoption are:
- Increasing accessibility of the technology.
- The need to reduce costs and automate key processes.
- The increasing implementation of AI in standard business applications. (IBM)
- By 2021, AI and ML use cases for businesses around the world will be:
- Improving the customer experience: 57%
- Generating customer insights and intelligence: 50%
- Interacting with customers: 48%.
- Detecting fraud: 46%
- Increase long-term customer loyalty: 44%. (Statista)
- 42% of companies said the profitability of their ML and AI initiatives exceeded their expectations. Only 1% said it didn’t meet expectations. (Accenture)
- Improving customer experience and automating processes are the top two uses of AI and machine learning. (Zippia)
- 44% of companies have deployed some form of AI and machine learning within their organization. (Thrive My Way)
- 56.5% of content publishers and marketing leaders are using AI and machine learning to personalize content for better results. (Thrive My Way)
- Advances in AI and machine learning have the potential to increase global GDP by 14% from 2019 to 2030 (WSJ).
- Top executives are leading the development of AI and ML in organizations to eliminate redundant tasks such as timesheets (78%), scheduling (79%), and paperwork (82%). (FounderJar)
- 75% of companies using AI and machine learning have increased customer satisfaction by about 10%. (Forbes)
- By 2021, 76% of organizations will prioritize AI and ML adoption over other IT initiatives. (Zippia)
AI Growth Statistics
2025
By 2025, nearly 100% of organizations will implement some form or method of AI
300%
Investment in AI will increase by more than 300% in the next few years
$87.68 b
is the expected value of the artificial intelligence (AI) hardware market
- Larger companies are twice as likely to have actively deployed AI, while smaller companies are more likely to be exploring or not pursuing AI at all. (IBM)
- 46% of organizations plan to implement AI in the next three years. (Deloitte)
- By 2025, nearly 100% of organizations will implement some form or method of AI. (Forrester)
- 80% of organizations plan to deploy AI as a customer service solution. (G2)
- Investment in AI will increase by more than 300% in the next few years. (G2)
- AI Web design in 2023 was good enough to fool 54% of the population. (Sortlist: AI Web Design Opinion Study)
- Executives are using AI to eliminate repetitive tasks such as paperwork (82%), scheduling (79%), and timesheets (78%). (G2)
- The A.I. hardware market valuation is expected to grow to $87.68 billion by 2026. (EarthWeb)
- $87.68 billion is the expected value of the artificial intelligence (AI) hardware market at a CAGR of 37.60% from 2019 to 2026 (NeighborWebSJ).
- By 2035, AI is expected to increase corporate profits by 38% and generate an additional $14 trillion for those same companies. (Thrive My Way)
- 44% of larger companies estimate that without investing in AI, they will lose out to smaller A.I. startups. (Thrive My Way)
Marketing and Machine Learning Statistics
Content
56.5% of marketers are using ML and AI to personalize content
Revenue
31% of those using ML and AI in sales and marketing say they have increased revenue and market share
61%
of marketers say machine learning and AI are the top priority for their data strategies
- 48% of companies are using ML and AI in their marketing and sales processes to gain insight into their prospects and customers. (Harvard Business Review)
- 56.5% of marketers are using ML and AI to personalize content. (CMO Survey)
- 67% of users agree that ML and AI in marketing and sales will be critical to their company’s future competitiveness. (Harvard Business Review)
- 31% of those using ML and AI in sales and marketing say they have increased revenue and market share. (Harvard Business Review)
- Marketing leaders (66%) say machine learning and automation allow their teams to focus more on strategic marketing activities. (Think With Google)
- 61% of marketers say machine learning and AI are the top priority for their data strategies. (Zippia)
- Marketing leaders are more than twice as likely to report investments in ML technologies and automation for marketing activities. (G2)
- More than 50% of leading performance agencies have shifted more than 30% of their time to strategic activities thanks to machine learning. (Think with Google)
- 7% of respondents see a fear of job loss among sales and marketing teams due to the use of AI and automation. (Harvard Business Review)
- Machine learning has improved 47% of sales and marketing efforts for early adopters. (Deloitte)
Future of Machine Learning
Save time
30% of global IT professionals say their employees are saving time with AI
2025
AI and machine learning will help increase labor productivity by up to 37% by 2025
97 million
new jobs in 26 countries will be created by 2025 as a result of AI adoption
- Over the next three years, organizations that adopt intelligent automation will realize a 31% reduction in operational costs. (Deloitte)
- 30% of global IT professionals say their employees are already saving time with new AI and automation software and tools. (IBM)
- By 2024, AI-powered organizations will respond to customers, competitors, regulators, and partners 50% faster than their peers. (Oracle)
- AI and machine learning will help increase labor productivity by up to 37% by 2025. (Committee on Industry, Research and Energy)
- Global GDP could be up to 14% higher by 2030 (up to $15.7 trillion1 to the global economy) due to accelerated development and adoption of ML and AI. (PwC)
- 45% of total economic gains by 2030 will be the result of AI-enabled product improvements, stimulating consumer demand. (PwC)
- 97 million new jobs in 26 countries will be created by 2025 as a result of AI adoption. (World Economic Forum)
- Artificial Intelligence is now the 2nd most in-demand job based on Indeed’s 2020 Career Guide (Indeed).
- 3/4 of all elderly care services in Japan will be provided by AI robots by 2025 (Teks Mobile).
- 38% of U.S. jobs could be automated by 2030. (PwC)
Conclusion
ML has changed the way businesses operate on a daily basis. Sooner rather than later, all organizations will adopt ML one way or another. The reasons for this decision vary widely. Some are doing it simply to beat the competition, others because they understand the benefits it brings in terms of process automation, cost reduction, customer experience and accessibility.
But to achieve full adoption of ML, we need more professionals trained in the field. IT leaders’ biggest concern right now is that they can’t find the right talent within their teams or global job boards.
ML is here to stay and it’s predicted to continue to grow in the coming years. Maybe a career change to this field is just what you are looking for.
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