Generative AI Market Growing at CAGR of 31 4%

AI technologies for video production, like picture generation, may make videos from zero and be used for video alteration, such as improving video resolution and completeness. Because of its ability to generate code without manual coding, generative AI can be used in software development. These methods reduce developers’ time and effort in developing, testing, and repairing code by automating the software creation process.

As a result, generative algorithms can now generate data using models to generate increasingly realistic images, videos, and sounds. In addition, generative AI is being tested in manufacturing as a tool for fast prototyping and in business to enhance data enhancement for robotics process automation (RPA). These models have been used to create synthetic images for various purposes, including art, design, and entertainment.

Product & Services

By Region, the study provides market insights into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. In terms of revenue, North America held the largest share of 42.10% in the Generative AIs market in 2022 and is expected to continue its dominance throughout the forecast period. The rapid expansion of digital platforms especially during pandemic has facilitated the deployment of generative AI applications in numerous fields including drug discovery, contact tracing, remote healthcare misinformation detection and epidemiological modelling. The Generative AI Market industry report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies. There is a significant consumer demand for high-quality and visually appealing images, which has driven the adoption of generative AI techniques for image generation.

Moreover, the BFSI segment is expected to witness considerable growth during the projected period because of a surge in adoption of big data and machine learning algorithms and high growth in investment in the fintech sector. The speed, effectiveness, inventiveness, and correctness of development have all enhanced as generative AI has been more fully integrated into tools and workflows. As this technology continues to be integrated and entrenched within software tools and workflows that developers use daily, it has essentially become routine to developers and their processes throughout the Software Development Life Cycle (SDLC). For instance, developers presently use IntelliCode, an AI-powered program that suggests auto-completions during coding based on project analysis. One of the most promising opportunities for the generative AI market lies in its integration into industry-specific applications. Different sectors can leverage the creative capabilities and personalization aspects of generative AI to solve unique challenges and create tailored solutions.

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This advantage, combined with their effectiveness across diverse NLP tasks like language modeling, text classification, question answering, and machine translation, led to the development of large-scale pre-trained language models like GPT and BERT. The ability to generate high-quality data and content with ease is expected to drive the transformer segment during the forecast period. One of the main advantages of the transformer segment in the global AI market is that they offer a powerful and flexible solution for ML tasks that require the processing of complex Yakov Livshits and large volumes of data. The transformer segment can generate more accurate and realistic outputs as they are better able to handle the natural language input and output. Hence, due to other applications and the growing need to generate accurate data across enterprises, it is expected to drive the growth of this segment which, in turn, will drive the global generative AI market growth during the forecast period. Furthermore, market players are adopting various strategies for enhancing their services in the market and improving customer satisfaction.

Besides this, the emerging popularity of generative AI for assisting chatbots in conducting effective conversations and enhancing customer satisfaction is also contributing to market growth. Generative AI can create personalized recommendations, tailored advertisements, and customized products based on individual preferences and behavior. Moreover, the rising utilization of generative AI for creating virtual worlds in the metaverse and producing digital artworks using text-based descriptions and generating unique and innovative content is also propelling the market growth. Furthermore, the market has attracted significant investments and funding from both established companies and venture capitalists. This influx of capital has accelerated research, development, and commercialization efforts, further creating a favorable market outlook across the globe.

The regional market expansion can also be attributed to businesses’ rapid digitization, which strains cloud networks and data centers. Additionally, AI adoption aids organizations in empowering civil society members to be responsible and knowledgeable AI device users. The rising need for generative AI solutions in several sectors and the development of new and creative generative AI technologies will drive market expansion. The rising deployment in the healthcare, media, and entertainment industries is driving market development in North America. Generative AI is a new type of AI that learns from data and creates new data based on what it learns.

By Industry vs Application Analysis

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

OpenAl’s journey continued with DALL-E’s introduction in 2021 and a ChatGPT preview in 2022, focusing on conversational AI. The release of DALL-E 2 in 2022 further revolutionized image generation with quadruple the resolution. OpenAl’s prowess lies in driving AI evolution, revolutionizing language and image processing.

A constrained set of parameters are provided to generative AI software to use during the training phase. Based on component, services category is predicted to show the fastest growth over the forecast period owing to the growing concerns over data security, trade forecasting, modeling risk factors, and fraud detection. Further, the software segment held the major market share during the foreseen period due to an increase in research & development activities.

It brings together some of the top generative AI and Large Language Model (LLM) researchers in Europe and provides access to data sources, robust computing resources, and infrastructure for building, running, and using LLMs. Growth could expand at a CAGR of 42%, driven by training infrastructure in the near-term and gradually shifting to inference devices for large language models (LLMs), digital ads, specialised software and services in the medium to long term, BI’s research finds. Based on Components, the Generative AI Market segmentation includes software and solution. The software segment held the majority share in 2022, contributing around ~65.3% to the market revenue. As the name suggests, software emerged as the dominant segment in the market, with the highest revenue share in 2022. The growing use of generative AI-based software, which provides benefits such as improved image resolution, reduced conversion time, improved performance, and quick output availability, is related to the segment’s rise.

• In healthcare, generative AI can be utilized to generate synthetic medical images, enabling data augmentation for training machine learning models without compromising patient privacy.
• The rising number of fraudulent activities, increased adoption of digitally advanced healthcare devices, and presence of technologically advanced players such as Google, Meta, Microsoft, and IBM among others.
• OpenAI’s AI chatbot ChatGPT was launched to the public in November and exploded in popularity because of its ability to hold intelligent conversations, compose music, code, and even write essays.

Bard is a chatbot built using a broad language model, similar to OpenAI’s ChatGPT and Microsoft’s Bing chatbot. Bard is a Large Language Model (LLM) that can produce many types of creative content, translate languages, and provide meaningful answers to inquiries. The versatility and potential of generative AI across different sectors have driven its adoption and contributed to market growth. It is used to create realistic computer-generated graphics and special effects in movies and video games. Moreover, generative AI has transformed advertising and marketing strategies by enabling personalized and customized content creation, allowing businesses to tailor their messaging and offers to individual consumers. Besides, it is used in the healthcare sector for tasks such as medical image analysis, drug discovery, disease diagnosis, and treatment planning.

In a similar context, Google’s highly anticipated AI chatbot tool, Bard, has faced pre-release scrutiny due to an erroneous response during a demonstration. This incident underscores the challenge of securing top-tier training data as enterprises race to incorporate AI technology akin to Microsoft-backed ChatGPT into their offerings. This is attributable to the existence of leading companies researching & developing generative AI applications. The global generative AI market size was estimated at USD 10.14 billion in 2022 and is expected to reach USD 13.00 billion in 2023. Problems often arise when companies outsource AI generation projects, and many freelancers work with data from several locations. Data security company Trust Wave estimates that nearly 63% of data thefts are due to a lack of due diligence, while third parties outsource data.

The region has a significant population of tech-savvy individuals, high internet penetration rates, and advanced AI technologies, resulting in the widespread usage of generative AI solutions. Detecting Fraud Among Drivers are driving the market in coming years, however, Ethics Of Ai-Generated Content restraints the growth of the market. For banks to maintain an appropriate amount of risk exposure, identify potential risk areas, and take action to sustain profitability, a risk management plan must be established.

The Natural Language Processing (NLP) segment owns the largest market share and is anticipated to grow significantly during the forecast period. NLP tasks include translation, text generation, summarization, dialogue systems, and sentiment analysis. Generative models permit the generation of text that is coherent and contextually pertinent. The software category will likely generate the most revenue over the projection period.Fraud, overestimation, unanticipated consequences, and data privacy concerns drive software segment growth.