Artificial intelligence (AI) that can generate new content, including text, images, audio, and video, is known as generative AI. Generative AI models create new data that has similar properties after learning the patterns and structure of their input training data. Based on a variety of inputs, such as text, images, sounds, animation, 3D models, or other types of data, they can produce new content.
Music, visual art, and text-based content can all be produced using generative AI models.
Source: Safalta.comThey can also be used to produce artificial data or code. Recent developments in the field could fundamentally alter how we approach content creation. Certain tasks, like image recognition or natural language processing, are designed for other types of AI.
Market analysts anticipate that the global generative AI market will increase from $10.28 billion in 2022 to $13.69 billion in 2023. This represents a 33.1% compound annual growth rate (CAGR). By 2028, the market is anticipated to grow to $51.8 billion.
Because it has the potential to completely transform many industries, generative AI is significant. As an illustration, it can be used to develop novel artistic and musical forms as well as realistic synthetic data for training machine learning models. Additionally, it can be used to develop novel modes of interacting with our surroundings, like virtual reality and augmented reality.
Here are 50+ statistics on generative AI for 2023:
- 70% of companies will have incorporated GAI in some way by 2023, from content creation to customised recommendations.
- By 2028, the market for generative AI is projected to be worth $51.8 billion, expanding at a CAGR of 35.6% between 2023 and 2028.
- Marketing, healthcare, and finance are the top 3 sectors utilising generative AI.
- Generative AI is already being used or experimented with by 51% of marketers, and 76% of them think it will be essential to their overall strategy.
- According to 82% of marketers, generative AI has changed how they will create content in 2023.
- 37% of marketers use AI for SEO tasks like SERP comparisons and longtail keyword mapping.
- Investors in AI who reported a positive return on investment comprised 71% of the total.
- 90% of marketers claim that automation and AI reduce the time needed for manual labour.
- With 10 trillion parameters, the most recent language model, GPT-4, enables the creation of text that is human-like.
- By the end of 2023, chatbots with AI and sophisticated language models will handle 85% of customer interactions.
- AI-driven systems now produce more than 60% of the content produced for use in digital marketing, increasing productivity and consistency.
- Compared to human-generated content, GAI-driven content has 30% higher engagement rates.
- With GAI models achieving 98% accuracy in identifying rare diseases, medical diagnosis accuracy has seen a significant improvement.
- Research and development times have been reduced by 40% thanks to accelerated drug discovery processes.
- 80% of designers now use tools aided by generative AI, which has revolutionised graphic design.
- Popular art works that resemble Deep Dream have grown in popularity, showcasing GAI's artistic potential.
- To ensure ethical AI usage, 65% of businesses actively fund ethics research.
- According to estimates, AI will generate 12 million more jobs by 2025 than it will eliminate.
- Over 1,000 research papers are published each month in the burgeoning field of generative artificial intelligence.
- In 2023, OpenAI will release GPT-4, the result of years of study and development.
- 80% of marketers say that AI has made their jobs more enjoyable.
- According to 79% of marketers, AI improves the creative aspects of their job.
- Generative AI is used in some capacity by one-third of the AI 50 companies.
- A generative AI model typically costs $10,000 to $100,000 to train.
- GPT-3, the name of the largest generative AI model, has 175 billion parameters.
- By the end of 2023, the market for generative AI software is anticipated to be worth $3.7 billion.
- Sixty-one percent of workers either use or intend to use generative AI.
- According to 68% of employees, generative AI will help them provide better customer service.
- Workers predict that generative AI will increase their return on other technological investments by 67%.
- The emergence of generative audio tools in September 2023 will draw more than 100,000 developers.
- 30% of the messages that large organisations send out will be generated artificially by 2025.
- Within the next 18 months, generative AI has been prioritised by 67% of the IT leaders surveyed.
- Startups using generative AI are multiplying quickly. There will be 200 or so generative AI startups by 2020. This quantity is anticipated to increase to 1,000 by 2023.
- 53% of sellers reported being unsure of how to maximise the benefits of generative AI at work.
- 49% and 47%, respectively, of respondents said they lacked knowledge on how to use generative AI safely or effectively.
- Nearly 40% of sales professionals fear losing their jobs if they don't learn how to use generative AI in the workplace.
- In the last five years, the average amount of time needed to train a generative AI model has dropped from 10 years to 1 month.
- In the last three years, there have been a 200% increase in the number of generative AI startups.
- Generative AI is anticipated to have a $111 billion global market by 2030, up from $1.3 billion in 2022.
- By 2025, 80% of companies in the United States are anticipated to be using generative AI, up from the current 60%.
- In the next five years, generative AI, according to 70% of marketers, will be crucial for their companies.
- 60% of consumers are willing to pay more for goods or services produced by generative artificial intelligence.
- New types of music and art are being produced using generative AI, such as the AI-produced paintings that fetched millions of dollars at auction.
- Additionally, generative AI is being used to create novel interfaces with our environment, such as the increasingly well-liked virtual assistants.
- By 2025, large organisations' outbound marketing communications will contain 30% AI-generated content.
- By 60% to 70% less work will be done thanks to generative AI.
- More women than men will be impacted by generative AI.
- A potential annual increase in labour productivity of 3.3% will be facilitated by generative AI.
These are only a small sample of the numerous statistics demonstrating the growing significance of generative AI. We can anticipate seeing even more ground-breaking and innovative applications in the years to come as the technology advances.
ConclusionThese numbers demonstrate the possible effects of generative AI on the labour force. It is likely that more and more jobs will be automated as technology advances. This might result in job losses, but it might also open up new possibilities for the generative AI industry. We must be aware of these potential effects in order to be ready for them.
What is generative AI?
What are some of the benefits of generative AI?
It can save time and money by automating tasks that were previously done manually.
It can improve the quality of content by creating outputs that are more realistic and engaging.
It can generate new ideas and insights that would not be possible with traditional methods.
It can help us to better understand the world around us by creating new ways of visualizing data.
What are some of the challenges of generative AI?
The outputs of generative AI models can be inaccurate or misleading.
Generative AI can be used to create deepfakes, which are videos or audio recordings that have been manipulated to make it look or sound like someone is saying or doing something they never actually said or did.
Generative AI can be used to generate harmful content, such as hate speech or propaganda.
What are some of the applications of generative AI?
Marketing: Generative AI can be used to create realistic marketing materials, such as product images, website copy, and social media posts.
Healthcare: Generative AI can be used to design new drug molecules, develop new medical treatments, and personalize patient care.
Finance: Generative AI can be used to detect fraudulent transactions, predict financial markets, and manage risk.
Art and entertainment: Generative AI can be used to create new forms of art, music, and entertainment.
Data science: Generative AI can be used to create synthetic data that is used to train machine learning models.
What are the ethical considerations of generative AI?
The potential for generative AI to be used to create harmful content, such as deepfakes or propaganda.
The potential for generative AI to be used to discriminate against certain groups of people.
The potential for generative AI to be used to create unrealistic expectations about the world.
It is important to be aware of these ethical considerations and to take steps to mitigate the risks associated with generative AI.