Machine learning is completely transforming the business world globally. With Machine learning services businesses in numerous industries can deploy ML-based solutions to enhance productivity, improve customer support, help in decision-making, and much more.
The advancement of AI and ML algorithms helps businesses process massive data easily and enables organizations to process massive amounts of information quickly and efficiently. In this article, we are going to mention top Machine Learning Statistics, along with ML Market size, Adoption statistics, impact on business, marketing, and much more. So, let’s begin.
Machine Learning Key Statistics
- Companies can increase the customer satisfaction rate by 10% using Machine Learning according to Forbes.
- The Global Machine learning platform market size is expected to reach $31,36 billion by 2028. (Proficient Market Insights)
- The United States machine learning market was worth only $100 million in 2018.
- The AI market is expected to reach a whopping $500 mark by 2023 and a mark of $1,597 by 2030. (IDC, Precedence research)
- 76% of surveyed companies were prioritizing Artificial Intelligence and Machine learning over IT initiatives in 2021.
- 49% of respondents consider Artificial intelligence and Machine learning projects as high priority, and 28% of respondents consider AI and ML as top priority among the IT projects in 2021. (Statista)
- By 2030, the forecasted global explainable AI market size is expected to reach $21 billion. (NMSC)
Machine Learning Market Size
The Machine learning market size has been witnessing growth in the last few years. One of the most prominent segments of this market is its deep learning software which is predicted to reach $1 billion by 2025.
Let’s look at the statistics of Machine learning market size to understand the impact of ML today and in the future:
- In the first quarter of 2019, the total funding allocated to ML globally was $28.5 billion.
- The estimated size of the United States deep learning software market is expected to reach $80 million by 2025.
- The machine learning market size is projected to reach $158.80bn in 2023.
- An annual growth rate of (CAGR 2023-2030) of 18.73% is expected with the market volume resolution of $528.10bn by 2030.
- The United States is expected to have the largest market size in global comparison with $56.75bn in 2023.
- $117.19 billion is the global machine learning market expected in 2027 at a CAGR of 39.2% during the forecast period.
Machine Learning Adoption Statistics
The adoption of Machine learning has reached completely new heights with more and more businesses globally implementing ML algorithms to enhance their capabilities. Here are the statistics on how ML adoption is changing the functionality of businesses and companies around the world.
Experts forecast the Global Machine learning adoption rate between 2018 and 2024 to be around 42% CAGR
According to Statista, various businesses are adopting machine learning on a massive scale, with 65% believing that ML technology will be beneficial for analyzing and operating data and making useful decisions.
91.5% of companies have an ongoing investment in Machine learning and Artificial Intelligence
Machine learning is one of the most critical aspects that allows various AI applications and technologies to function and resolve problems. This includes standard deviation observations, speech and pattern recognition, robotics, predicting the stock market’s highs and lows, and much more.
Accessing Machine learning rarely decreases business expenses, but it does help increase the revenue reported by 80% of individuals in a report by McKinsey
Often people expect a decrease in fundamental cost when leveraging machine learning techniques and statistical models. However, accessing machine learning can help increase revenue.
25% of IT leaders state that machine learning programs are capable of helping to curb security risks
One of the top concerns faced by businesses globally is security. Regardless of machines and technology getting more advanced day by day, hackers often find a new way to outmaneuver them and access their private data. However, thanks to machine learning today IT leaders are able to curb security risks in their companies.
33% of IT leaders implement Machine learning to enhance their business analytics processes
Machine learning is crucial for business analytics as companies generate terabytes of real-world data points every second. Applications that leverage machine and statistical learning algorithms are so high in the market today since they assist business owners in better understanding big data.
Machine Learning in Voice Assistants
Machine Learning contains a subset called “deep learning.” It is developed around ML practice and is responsible for generating platforms behind voice assistants including Siri, Google Assistant, and Echo.
Here are some of the statistics related to Machine Learning in Voice Assistants.
- The value of the Global Natural language processing market is expected to reach $42.04 billion by 2026.
- 50% of individuals globally utilize voice assistants which is roughly 3.25 billion.
- The Global COVID-19 pandemic impacted the usage of voice assistants as AI usage increased by 7%.
- According to voicebot, there was a rise in the usage of voice assistance multiple times a day by 5% in 2022.
- Around 80.5% of users under the age of 30 are likely to utilize voice assistants in smartphones compared to 60.5% of users in the oldest age group.
Machine Learning in Business
Machine learning has been embraced globally by numerous businesses and organizations. This technology has been involved in driving innovations in various enterprises allowing them to generate smart processes using AI with learning capabilities.
Here are the statistics of machine learning in businesses.
- The productivity of businesses can increase by 54% by leveraging Machine Learning algorithms.
- 15% of organizations and businesses are already utilizing Machine learning to improve their businesses.
- C-level executives are responsible for looking after 75% of AI projects in various firms.
- 15% of manufacturing businesses claim they are willing to utilize AI in production.
- 75% of businesses utilize AI and Machine learning to improve customer satisfaction by 10%.
- In 2021, there were a total of 4400 funding rounds for Machine learning businesses raising a total of $73.7 Billion from across all rounds.
Machine Learning in Marketing
Machine learning has also impacted the marketing and sales industry by improving the accuracy of lead scoring, improving customer churn prediction, generating pricing models, and much more.
Here are the top statistics about machine learning in marketing to help understand how ML is reshaping the marketing industry.
61% of marketers state that AI and ML is one of the most crucial parts of their data strategy
The demands and expectations of customers have changed. Today users need to interact personally with the customers to gain their attention which requires effective marketing of products and services.
Due to this marketers are investing in Artificial Intelligence and Machine learning to personalize their content and run various campaigns that can help provide excellent user experience to their customers.
87% of Artificial Intelligence adopters states they consider using AI and ML for sales forecasting and improving email marketing
The usage of Machine learning for sales forecasting and email marketing can help fasten customer churn prediction, generate dynamic pricing models, enhance lead scoring accuracy, and much more.
According to a survey conducted by Refinitiv 16% of respondents believed Machine learning is capable of improving the sales and marketing campaigns
Numerous businesses and companies believe that the usage of machine learning algorithms for targeted marketing can be more efficient compared to old-school advertising tactics.
Marketing and sales are considered the most profitable sections to incorporate machine learning systems
Machine learning allows businesses to personalize algorithms to create suitable product recommendations tailored to users who visit the site or platform. These algorithms are derived using numerous data sets on customer behavior which can be helpful to increase customer retention and sales.
Machine Learning for Retail
- The three largest areas of Machine learning and Artificial Intelligence in the Retail industry are Personalized design and production, inventory and delivery management, and anticipating customer demand. (PwC)
- The Global Artificial Intelligence and Machine learning in the retail market was $8.41 billion in 2022. The market is expected to grow and reach $45.74 billion by 2032 at a CAGR of 18.45% during the forecast duration of 2023-2032. (Precedence Research)
- In the United States retail industry is expected to remain the largest AI and ML spending industry from 2021-2025 according to IDC.
Machine learning for healthcare
- The Global AI in the healthcare market is expected to reach $187.95 billion by 2030 with a CAGR of 37% from $11.06 billion in 2021. (PwC)
- The three leading areas with the highest AI and ML potential in the healthcare industry are ML-based medical diagnosis tracking incidences of diseases, and imagining diagnostics. (Precedence Research, Statista)
- North America is the leading AI and ML in the healthcare market accounting for more than 58% of the market share in 2020 and it is forecasted to continue up until 2030. (Precedence Research)
- 98% of healthcare businesses or organizations already contain an AI strategy or are in the process of implementing one. (Optum)
There is no doubt that machine learning is transforming the business world globally and enhancing the productivity of businesses in numerous industries whether it be marketing, healthcare, retail, or more.
Due to this more and more companies are investing in Machine learning. Above we have listed down Machine learning statistics including its market size, Adoption, Impact on business, retail, and much more.
For a deep dive into the data that fuels algorithms and drives the machine learning revolution, check out our detailed article on Big Data Statistics.