Top 30 AI Statistics You Need to Know for Your Business

Rakesh Patel
Rakesh Patel
September, 12 2024
Top AI Statistics

With each passing day, it becomes more evident that artificial intelligence (AI) technologies are here to stay. In the modern era, AI technology will likely power everything from your web browser to your refrigerator. However, to know how prolific AI’s impact is, we need to look at key AI statistics to gain a comprehensive overview of the industry.

Staying on top of the industry is especially crucial since many expert sources, such as McKinsey, have said AI is the fourth industrial revolution to deliver a massive impact. AI statistics will also help businesses identify the areas and markets they could capture with brand-new AI-related products and services.  

This is why, to give you the best-curated insights into the AI market, we have compiled this list of the top 30 artificial intelligence statistics you need to know in 2024. Unlike usual articles, we have covered everything from the global market share of different sectors to user trends with AI to help you make informed decisions for your business.

Introduction to the AI Industry

Artificial intelligence has always been the key to improving any product. AI made everything from enhanced surveillance to process automation possible solely. However, these solutions were often restricted to enterprise use cases, so only the largest corporations could afford them.

After the introduction of popular consumer-grade AI models such as ChatGPT, businesses of all sizes had free access to AI’s generative powers. This led to far higher adoption rates by Small and Medium-sized Enterprises (SMEs) along with proportional efforts from AI software development providers. Even automotive organizations implement AI to make autonomous self-driving cars. 

As the market adopts artificial intelligence’s transformative force, more individuals from all sectors are constantly ideating how AI can be used further for automation. However, almost all the popular AI solutions use standard global AI technologies, for which plenty of pre-trained models can be readily integrated to create brand-new products.

Essential AI Technologies Powering Modern Solutions

  • Natural Language Processing (NLP): The technology that enables machines to understand, interpret, and generate human language. Applications include chatbots, language translation, sentiment analysis, and speech recognition.
  • Computer Vision: The field of AI enables machines to interpret and make decisions based on visual data, such as images or videos. It’s used in facial recognition, object detection, autonomous vehicles, and medical imaging.
  • Recommendation Systems: AI systems that predict and recommend items to users based on their preferences and behavior. These are commonly used in e-commerce, streaming services, and social media.
  • Machine Learning (ML): A subset of AI that involves training algorithms to learn from and make predictions or decisions based on data. It includes supervised learning, unsupervised learning, and reinforcement learning.
  • Predictive Analysis: This technology involves using statistical algorithms and machine learning techniques to analyze historical data and predict future events or trends.It is widely used in various industries to make data-driven decisions that anticipate future conditions and optimize performance.

30 AI Statistics for 2024 by Category

To give you an overview of the AI industry, we have divided the most relevant statistics into categories that represent a trending AI technology or market. We ensured each statistic within a category was highly relevant to its respective subject and provided business owners with some key insights into the AI market.

Global AI market statistics

1. The global AI market size is predicted to reach a collective valuation of $826.7 billion by 2030. This industry growth will occur at a healthy Compound Annual Growth Rate (CAGR) of 28.46% between 2024 and 2030. [3]

2. One-third of small businesses know AI tools and have already started using them as a marketing strategy. The rest of the small business owners reported that they are interested in experimenting with AI further to see how they can integrate it into their operations. [2]

3. 65% of C-suite executives discussed AI usage within the workplace and expressed that they are not concerned with the presence of AI to handle menial tasks. However, only 46% of managers had the same sentiment towards integrating AI into their work. [1]

4. The top two use cases in which employees use artificial intelligence the most are writing and personal assistance, which comprise more than half of the usage area. These two AI applications stand at 61% and 51%, respectively, in terms of usage proliferation among the workforce. [1]

5. As of March 2024, the largest market share for artificial intelligence solutions is captured by the healthcare sector at 15.7%, followed by finance and manufacturing at 13.65% market share. [3]

6. 63% of North American small business owners state that they know that AI tools exist to help them grow their business and are interested in implementing AI technology within their business operations. [8]

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AI-powered voice search statistics

7. The voice search feature is utilized by nearly half of consumers over 55, standing at  43% utilization. The number of regular voice search users spikes among younger users, with 58% of consumers between the ages of 25 and 34 reporting using the feature daily. [4]

8. Approximately 50% of the population in the United States already use voice search solutions, with Google Assistant and Siri being the top choices for AI-powered voice assistants. [18]

9. The top use case for AI-powered voice assistants was looking up weather reports (17%), followed by local search queries for restaurants and fuel stations (16%). Hands-free search during driving is also a rising use case for AI assistants (14%).  [4]

10. The estimated savings by implementing AI-powered voice-enabled medical transcription technologies will be over $12 billion annually by 2027.  [7]

11. The Opportunity for consumer-facing AI-powered healthcare apps is booming as the healthcare voice assistant market is valued at $5.8 billion in 2024. 72% of patients also state that they are comfortable using AI tools for scheduling appointments or ordering medication. [7]

Generative AI statistics

12. North America and the European Union collectively dominate the generative AI space with over 68% market share. The Asia-Pacific region comes in third with just 22.2% of the market share in generative AI. [17]

13. The utilization of generative AI regularly is dominated by marketing teams at 34% of total daily users and primarily to refine marketing strategies. [11]

14. Within the next 18 months, IT leaders will prioritize generative AI projects at 67%. 33% of IT leaders also mentioned that generative AI was their top priority. [5]

15. The popular generative AI tool ChatGPT is reported to have increased individual work productivity by reducing the time taken for project completion by 40%. Subsequently, the use of ChatGPT also escalated overall output quality by 18% [6]

16. The product and service development sector comprises 23% of daily users for overall generative AI utilization. The primary use case for development teams is developing custom designs and making testing and simulations faster. [11]

17. Around 18% of the global workforce jobs could be affected by generative AI tools. This translates into roughly 300 million jobs being affected, with individuals working white-collar jobs being the most vulnerable group. [2]

Statistics for wearable AI devices

18. The total wearable AI market is currently valued at $38.85 billion in 2024 and is projected to grow to $260.92 billion by 2032. This represents tremendous growth at a CAGR of 26.8% for the entire sector. [13]

19. The dominant wearable AI device in the consumer market is the smartwatch as it boasts the highest revenue share at 30.2%, which is higher compared to all other competing device types. [12]

20. As of 2024, wearable AI devices are the least represented in voice search metrics. Only 14% of respondents reported using a wearable device for using AI voice assistants. [18]

21. North America is the leading region in wearable AI market size, controlling over 27.9% of global revenue from wearable AI devices. However, the Asia-Pacific region will witness the fastest growth in the global market size. [12]

22. Regarding components, the primary cost for wearable AI devices is sensors such as accelerometers, oximeters, and gyroscopes. These sensors comprise about 54.4% of the overall device cost, with connectivity modules and processors coming in second and third, respectively. [12]

Statistics for user behavior with AI

23. Workers with a mental or physical disability are 8% more likely to consider the adoption of AI technologies to help with daily tasks and responsibilities. The global AI adoption likelihood stands at 29%; meanwhile, the same likelihood stands at 37% for disabled individuals. [1]

24. Marketers primarily use generative AI solutions for ideation. 45% of marketers listed inspiration as their top use case and reason for AI adoption. The least reported use case is writing, with only 8% of marketers stating that they use artificial intelligence to write content. [9]

25. IT professionals from India and China report the highest adoption rate of AI in their workflows, stating that 60% of all organizations already have AI protocols. Meanwhile, professionals from other countries, such as South Korea, report that only 22% of organizations actively use AI. [10]

26. 40% of frontline workers do not trust leadership with AI’s usage at work and believe they know how to integrate AI best to accommodate customers. When asked if they believe they can change how they do things at work with AI, 53% of respondents agreed. [1]

27. Upon surveying marketers, 46% of respondents stated that AI would create new jobs within the marketing industry. Meanwhile, only 32% believed that AI would displace jobs for marketing professionals. [8]

AI regulation statistics

28. Almost 50% of all governments across the globe are predicted to enact regulations against AI in favor of user privacy and security. These regulations will also serve as a barrier to protect corporations against unethical applications and will place greater emphasis on the responsible use of AI technology. [16] 

29. The European Commission launched an AI pact on the 1st of August 2024 for organizations to enroll in to discuss potential security solutions to be integrated into AI products to increase user safety. This pact is mainly focused on high-risk AI sectors such as infrastructure and healthcare, where the accuracy and resilience of the technology are critical. [14]

30. States like Colorado have enacted legislative regulations for consumer-grade AI products to prevent algorithmic discrimination. The act states that post the 1st of February 2026, all developers of high-risk AI products will disclose potential risks and countermeasures taken to prevent an individual from algorithmic discrimination caused by AI. [15]

Implications of AI Statistics for Businesses in 2024

Now that we’ve looked at a bunch of statistics from the AI market, it is time to understand what this means for business owners. Judging by the global AI market size for different sectors, businesses must know many opportunities and pitfalls. Some of these key areas to look out for are as follows:

1. Leveraging niche AI models

As user demands with AI models increase, AI tech must evolve accordingly. Typically, developers and AI development services focus more on refining general models to fit these needs. However, an emerging trend is to use niche AI models that are purpose-built for exclusive use cases. Such AI models help businesses build a better AI product by:

  • Lowering upfront investment: Niche AI models are often much smaller in scale than general AI models, given that they have a specific function, such as language translation or anomaly detection. This leads to a lower AI development cost.
  • Enhanced customization: Niche AI models are often custom or community-developed, so they offer many more customization options than a closed general AI model. This allows for greater fine-tuning and customization, which directly translates into better model performance. 
  • Better performance: Niche AI models require much less computing power to produce results as they usually work with refined training data. This reduces the data processing load to produce an acceptable result, which allows the solution to be faster.  

A practical example of how a niche AI model would help in a real-world scenario is how a healthcare startup uses a niche AI model tailored for medical imaging. In this scenario, they would run it locally for reliable diagnostics without heavy infrastructure while customizing it to their specific needs.

2. Increasing adoption of AI for smaller businesses

As the global AI market progresses, more small businesses are looking to invest in AI development tools such as Mintlify for software documentation to offset the cost of talent and increase productivity. Since the saturation of such businesses using AI is so low, it can be inferred that the growth for AI products for small-scale applications will increase demand. 

To meet the rise in AI adoption, independent software vendors must ramp up the production of brand-new solutions. This gives businesses a tremendous opportunity to align their workforce towards AI training to keep them ready for the future, when AI tools will have much higher market penetration. 

Businesses are advised to consider developing their own AI solutions and machine learning algorithms, as they could discover new use cases that greatly improve workplace productivity.

3. Demand for multimodal AI models

Given the current artificial intelligence growth statistics, mobile AI models seem to be the next frontier in the world of smart virtual assistants. However, since mobile users typically use voice commands in tandem with written prompts, it is increasingly critical to have multimodal AI models which can serve multiple input types. 

The same scenario applies to the professional generative AI market, where instead of providing multiple input options, the model is supposed to provide multiple output formats. A popular example is Microsoft’s CoPilot, which amalgamates multiple generative AI models from OpenAI to give users a one-stop solution for all of their AI-generated content requirements. 

But again, with such complicated AI models, performance demands also go up, as they demand powerful natural language processing models that can support different input types. Businesses using multimodal output models face the same issue, as they need to understand the format of the desired output, which increases resource usage.

4. Increased workforce productivity with AI

With the rise of AI technologies, more workers are starting to adopt AI globally to increase their individual productivity. Even in legacy conservative organizations, the spread of structured artificial intelligence implementation programs is rising in the following ways:

  • Worker training programs: To enhance the effectiveness of AI, dedicated programs are being made for workers to understand the basics of prompt engineering. This is done so that the accuracy of responses is improved leading to better productivity. 
  • Custom AI development: With the increasing AI adoption rate among workers, companies are investigating the viability of developing a custom AI solution to empower their workforce with a purpose-built program that increases output speed and quality. 
  • AI integration: For more traditional workforces, the implementation of AI within existing applications is on the rise. Such integrations are being pushed to make the transition smoother for workers that are well-adapted with legacy solutions. 

Such rapid increases in productivity show how AI service revenue will increase in the coming years. This is also a great opportunity for other product businesses to release their offerings to address the gaps within enterprise AI solution markets.

5. Compliance with legislation around AI

One of the more concerning areas that businesses need to consider when using AI solutions is the upcoming legislation surrounding the field. Most of these legislative actions are centered around data privacy and the responsible use of AI. Let us look at which types of laws are currently impacting AI projects the most. 

  • User data privacy:  Regarding data privacy, actions such as data scraping are seeing increasing conflicts as they breach the privacy of the data owner and might also violate copyright infringement laws.
  • Ethical usage policies:  With the prevalence of AI there is a risk of users interacting with AI to get real-life decisions. However, due to possible algorithmic discrimination jurisdictions have emphasized that AI solutions must be engineered to prevent such instances of misinformation. 
  • AI reliability standards: The latest trend among governing bodies is to examine the reliable use of AI. These actions are aimed at helping large corporations understand the risks of AI within critical infrastructure to enhance resilience. 

Considering such heavy legal implications, it has become increasingly important for corporations to test if their AI products violate any regional guidelines thoroughly. If your project is built for essential services such as healthcare or law enforcement, it is also possible that you will have to meet additional compliance standards such as HIPAA and GDPR.

How We Sourced Our Statistics

We used stats and estimations from the world’s best data sources to find these statistics. Including research documents from organizations such as MIT and McKinsey. Each statistic mentioned throughout this article is accompanied by a number that denotes where it was sourced from. The sources above have been listed below: 

  1. Qualtrics
  2. Everest Group
  3. Statista
  4. UpCity
  5. Salesforce
  6. Massachusetts Institute of Technology
  7. Augnito
  8. Unbounce
  9. Hubspot
  10. IBM
  11. Mckinsey & Company
  12. Grand View Research
  13. Fortune Business Insights
  14. European Commission
  15. NSCL
  16. Gartner
  17. Precedence Research
  18. AnsweriQ

FAQ About AI Statistics

Which industry is the most likely to adopt AI technologies?

According to multiple sources, such as ResearchGate, the industry that has shown the most interest in investing in AI technology is banking and finance. This is because AI can increase banking industry revenue by solving several consumer challenges. This includes giving customers curated asset management features and performing autonomous customer support operations.

How does knowing the global AI market share help businesses?

Considering the global economy in terms of AI technology helps businesses discover emerging markets where they could potentially capitalize. Basically, keeping an eye on any AI market size allows businesses to discover new product ideas. They can subsequently launch them to capture any growing demand early and establish themselves as industry leaders.

Transform Your Project According to AI Statistics with Space-O

Throughout this blog, we have explored the different statistics and trends for the AI industry as of 2024. You gained comprehensive insights into the AI market and were also introduced to trends within brand-new concepts such as AI-enabled voice search. 

We also compiled our knowledge of the statistics to bring you key implications that you might want to keep in mind before embarking on your AI journey. But alas, all of this can sometimes be too complicated to keep track of when developing AI solutions. 

This is why we at Space-O offer our expertise in this domain to make building your AI product effortless. Having over 14 years of experience in the field, our talented developers and consultants are here to help you with any query surrounding AI.