AI is rapidly gaining momentum, impacting not just the tech world, but also fields like healthcare, hiring, arts, finance, and environmentalism.

In this article, we’ll explore 100 of the most interesting AI facts and statistics from 2024, covering both industry-wide trends and niche insights—plus a few predictions for 2025.

Let’s get started.

Quick stats and facts

Let’s start with five quick facts about the AI market.

1. The AI market is estimated to reach a $826B by 2030.
2. Global revenues from AI in enterprise applications are expected to rise from $1.62 billion in 2018 to $31.2 billion by 2025.
3. By 2025, the AI sector is expected to require 97 million specialists to meet job demand.
4. 97% of mobile users rely on AI-powered voice assistants.
5. 46% of companies leverage AI for managing customer relationships.

Predictions for 2025

In 2025, there are 5 predictions that you should be aware of.

1. More agentic workflows: By 2025, AI will enable more autonomous, agentic workflows, where AI systems take proactive actions, making decisions and completing tasks without human input. Models like the o1 by OpenAI is starting to enable these workflows with more capable reasoning models, that can be useful for the planning stage for each agents. This will create more tooling needs to evaluate and measure the performance of agents, something we’re very familiar with at Vellum.
2. New Voice-powered apps: OpenAI leads the way here with their Realtime API, where developers can now build fast speech-to-speech experiences into their applications — signaling a trend in the market.
3. The Stable Diffusion moment for video: AI tools, like the Sora model, will revolutionize video creation by automating editing, enhancing personalization, and generating original video content, leading to disruptions in how media is produced and consumed.
4. Coding on auto-pilot: Right now, tools like Cursor AI and Copilot are getting a lot of attention. But by 2025, we’re likely to see agentic workflows that can handle coding tasks entirely on their own. On top of that, it’s very possible we’ll see a website or app built entirely by AI that hits $500K in ARR, driven by a solo founder and going viral.
5. AI regulations and transparency: The demand for AI regulation will increase, leading to stricter rules and the development of transparent AI systems. By 2025, organizations will be required to provide clearer explanations of AI decision-making processes to improve reliability.

General facts

Next, let’s discuss some general facts surrounding the world of AI.

AI Investment

AI isn’t happening in a vacuum. Billions are being invested in the space, and it’s only expected to soar in coming years.

1. The AI market is estimated to be worth $184B in 2024, jumping over $100B in value from the previous year.
2. The AI market is estimated to reach a $826B worth by 2030. Alternative bullish estimates expect AI to surpass a trillion dollar market cap by 2030.
3. OpenAI and Microsoft are planning on building a super-computer with millions of GPUs that will cost more than $100B to build. The project is currently dubbed Stargate and should be running by 2028.
4. Google’s Gemini model cost between $30M and $191M to train without taking into account the salaries of the engineers that worked on it. GPT-4, meanwhile, cost between $41M and $71M.
5. Nvidia's dominance in the AI hardware sector has escalated, with the company projecting total GPU demand to reach $2 trillion. This is driven by the growing needs of AI workloads, such as training large language models (LLMs) and scientific simulations.
6. Global revenues from AI in enterprise applications are expected to rise from $1.62 billion in 2018 to $31.2 billion by 2025.
7. Over 60% of retail respondents in a recent study plan to increase their AI infrastructure investment in the next 18 months.
8. Among AI technologies, the deep learning segment captured the largest market share in 2023, with a 36.9% market share.
9. The number of AI-focused startups has increased 14x since 2000.
10. China and India have the [highest rate of AI adoption](https://www.bsigroup.com/en-US/insights-and-media/media-center/press-releases/2024/july/momentum-of-ai-adoption-strongest-in-india-china-and-us-finds-bsi/#:~:text=It identifies India as the,close third place%2C scoring 4.0.), followed by the U.S.

Technology

Let’s cover five core facts surrounding some modern AI techniques that have played a massive role in AI’s recent success.

1. BERT, or Bidirectional encoder representations from transformers, is a language model designed by Google that dramatically improved upon previous models like GPT-2. BERT is made up of a Tokenizer, Embedding module, Encoder, and a Task head.
2. In models like GPT and BERT, text is split into smaller parts called "tokens" (which can be words or pieces of words). Each token is then converted into a set of numbers, called an "embedding," which the model uses to understand and work with the text.
3. OpenAI trains its models on Nvidia chips, using both their A100 and H100 graphics chip, a super-computer built by tens of thousands of chips.
4. Models like DALL·E and GPT-4 have introduced multimodal capabilities, meaning they can process and generate not only text but also images. Using both vision and language models allows AI to generate images from text prompts or describe images in natural language.
5. Diffusion models, like those in DALL-E and Stable Diffusion, start with random noise and slowly refine it to generate clear, realistic images. This process is similar to how ink spreads in water, and these models are popular for creating detailed visuals from text prompts.

Usage

Let’s talk about how AI is being used today.

1. 65% of organizations regularly use GenAI. Through the same survey, over 70% of organizations use some type of AI.
2. The number of people using AI tools globally surpassed 250 million in 2023, more than doubling since 2020. This rapid growth is expected to continue, with users predicted to exceed 700 million by 2030.
3. Adoption of AI in sales and marketing doubled between 2023 and 2024.
4. Around 50% of organizations using AI are adopting off-the-shelf models with little or no customization, while industries such as energy and telecommunications are more likely to customize or build proprietary models for specific business needs.
5. A survey by MIT Technology Review found that businesses expect the number of job functions using generative AI to more than double in 2024.
6. A recent PWC report revealed that 96% of respondents plan to use AI simulations, such as digital twins. Simulations play a crucial role in AI by accelerating risk analysis, offering insights, predicting supply chain dynamics, and more.

Impact

Next, let’s survey the immediate impact of AI.

1. AI is expected to contribute $15.7 trillion to the global economy by 2030, driven by productivity gains and increased consumer demand for AI-enhanced products.
2. AI is increasingly embedded in everyday technologies, such as voice assistants (Siri, Alexa), recommendation systems (Netflix, Spotify), and smart home devices, making AI a seamless part of daily experiences.
3. AI is predicted to boost labor productivity by up to 40% in the coming years, as businesses adopt AI tools to streamline operations and enhance efficiency.
4. By the end of 2024, more than 8 billion digital voice assistants are projected to be in use globally, doubling from 4 billion in 2020, as AI continues to power voice interaction technologies.
5. 73% of businesses are projected to use AI for customer experience management by 2025, using AI-powered chatbots and recommendation engines to improve customer interactions.
6. 77% of consumers use some form of AI technology.
7. A survey by MIT Technology Review found that 81% of executives view AI as a significant competitive advantage for their business.
8. More than 33% of companies in a recent survey said they used AI in at least one business function.
9. 42% of businesses utilize AI for creating website copy, while 46% use AI for tailored advertising (46%).
10. AI has gained traction in phone call management, with 36% of respondents in a survey already using or planning to use it in this area, while 49% employ AI for optimizing text messages.
11. According to one study, developers expect to be 30% more efficient using generative AI assistants.

Job Market

One of the biggest impacts of AI is its impact on the job market. Let’s discuss the impact of AI on the job market in detail.

1. The demand for AI and machine learning skills has increased by 74% over the last four years.
2. A survey found that 73% of employers have made hiring talent with AI skills and experience a priority, but nearly 75% say they can’t find the talent they need.
3. AI is projected to create 97 million new jobs while eliminating 85 million by 2025, leading to a net increase of 12 million jobs.
4. Generative AI-related job postings have surged, with LinkedIn reporting a 21-fold increase in job listings mentioning terms like GPT or ChatGPT since November 2022.
5. As AI reshapes work, there is a shift from requiring traditional degrees to emphasizing skills. Many organizations now prioritize candidates with hands-on AI experience and alternative credentials.
6. 34% of companies in a recent survey reported a shortage of data scientists to meet their AI goals.

History

Let’s not just look into the future, but also survey the past, understanding the bedrock that the modern AI industry is built atop.

1. Neural networks, the foundation of many early AI systems, has its roots in 1943, when Warren McColloch and Walter Pitts wrote a paper on it. They built on ideas originally put forward by Alan Turing, who played a major role in WWII.
2. Known as the "godfathers of AI," Yoshua Bengio, Yann LeCun, and Geoffrey Hinton were instrumental in developing foundational deep learning techniques, which are crucial for generative AI models. Their work on neural networks in the early 2000s enabled the later development of generative models and earned them the 2018 Turing Award.
3. Eight Google engineers invented the "Transformer" architecture, which is the T in GPT, shaping the AI landscape we know today. Their groundbreaking paper, “Attention is All You Need,” set the foundation—and the rest is history.
4. ChatGPT featured the fastest growing user base, reaching 100M users in less than 3 months. It surpassed other popular consumer apps like TikTok (9 months) and Instagram (2.5 years).
5. RAG enables LLMs to append contextual knowledge outside of the training data to aid queries. It was invented by Patrick Lewis. His team didn't expect RAG to become a well-known acronym and regretted giving it such a banal name.
6. OpenAI was founded in December 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman, among others. The founders aimed to advance artificial intelligence in a safe and beneficial way for humanity.

Facts per industry

It’s not just general facts that stun; there are plenty of industry-specific facts that illustrate how impactful AI is.

Healthcare

1. The AI healthcare market, valued at over $22 billion in 2023, is expected to grow more than 36% each year from 2024 to 2030.
2. According to Stanford, AI is more proficient than humans are summarizing medical records. This has a serious impact because inaccuracies in EHR (Electronic Health Record) summaries could affect patient outcomes; in the same study, 36% of evaluators thought AI outperformed human summaries, with an additional 45% thinking they were comparable.
3. AlphaFold is a cutting-edge neural network model that can predict the 3D structure of proteins with atomic accuracy. It solved a problem that scientists have been working on for over 50 years. So far, 100,000 protein structures have been experimentally determined out of billions of sequences.
4. AI is not only diagnosing skin conditions like melanoma, but could also revolutionize dermatology training. AI-powered simulations can help dermatology trainees gain exposure to rare skin conditions, provide personalized feedback, and even improve surgical skills through virtual reality.
5. AI can be used to restore the voices of those that lost theirs due to a medical disability.  This is accomplished via voice banking, where previous recordings of their voice are used to power an AAC (augmentative and alternative communication) device that plays synthetic voices.
6. AI-driven platforms like Deep Genomics analyze genetic mutations to predict how they affect human biology, allowing researchers to expedite discovery of new gene therapies for rare diseases.
7. The AI in healthcare market was valued at $16.3 billion in 2022, and is expected to grow to $173.55 billion by 2029.
8. In 2021, about a fifth of healthcare organizations were in early-stage AI initiatives, and a quarter were in the pilot stage.
9. AI is used for a variety of purposes, including (i) drug discovery, asAI could reduce the cost of finding new drugs by 70%, (ii) hospital admissions, as predictive AI tools could reduce hospital admissions by half, and (iii) medication errors, as AI could save $16 billion by reducing medication dosing errors.

Finance

1. The global generative AI market in finance is expected to grow from $1.09B to $9.38B by 2032
2. 43% of respondents in a recent survey of financial firms have already implemented generative AI within their organization, while 46% are utilizing large language models (LLMs).
3. The perception of AI's potential to drive new operational efficiencies increased by 30% from last year, indicating that financial businesses are eager to adopt tools like generative AI.
4. Data issues have become the top concern for financial organizations adopting AI, rising from 28% to 38% since last year, marking a 36% increase.
5. AI is revolutionizing fraud detection by ****allowing financial institutions to analyze large datasets and detect suspicious activities in real-time. PayPal uses AI to quickly detect and respond to fraud, protecting both the company and its customers.
6. Banks and fintech companies are using AI to offer customized investment advice and financial planning. Wealthfront, for example, uses AI to provide automated investment management and deliver tailored recommendations based on individual user profiles.
7. A British mortgage provider reduced the average time for completing a mortgage application from 1-2 hours to 8-10 minutes with AI.
8. AI is ****helping banks assess borrower risk more accurately by analyzing non-traditional data sources. For example, Zest AI uses machine learning algorithms to assess credit risk for underserved populations, reducing biases in traditional credit scoring systems.
9. Many banks are incorporating AI into chatbots and virtual assistants that can offer 24/7 support. Bank of America’s AI assistant, Erica, helps customers with transactions, financial planning, and even fraud alerts, improving user experience and operational efficiency.
10. AI is helping financial institutions make better predictions about market trends and investment returns. BlackRock’s investing platform, Aladdin, uses AI to analyze large datasets for forecasting and risk management, helping investors make smarter decisions.

Retail

1. Retailers are increasingly adopting AI technologies, with 42% of those surveyed already utilizing AI and another 34% exploring or testing AI initiatives. Notably, 14% remain unaware of AI technologies applicable to their business needs.
2. In a recent survey, among respondents who have adopted AI, over 80% have implemented three or more use cases, and more than 50% reported having six or more use cases in active deployment.
3. Companies like North Face use AI to help customers find the perfect jacket by asking questions about the customer’s preferences and the weather conditions where they live.
4. More than 63% of retail companies use AI to improve customer interactions, and 40% have set aside teams and budgets for it.
5. AI enables retailers to optimize inventory management and supply chain operations. Walmart leverages AI to forecast inventory needs and restock items efficiently to minimize stockouts.
6. AI is revolutionizing dynamic pricing, allowing retailers to adjust prices in real time based on demand and competition. Zara uses AI to analyze market trends and adjust pricing for maximum profitability.
7. Retails are increasingly using GenAI ****to provide tailored recommendations for customers. For instance, Amazon uses GenAI-powered algorithms to suggest products based on users' past purchases, browsing behavior, and preferences.
8. Retailers are leveraging AI to address shrinkage, a $112 billion industry challenge. Notably, 54% of C-suite executives consider it one of their top AI applications, underscoring the urgent need to improve security and asset protection strategies.

Environment

1. AI is already being used in production to tackle climate change by companies like Pachama. Researchers are using AI to forecast environmental changes, optimize renewable energy systems, and even analyze satellite data to track deforestation and carbon emissions.
2. AI is being used to help protect endangered species. Organizations like Wild Me are using AI to analyze photos of animals and track their movements, helping conservationists monitor populations of species like whale sharks and giraffes in real time.
3. AI is helping scientists better predict and respond to environmental changes. NASA and IBM Research recently released a new foundation model for weather and climate to aid in storm tracking, forecasting, and historical analysis.
4. AI is helping reduce deforestation by monitoring forests and detecting illegal logging activities in real time. Global Forest Watch uses AI to analyze satellite imagery and alert authorities about deforestation hotspots, allowing for quicker intervention.
5. AI is improving waste management by optimizing recycling processes and reducing landfill waste. Companies like Everest Labs use AI-powered robots to sort recyclable materials from waste streams, increasing efficiency and accuracy in recycling facilities.

Agriculture

1. AI is being used to improve crop yields and reduce the need for pesticides. AI drones are used to monitor fields, detect crop health issues, and even perform targeted spraying of water or nutrients. This is particularly popular in America, where the working pool for farm workers is thinning.
2. AI is powering vertical farming by using machine learning algorithms to optimize plant growth through precise light, water, and nutrient delivery. They also can monitor for diseases to help contain outbreaks before they spread.
3. AI is improving soil management, ****helping farmers analyze soil conditions and make better decisions. For example, Teralytic’s AI-driven soil sensors monitor key metrics like moisture and nutrient levels, providing real-time insights to optimize planting and fertilization.
4. AI is supporting sustainable irrigation, reducing water consumption while improving crop yields. AI-driven platforms like Prospera Technologies analyze real-time data from sensors and satellites to provide precise irrigation recommendations, minimizing water waste.
5. AI is advancing livestock monitoring ****improving animal health and productivity. Cainthus uses AI-powered cameras to monitor dairy herds, analyzing cow behavior to improve dairy farm management.

Government

1. Some governments like Brazil are using AI to detect tax fraud, by reconciling goods and sales taxes with cargo trucks that are crossing interstates.
2. AI is being used to make smart traffic lights that minimize stoplight idling—something that is being piloted in Seattle.
3. NASA has been using AI to assist in space missions for a while, such as controlling the Mars rover and analyzing large datasets from deep space exploration. AI was key to helping discover new exoplanets by combing through Kepler data that had been previously overlooked.
4. AI is helping disaster response teams predict and respond to natural disasters. Tools like IBM’s Watson Decision Platform for Agriculture are used to predict the impact of hurricanes and floods, aiding governments and NGOs in preemptive action.
5. AI is enhancing government transparency, enabling public institutions to analyze and share data more effectively with citizens. The Estonian government uses AI to make public data more accessible and transparent, allowing citizens to easily access information about government decisions and services.

Manufacturing

1. AI is being used to predict equipment failures before they happen, reducing downtime and maintenance costs. For example, Siemens uses AI-driven analytics to monitor machinery and predict when maintenance is required.
2. Manufacturers are using AI to improve quality control by using computer vision to detect defects in products before they go out to customers. For example, General Electric employs AI to automatically identify defects in components and enhance quality assurance.
3. AI is helping companies optimize their supply chains by predicting demand and managing inventory in real-time. For example, Bosch utilizes AI to streamline its supply chain operations, ensuring timely delivery and efficient resource management.
4. AI-driven robots are being used to automate repetitive tasks in manufacturing and improve precision. For example, Tesla’s manufacturing facilities use AI-powered robots to assemble cars with minimal human intervention.
5. Manufacturers are using AI to optimize energy consumption in factories, reducing costs and environmental impact. AI platforms like Schneider Electric’s EcoStruxure use predictive algorithms to manage energy usage across manufacturing plants and improve sustainability.

Education

1. By 2025, AI is expected to enable fully personalized learning experiences, adjusting content and pacing based on individual student needs. Adaptive learning platforms like DreamBox and Squirrel AI are already tailoring education to fit different learning styles.
2. AI-driven tutoring systems, such as Carnegie Learning, provide students with real-time feedback and tailored guidance. These systems are designed to support students outside of the classroom, helping them improve in areas where they struggle.
3. AI is transforming the way assessments are conducted, allowing for more personalized and adaptive tests. AI-driven platforms can evaluate student performance in real time, offering more dynamic assessments that go beyond traditional exams.
4. AI is making virtual classrooms more effective by providing tools for automatic note-taking, transcriptions, and personalized content recommendations. Platforms like Coursera and Khan Academy integrate AI to support students with personalized course recommendations and supplementary learning materials.
5. AI is driving a shift toward continuous, lifelong learning, offering adults and professionals access to learning platforms that are normally built for early students. This will help bridge skill gaps in fast-evolving fields like technology and healthcare.

Telecommunications

1. The global AI in telecommunications market is projected to reach over $11 billion by 2030, with an expected compound annual growth rate of over 28% from 2023 to 2030.
2. In a 2023 survey, 90% of telecom companies indicated they were integrating AI, either in the assessment/pilot phase or actively implementing and using it.
3. Of telecom companies reporting they are using AI, 57% are utilizing GenAI to enhance customer service and support, 57% to boost employee productivity, and 48% for network operations and management.
4. McKinsey estimates that new GenAI use cases could generate up to $100 billion in additional value for telecommunications companies.
5. A recent report estimates that telecom companies will potentially gain $140 to $180 billion stemming from increased employee productivity.

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Arts

1. AI-generated music is picking up traction, where some algorithms can compose original pieces that mimic human emotion. OpenAI’s MuseNet, for example, creates 4-minute songs with up to 10 instruments, ranging across genres from classical to pop. However, this has triggered some pushback from artists.
2. AI is being used by some film directors to make editing decisions. For example, IBM’s AI Watson was used to create a movie trailer for the horror film Morgan by analyzing other trailers and selecting the best clips. However, this has generated pushback from creatives in the industry.
3. AI is helping restore and complete unfinished art**,** bridging historical gaps in creative works. A recent project used AI to analyze Beethoven’s compositions and complete his unfinished 10th Symphony, providing a unique collaboration between human musicians and AI.
4. AI is transforming how music is remixed and recomposed, allowing artists to create variations of existing songs. For example, Google’s Magenta AI uses neural networks to remix famous songs by understanding their structure, offering musicians tools to reimagine their own work
5. GenAI is being integrated into live performances, where it adapts to real-time inputs and enhances creativity on stage. For example, Refik Anadol’s immersive AI-generated visuals respond to music in live settings, creating dynamic environments for concerts and art shows

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Conclusion

AI has massive ramifications across sectors and for the technology market as a whole. It is a soaring space and will become a trillion dollar industry by the end of the decade.

It also poses massive questions for the future job market and our relationship with technology. We’re already seeing incredible niche applications of AI being rolled out; we cannot wait to see what the future holds.