20 statistics showing the development of machine learning
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We are all familiar with asking Alexa and Siri to complete simple tasks for us such as setting a timer, playing a song, or reading us the latest news stories.
But do we know how fast the technology behind these digital assistants is evolving, and what they could be capable of in the near future?
Machine learning (ML) is the process that makes artificial intelligence models like Alexa and Siri possible- through the development of algorithms and statistical models. These computer systems are able to make decisions and predictions based on certain patterns in data without explicit instruction within its programming to do so. For example, Alexa making a mistake and using the data it receives to improve its performance for next time. This is the same for if the response was favourable.
Let’s take a look at some of the key statistics that will put into perspective how influential this technology could become in our day-to-day lives.
Global Figures
- In 2022, the global machine-learning market was valued at $19.20 billion (Fortune Business Insights)
- In 2023, this was valued at $26.03 billion (Fortune Business Insights)
- In 2024, this is valued at
- By 2030, the value is expected to hit $225.91 billion, at a growth rate of of 36.2% (Fortune Business Insights)
- Companies in India (59%) UAE (58%), Singapore (53%) and China (50%) are the worlds leading countries for AI adoption as of 2023.
- An IBM survey states 42% of enterprise-scale companies are already implementing machine learning, with a further 40% considering exploring this in 2025.
- Global 2000 companies are expected to allocate over 40% of their IT spend to AI initiatives
- Over $11 billion has been invested globally in the leading Machine learning platform, OpenAI.
The current benefits
- 97% of companies that already use machine learning say that they have only benefitted (not suffered) in terms of productivity levels.
- Tech companies currently using AI initiatives to add 9% in global industry revenue.
- 80% of busines owners reported that using machine learning rarely decreases business expenses but almost always increases profit
The current concerns
- AI incidents including mistakes from self-driving cars or facial recognition systems Increased by 32% between 2022 and 2023
- Inaccuracy, cybersecurity and explainability were the top 3 negative consequences for organizations that had implemented AI at the start of 2024
- Only 53% of companies check for data privacy implications in their machine learning project.
Industry breakdown
- Healthcare is the top industry predicted to be affected by machine learning, with the AI healthcare market valued at $15.1 billion in 2022 and expected to reach $187.95 billion by 2030
- Copywriters to see 50% increase in productivity using machine learning-powered tools.
- Public opinion of AI is also becoming more positive, with the customer acceptance rate of AI chatbots in healthcare rising to 27%, and in retail rising to 34%
Latest developments
- Machine learning can predict the highs and lows of the stock market with 62% accuracy.
- The error rate of the OpenAI speech recognition system was less than 5% as of 2019.
Stand out-stat
- Postings for AI specialist jobs are growing 3.5x faster than any other job categories
Why are industries wanting to implement machine learning?
IBM conducted research into the reasons behind such large adoption of AI and machine learning into a global business. 1 in 4 companies put this down to a lack of labour skills and shortage.
As we can see, machine learning is having a huge impact across several industries across the globe. AI technologies have the potential to have a huge positive effect on many industries, but trust and a skills shortage still stand as huge barriers before their full potential can be achieved.
For more resources like this, take a look at our other blogs.
Alternatively, see our Linkedin Newsletter the Friday Five to keep up to date with the latest advancements in tech and AI.
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