Even before the release of ChatGPT in November 2022, in recent years, generative AI technology has become increasingly popular, due to its variety of use cases — from text-based conversations to image recognition and natural language processing. (Learn more about other generative AI examples.) Companies can also use generative AI to create synthetic data for training machine learning models. It can also be used to produce creative outputs, such as music and art.
As the use of ChatGPT, artificial intelligence (AI), and generative AI becomes increasingly prevalent, it's important to be aware of the latest statistics surrounding these technologies.
We've researched and compiled all the key stats you should know, grouped into the following sections:
Adoption of generative AI
AI and Generative AI market
AI's impact on businesses
Other generative AI stats
Adoption of generative AI
ChatGPT exceeded 1 million users 5 days after its launch (Greg Brockman, Co-Founder of OpenAI)
DALL-E, which uses OpenAI to generate images, took about 2.5 months to reach 1 million users (Sam Altman, Co-Founder of OpenAI)
GitHub Copilot, an AI-based programming tool for developers, had 400,000 subscribers within the first month of its release (Microsoft)
In the United States, adoption rate of generative AI in the workplace is the highest for Gen Z at 29% (Statista)
The technology sector is the top sector working with OpenAI, followed by education. (Enterprise Apps Today)
48% of individuals believe that neither Photoshop nor generative AI should be used in social media advertising (Statista)
Expected adoption of generative AI
By September 2023, generative audio tools will emerge and attract over 100,000 developers (stateof.ai)
By 2025, 30% of outbound messages from large organizations will be synthetically generated, up from less than 2% in 2022. (Gartner)
By 2025, generative AI will account for 10% of all data produced, up from less than 1% in 2021 (Gartner)
By 2025, more than 30% of new drugs and materials will be systematically discovered using generative AI techniques (Gartner)
By 2030, a major blockbuster film will be released with 90% of the film generated by AI, from text to video (Gartner)
By 2024, 60% of data used for the development of AI and analytics projects will be synthetically generated (Gartner)
AI and Generative AI market
In 2021, the artificial intelligence market was valued at approximately $59.67 billion USD and is projected to reach roughly $422.37 billion USD by 2028. (Zion Market Research)
The generative AI market is projected to reach $110.8 billion USD by 2030 (Acumen)
The Asia Pacific is the fastest growing regional market for generative AI (Acumen)
The revenue forecast for the artificial intelligence market in 2030 is $1.8 trillion USD (Grand View Research)
Investment in AI-related technologies
AI-enabled drug discovery and AI software coding are the two areas in AI that have received the most funding from venture capital firms over the last three years (Gartner)
In 2021, there was $93.5 billion USD of private investment in AI-related companies, which is double compared to 2020 (McKinsey)
More than two-thirds of generative AI companies have not yet raised a Series A round (or later) (CB Insights)
AI's impact on businesses and performance
66% of customer service professionals say that using AI has a positive impact on business performance (Dialpad)
Using Codex, a code generation tool, developers at Deloitte found a 20% improvement in code development speed (HBR)
Other generative AI stats
China dominates the search interest for ChatGPT, followed by Nepal and Singapore (Wired)
OpenAI’s AI detection software, known as classifier, can correctly identify 26% of AI-written text, while mislabeling human-written text as AI-written 9% of the time (OpenAI)
The GPT-3 language model has been trained on 175 billion parameters (OpenAI)
Food for thought
ChatGPT’s current model only contains data up to 2021, and is not focused in any one specific area or industry.1 (If, say, you run a healthcare contact center that needs to answer patient inquiries, you’d likely need a model that’s specifically trained on healthcare and medical data.)
Interested in using generative AI for your business?
Book a chat with our team to learn about how businesses and organizations are already using Dialpad AI to make their contact center, support, and sales teams more productive, with real-time insights and assistance for agents. Or, take a self-guided interactive tour of the app on your own!
FAQs about generative AI statistics
The generative AI market is growing rapidly due to increased demand and adoption of this technology. This is seen in the increasing number of investments in AI-related startups, as well as the number of companies launching AI-based products and services.
The generative AI market is projected to reach $110.8 billion USD by 2030, while the greater artificial intelligence market is forecasted to have $1.8 trillion USD in revenue within the same year.
Due to the various use cases, a number of industries can benefit from the use of generative AI. One industry, in particular, is the pharmaceutical industry. Generative AI can help scientists discover and design new medicine, which has typically been a long and expensive process. Beyond that, this technology is also impacting the automotive, aerospace, defense, electronics, and energy industries according to Gartner.
The art and design industry also benefits from generative AI through Imagen, DALL-E 2, Midjourney, and Stability AI. ChatGPT is starting to impact contact centers, such as enabling chatbots to “write” in a more conversational manner. Generative AI is also being adopted in other departments like sales, marketing, and software development.
It’s estimated that 30% of outbound messages from large organizations will be synthetically generated in 2025. The different use cases for generative AI will continue to expand as the technology is further developed.
As the technology itself continues to evolve, it's likely that AI will be able to create more complex, higher quality content and decisions. Additionally, the development of new AI applications will enable AI to gain an even deeper understanding of data, leading to more accurate and reliable results.
By 2030, it's expected that large language models will be able to create final drafts of AI-generated text, code, and images that are better than professional writers, developers, and artists, according to Global X Research.
References
1 help.openai.com/en/articles/6783457-chatgpt-general-faq