ChatGPT was the chatbot that kickstarted the generative AI revolution, which has been responsible for hundreds of billions of dollars in data centres, graphics chips and AI startups. Launched by...

The results of a survey conducted among recent college graduates in the United States show that the use of AI at school and work is common for Gen Z. Some ** percent of young adults in the U.S. said they already used generative AI to help with their classwork. Another ** percent also said they would see themselves employing these tools in their professional career. In comparison, ** percent of Gen Z had AI-related concerns of some kind.

During a 2023 survey conducted among professionals in the United States, it was found that 37 percent of those working in advertising or marketing had used artificial intelligence (AI) to assist with work-related tasks. Healthcare, however, had the lowest rate of AI usage with only 15 percent of those asked having used it at work. The rate of adoption in marketing and advertising is understandable, as it is the industry that most weaves together art and creative mediums in its processes.

Generative AI linked to education

Those positions that require a higher level of education are most at risk of being automated with generative AI in the U.S. This is simply because those jobs that require less formal education are rarely digital positions and are more reliant on physical labor. Jobs that require tertiary education, however, are still the least likely to be automated overall, even with the added influence of generative AI.

ChatGPT has competitors

While the OpenAI-developed ChatGPT is the most well-known AI program and the currently most advanced large language model, - other competitors are catching up. While just over half of respondents in the U.S. had heard of or used ChatGPT, nearly half of respondents had also heard of or used Bing Chat. Google’s Bard was slightly behind, with only around a third of Americans having heard of or used it.

During a 2022 survey conducted among professionals in the United States, it was found that 29 percent of respondents belonging to Gen Z used generative AI tools. Moreover, 28 percent of Gen X and 27 percent of millennials respondents used such tools, respectively.

Generative AI

Generative artificial intelligence (AI) refers to algorithms that focus on producing new content, such as text, images, music, speech, code, or video. Generative AI is part of deep learning, the machine learning branch which aims to reduce the manual work of programming parameters for AI. Currently, researchers and developers use generative AI in various industries, like advertising and marketing, but rumors suggest that more businesses and consumers will adopt this technology in the near future to perform a wide range of tasks.

ChatGPT

An example of generative AI is ChatGPT, the famous chatbot software launched in November 2022 by the American startup OpenAI, which is also well known for its art generative AI program Dall-E. The chatbot can produce text based on given inputs, recognize mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT has quickly gained popularity, becoming one of the major breakthroughs of the last few decades in the technology industry. Indeed, it was the fastest IoT service to accumulate a one-million user base, in only five days.

The Generative AI Tools market is experiencing explosive growth, driven by advancements in deep learning and the increasing availability of large datasets. While precise market sizing data is unavailable, considering the rapid adoption across various sectors and a projected Compound Annual Growth Rate (CAGR) – let's conservatively estimate it at 35% – the market is poised for significant expansion. By 2025, the market size likely surpasses $10 billion USD, with a projected value exceeding $50 billion by 2033. Key drivers include the increasing demand for automation in content creation, software development, and design, coupled with the ability of generative AI to personalize user experiences. Emerging trends like the integration of generative AI into existing software applications, the rise of multimodal models (combining text, image, and other data types), and the development of more ethical and responsible AI models are shaping the market's future. Significant restraints include the high computational costs associated with training and deploying generative AI models, concerns regarding data privacy and bias in AI outputs, and the need for skilled professionals to effectively utilize these tools. Market segmentation reveals a strong presence across private and enterprise applications, with Text Generators currently dominating the type segment, followed by Image Generators and Code Generators. However, rapid growth is anticipated in Music and Audio Generators, driven by innovations in AI-powered music composition and sound design. Major players like OpenAI, Google (Alphabet), Microsoft, and others are fiercely competing, driving innovation and accessibility within this rapidly evolving landscape. Geographical distribution shows strong initial growth in North America and Europe, but emerging markets in Asia-Pacific and other regions are expected to contribute significantly to the market expansion in the coming years.

The U.S. Healthcare Generative AI Market size was valued at USD 563.56 million in 2023 and is projected to reach USD 4950.41 million by 2032, exhibiting a CAGR of 36.4 % during the forecasts period. Recent developments include: In January 2024, Microsoft's Nuance Communications announced the DAX Copilot (DAX), an AI-powered solution that integrates with the EHR available with Epic Systems Corporation. This tool automates clinical documentation by improving access to compilation during patient exams which enhances healthcare outcomes. , In December 2023, Google introduced MedLM, a family of foundation AI models designed for healthcare use. These models are now available to Google Cloud customers in the US through the Vertex AI platform. , In September 2023, Oracle launched the Oracle Clinical Digital Assistant, a new generative AI services for healthcare organizations which is integrated with Oracle's EHR solutions, allows providers to use generative AI and voice commands to reduce manual work, allowing them to focus on patient care. Patients can also take self-service actions using voice commands. , In September 2023, Microsoft Corp. and Mercy partnered to utilize generative AI and other digital technologies to enhance patient care and patient experience, marking a significant shift in healthcare towards utilizing advanced digital technologies for consumer care delivery. , In August 2023, HCA Healthcare and Google Cloud partnered to utilize generative AI technology to enhance workflows, particularly in clinical documentation, allowing doctors and nurses to concentrate more on patient care by reducing administrative tasks. , In August 2023, Microsoft and Epic partnered to address the use of generative AI in healthcare by combining Microsoft's Azure OpenAI Service with Epic's deep understanding of clinical procedures and electronic health records to tackle pressing issues in healthcare , In July 2023, AWS HealthScribe, an AI-powered solution for healthcare software providers that helps doctors with paperwork, has been released by Amazon Web Services. The program assists clinicians in creating transcripts, drafting clinical notes, and analyzing patient discussions through the use of generative AI and voice recognition. , In March 2023, Enlitic introduced Enlitic Curie, a platform that makes it easy for radiology departments to manage their workflow. The platform hosts Curie|ENDEX, which utilizes NLP and computer vision for the analysis & processing of medical images, and Curie|ENCOG, which leverages AI to identify and protect Protected Health Information , Northwestern Medicine, Chicago's academic health system in the Midwestern region of U.S., employs Microsoft Fabric's healthcare data solutions to integrate clinical data, meet regulatory requirements, and unlock insights using generative AI, thereby enhancing patient care quality. .

ChatGPT, developed by OpenAI, is the most widely known generative AI software in the U.S. in 2023, known by ** percent of respondents. ********* of respondents had used or heard of the program. This is unsurprising, as its launch into the public sphere at the end of 2022 was heavily documented by a wide variety of media. Stable Diffusion, an image generator AI, was lesser known, with less than a quarter of respondents having heard about it or used it. Cautious of the new tech While generative AI has a tremendous amount of potential for improvement and efficiency in everyday life, it is a simple fact that many users are not ready to trust this technology yet. This is for a variety of reasons, with some believing it to be too insecure, while others believe that companies are simply not transparent enough about how they use the technology. Lack of knowledge For many, it boils down to a lack of user experience, as not everyone has the need or interest to get invested in this new technology trend. In fact, most companies are still looking to roll out generative AI expertise more widely across their organizations.

The Generative AI Software market is experiencing explosive growth, driven by advancements in deep learning and the increasing availability of large datasets. While precise market sizing figures were not provided, considering the rapid adoption across various sectors and the involvement of major tech players like OpenAI, Google, and Microsoft, a reasonable estimate for the 2025 market size could be in the range of $15 billion. This substantial valuation reflects the diverse applications of generative AI, including text, image, code, and audio generation. The market's Compound Annual Growth Rate (CAGR) is likely to be exceptionally high, potentially exceeding 30% over the forecast period (2025-2033), fueled by continuous technological innovation and expanding use cases. Key drivers include the increasing demand for automation in content creation, software development, and data analysis, as well as the growing need for personalized user experiences. The enterprise segment is anticipated to be a major revenue contributor, as businesses leverage generative AI for enhanced productivity and improved decision-making. However, challenges such as ethical concerns surrounding AI-generated content, data privacy issues, and the high computational costs associated with training and deploying large language models present potential restraints to market growth. Segmentation by application (private vs. enterprise) and by type (text, image, code, audio generators) provides a granular view of the market's composition and evolving dynamics. The geographical distribution is expected to be relatively broad, with North America and Europe holding significant market shares initially, followed by a rapid expansion in the Asia-Pacific region due to burgeoning technological advancements and increasing digital adoption. The competitive landscape is highly dynamic, featuring both established tech giants and innovative startups. Companies like OpenAI, Google (Alphabet), Microsoft, and Adobe are investing heavily in research and development, while smaller players are focusing on niche applications and specialized solutions. Strategic partnerships, mergers, and acquisitions are expected to reshape the market structure over the forecast period. The continued evolution of generative AI models, combined with the decreasing costs of computing power, will further accelerate market growth. Future developments will likely focus on improving the efficiency, accuracy, and ethical considerations of generative AI technologies, opening new avenues for applications across various industries. Overall, the generative AI software market is poised for significant expansion, presenting lucrative opportunities for businesses and investors alike.

The global enterprise generative ai market size is forecast to rise from USD 3.98 billion in 2025 to USD 88.07 billion by 2035, advancing at a CAGR above 36.3%. Companies leading innovation in the industry are OpenAI, Google, Microsoft, Anthropic, IBM, contributing to the sector’s development and expansion.

Weekly active user statistics for ChatGPT from January 2023 to April 2025.

The Artificial Intelligence Automatically Generates Content market is poised for substantial growth, projected to reach an estimated market size of approximately $35,000 million in 2025, with a compound annual growth rate (CAGR) of around 25% anticipated over the forecast period of 2025-2033. This rapid expansion is fueled by the increasing demand for personalized and efficient content creation across a multitude of industries. Key drivers include the burgeoning need for automation in content generation to reduce costs and increase output, the growing sophistication of AI models capable of producing high-quality text, images, audio, and video, and the widespread adoption of AI-powered content creation tools by businesses of all sizes. Furthermore, the evolving digital landscape, with its continuous need for fresh and engaging content for marketing, education, and entertainment, acts as a significant catalyst. The market's segmentation reveals a diverse range of applications, from handling intricate financial reports and medical insurance documentation to crafting compelling retail descriptions, sophisticated word processing, and seamless travel itineraries. Simultaneously, the evolution of AI generation types, encompassing the creation of hyper-realistic images, dynamic videos, immersive audio, and coherent text, underscores the breadth of innovation within this sector. Despite the immense potential, certain restraints could influence the market's trajectory. These include the ethical considerations surrounding AI-generated content, such as issues of plagiarism, authenticity, and the potential for misinformation. The high cost of developing and implementing advanced AI content generation systems, along with the need for skilled professionals to manage and fine-tune these technologies, can also present a barrier for some organizations. Data privacy concerns and regulatory frameworks surrounding AI usage further add complexity. However, the dominant trends, such as the rise of generative AI models like large language models (LLMs) and diffusion models, coupled with the increasing integration of AI content generation into existing workflows and platforms, are expected to outweigh these challenges. Major players like Amazon, OpenAI, Meta, and Google are heavily investing in research and development, fostering an environment of intense competition and rapid technological advancement, particularly within regions like North America and Asia Pacific, which are anticipated to lead in adoption and innovation. This comprehensive report delves into the dynamic and rapidly evolving landscape of Artificial Intelligence (AI) for automated content generation. Spanning the Study Period of 2019-2033, with a Base Year of 2025 and a detailed Forecast Period of 2025-2033, this analysis provides an in-depth examination of market dynamics, technological advancements, and future projections. The report leverages data from the Historical Period of 2019-2024 to establish a robust understanding of past trends and inform future predictions. The market is anticipated to reach values in the millions of dollars, reflecting significant growth and investment.

Creativity is core to being human. Generative AI—made readily available by powerful large language models (LLMs)—holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We study the causal impact of generative AI ideas on the production of short stories in an online experiment where some writers obtained story ideas from an LLM. We find that access to generative AI ideas causes stories to be evaluated as more creative, better written, and more enjoyable, especially among less creative writers. However, generative AI-enabled stories are more similar to each other than stories by humans alone. These results point to an increase in individual creativity at the risk of losing collective novelty. This dynamic resembles a social dilemma: with generative AI, writers are individually better off, but collectively a narrower scope of novel content is produced. Our results have implications for researchers, policy-makers, and practitioners interested in bolstering creativity. Methods This dataset is based on a pre-registered, two-phase experimental online study. In the first phase of our study, we recruited a group of N=293 participants (“writers”) who are asked to write a short, eight sentence story. Participants are randomly assigned to one of three conditions: Human only, Human with 1 GenAI idea, and Human with 5 GenAI ideas. In our Human only baseline condition, writers are assigned the task with no mention of or access to GenAI. In the two GenAI conditions, we provide writers with the option to call upon a GenAI technology (OpenAI’s GPT-4 model) to provide a three-sentence starting idea to inspire their own story writing. In one of the two GenAI conditions (Human with 5 GenAI ideas), writers can choose to receive up to five GenAI ideas, each providing a possibly different inspiration for their story. After completing their story, writers are asked to self-evaluate their story on novelty, usefulness, and several emotional characteristics. In the second phase, the stories composed by the writers are then evaluated by a separate group of N=600 participants (“evaluators”). Evaluators read six randomly selected stories without being informed about writers being randomly assigned to access GenAI in some conditions (or not). All stories are evaluated by multiple evaluators on novelty, usefulness, and several emotional characteristics. After disclosing to evaluators whether GenAI was used during the creative process, we ask evaluators to rate the extent to which ownership and hypothetical profits should be split between the writer and the AI. Finally, we elicit evaluators’ general views on the extent to which they believe that the use of AI in producing creative output is ethical, how story ownership and hypothetical profits should be shared between AI creators and human creators, and how AI should be credited in the involvement of the creative output. The data was collected on the online study platform Prolific. The data was then cleaned, processed and analyzed with Stata. For the Writer Study, of the 500 participants who began the study, 169 exited the study prior to giving consent, 22 were dropped for not giving consent, and 13 dropped out prior to completing the study. Three participants in the Human only condition admitted to using GenAI during their story writing exercise and—as per our pre-registration—they were therefore dropped from the analysis, resulting in a total number of writers and stories of 293. For the Evaluator Study, each evaluator was shown 6 stories (2 stories from each topic). The evaluations associated with the writers who did not complete the writer study and those in the Human only condition who acknowledged using AI to complete the story were dropped. Thus, there are a total of 3,519 evaluations of 293 stories made by 600 evaluators. Four evaluations remained for five evaluators, five evaluations remained for 71, and all six remained for 524 evaluators.

The size of the Generative Artificial Intelligence AI in Healthcare Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of XXX% during the forecast period. Recent developments include: In February 2024, Persistent Systems launched an innovative generative artificial intelligence (AI)--powered population health management (PHM) solution in collaboration with Microsoft., In August 2023, Cognizant expanded its partnership with Google Cloud to develop healthcare large language model (LLM) solutions with the use of Google Cloud’s generative artificial intelligence (AI) technology., In April 2023, Microsoft expanded its collaboration agreement with Epic Systems Corporation to develop and integrate generative artificial intelligence (AI) into healthcare. According to the agreement, Microsoft would use the Azure OpenAI Service with Epic Systems Corporation’s electronic health record (EHR) software to increase productivity, enhance patient care, and improve the financial integrity of health systems globally., In March 2023, NVIDIA Corporation announced its collaboration with Medtronic to accelerate the development of generative artificial intelligence (AI) technology in the healthcare system and to bring new artificial intelligence (AI)-based solutions into patient care., In November 2022, Syntegra announced the launch of Syntegra Medical Mind 2.0 to expand its generative artificial intelligence (AI) technology to generate synthetic healthcare data..

Generative Artificial Intelligence (AI) models such as OpenAI’s ChatGPT have the potential to revolutionize Statistical Process Control (SPC) practice, learning, and research. However, these tools are in the early stages of development and can be easily misused or misunderstood. In this paper, we give an overview of the development of Generative AI. Specifically, we explore ChatGPT’s ability to provide code, explain basic concepts, and create knowledge related to SPC practice, learning, and research. By investigating responses to structured prompts, we highlight the benefits and limitations of the results. Our study indicates that the current version of ChatGPT performs well for structured tasks, such as translating code from one language to another and explaining well-known concepts but struggles with more nuanced tasks, such as explaining less widely known terms and creating code from scratch. We find that using new AI tools may help practitioners, educators, and researchers to be more efficient and productive. However, in their current stages of development, some results are misleading and wrong. Overall, the use of generative AI models in SPC must be properly validated and used in conjunction with other methods to ensure accurate results.

The rivalry between ChatGPT and Google Gemini defines the generative AI landscape. ChatGPT remains the leader in active engagement, while Gemini closes the gap through mass distribution. From corporate reports to web traffic studies, figures speak clearly about adoption, reach, and momentum. Explore what makes each platform stand out, and what...

Introduction

The Global Generative AI in Clinical Trials Market is anticipated to grow from USD 140.5 billion in 2022 to USD 1,135.3 billion by 2032, demonstrating a notable compound annual growth rate of 23.8%. This growth is largely fueled by the integration of generative AI into clinical trials, significantly enhancing research and development. By expediting data generation and processing, this technology shortens the timeline for drug trials, enabling quicker market introduction of new pharmaceuticals. The rapid synthesis and analysis of vast data sets improve the accuracy of trial outcomes and streamline the knowledge transfer process from research to manufacturing.

Generative AI revolutionizes patient engagement and monitoring in clinical trials by automating routine tasks such as data collection and patient interactions. This automation reduces error risk and allows healthcare providers to concentrate on critical decision-making and patient care. Moreover, generative AI creates sophisticated models that simulate human biological processes, aiding the exploratory stages of drug development and reducing real-world trial risks and costs.

The broader adoption of generative AI is driven by its potential to significantly cut development timelines and costs while enhancing the safety and accuracy of clinical research. This technology is becoming indispensable in transforming clinical trials, promising more rapid and precise development of medical treatments. As companies continue to harness these advanced capabilities, the landscape of clinical research is set to evolve dramatically.

Recent strategic developments highlight the industry’s momentum. In April 2024, Microsoft announced a partnership with Cognizant, investing $1 billion to expand generative AI use in enterprise operations, including healthcare. This collaboration leverages Microsoft’s Copilot in Microsoft 365 and GitHub to drive AI innovation. In March 2024, Google launched MedLM, a new healthcare-focused generative AI series for enhancing AI’s capacity to handle diverse healthcare data, thus improving health assessments.

In October 2023, Tencent Holdings Ltd. supported Baichuan, a Chinese AI startup, in a significant funding round that raised $300 million, bringing Baichuan’s valuation to over $1 billion. This investment, also backed by Alibaba Group and Xiaomi Corp., positions Baichuan to compete with major industry players like Microsoft and OpenAI, indicating a robust competitive landscape in the generative AI sector. This surge in investment underscores the growing recognition of generative AI’s transformative impact on various industries, including healthcare.

The AI Speech Model market is experiencing explosive growth, projected to reach an estimated $111 million in 2025, with a remarkable Compound Annual Growth Rate (CAGR) of 20.1% over the forecast period of 2025-2033. This rapid expansion is fueled by an increasing demand for sophisticated voice-enabled applications across both personal and commercial sectors. In the personal sphere, AI speech models are revolutionizing content creation, personal assistants, and accessibility tools, while commercial applications span customer service automation, personalized marketing, and advanced data analysis. The market is segmented into AI Speech Recognition Big Models and AI Speech Generation Big Models, with both categories seeing substantial investment and innovation. Emerging trends include the development of more nuanced and emotionally intelligent AI voices, real-time translation capabilities, and seamless integration with existing enterprise systems. The significant CAGR of 20.1% indicates a highly dynamic market, driven by continuous technological advancements and a widening array of use cases. Key players such as Nvidia, Amazon, Open AI, Microsoft Azure, and Elevenlabs are at the forefront of this innovation, investing heavily in research and development to create more powerful and versatile AI speech models. While the market is robust, potential restraints could include the ethical considerations surrounding AI-generated speech, data privacy concerns, and the need for substantial computational resources for training and deployment of these large models. However, the sheer potential for efficiency gains, enhanced user experiences, and new service offerings is expected to outweigh these challenges, propelling the market to new heights. The Asia Pacific region is anticipated to emerge as a dominant force, driven by significant investments in AI technology and a burgeoning digital economy, followed closely by North America and Europe. This comprehensive report delves into the dynamic landscape of AI Speech Models, exploring their evolution, market concentration, key trends, and future outlook. Spanning a study period from 2019 to 2033, with a base year of 2025 and a forecast period of 2025-2033, this analysis leverages historical data from 2019-2024 to provide actionable insights. The report will be crucial for stakeholders seeking to understand the burgeoning opportunities and challenges within this multi-million dollar industry.

Comparison of Seconds to Output 500 Tokens, including reasoning model 'thinking' time; Lower is better by Model