Generative AI Market Size & Share Forecast 2032 MRFR

The global Yakov Livshits was valued at USD 10.14 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 35.6% from 2023 to 2030. The global generative AI in digital marketing market size was USD 1.5 Billion in 2022 and is projected to reach USD 14.8 Billion by 2031, expanding at a CAGR of 29% during the forecast period, 2023–2031. The market growth is attributed to the rising development & launch of advanced artificial intelligence tools and their surging adoption in digital marketing practices. Advanced features of generative AI including algorithmic support and machine learning (ML) are expected to propel its demand in digital marketing. These AI tools are being highly used in the digital marketing industry for producing innovative content, improving marketing performance by gaining valuable insights, and optimizing advertising campaigns.

The growth trajectory of generative AI solutions encounters a significant hurdle in the form of limited access to high-quality input data. The effectiveness of AI performance is intricately tied to the caliber of data supplied to algorithms. Attempts to train AI models with Yakov Livshits subpar data lead to discrepancies in expected outcomes, some models even failing to achieve optimal results. The presence of deficient, irrelevant, or manipulated datasets poses financial risks, especially if disparities emerge between ground truth and AI predictions.

By Technology

A. Generative AI employs various algorithms, such as GANs and VAEs, to generate content. These algorithms learn patterns from training data before extrapolating those learned patterns to produce new material by extrapolation. Generative AI poses ethical and legal concerns regarding intellectual property rights, data privacy, authenticity, unauthorized copying of copyrighted material and potential bias in generated content that must be resolved by both businesses and regulators. Generative AI algorithms can analyze large datasets, identify patterns, and generate insights that support decision making and problem solving in industries like healthcare, finance, and manufacturing.

As more people embrace virtual reality technology, the trend of virtual worlds is on the rise, offering endless possibilities for entertainment, socialization, and even professional development. The sudden outbreak of the COVID-19 pandemic has led to the growing deployment of generative AI by numerous organizations to create new digital videos, images, texts, audio, or code, during the remote working scenario. Based on component, software segment is expected to hold the maximum share of the generative AI market. The global generative ai market was valued at $10.5 billion in 2022, and is projected to reach $191.8 billion by 2032, growing at a CAGR of 34.1% from 2023 to 2032.

By Model Analysis

Generative AI has the potential to transform businesses by opening new opportunities for automation, innovation, and personalization, all while lowering costs and improving customer experience. For instance, in March 2023, Grammarly, Inc., a U.S.-based AI-based writing assistant, announced the launch of GrammarlyGo, a feature of generative AI enabling users to compose writing, edit, and personalize text. Generated text and images include blog articles, computer code, poetry, and visual art.

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.

Furthermore, the growing demand for assist chatbots in the healthcare industry to provide personalized assistance to patients & improve customer experience is further driving the demand for this technology. Conversational AI has advanced significantly thanks to generative AI, enabling chatbots and virtual assistants to converse with users in a way that feels more natural and contextually aware. Across numerous industries, this human-like contact is improving user experience and customer service. Additionally, it excels in creating realistic images and videos, including faces, objects, and scenes. This skill encourages creativity and visual storytelling and has applications in gaming, design, and the entertainment sector.

Scope of Generative AI Market Report

Generative AI algorithms have showcased remarkable efficacy in the analysis of complex datasets, the identification of patterns, and the generation of valuable predictions. Moreover, over the past few decades, the IT sector has experienced substantial expansion, largely due to the swift integration of AI-based systems across diverse industries, augmenting productivity and agility. In addition, the growing popularity of generative AI in facilitating effective conversations for chatbots and enhancing customer satisfaction is projected to positively contribute to market growth.

These innovations make possible more sophisticated and accurate generative models which extend content creation capabilities across industries. Moreover, various software tools & frameworks offer customization options, allowing businesses to tailor their generative AI models to their specific needs. This makes it possible to create unique & innovative solutions that can give businesses a competitive edge in the market.

Through continuous iterations and improvements, GANs have demonstrated unparalleled success in tasks such as image and video synthesis, natural language generation, and creative content creation. Their ability to produce high-quality outputs with a wide range of applications across industries has made GANs the technology of choice for many companies, leading to their significant market share. On the other hand, the retrieval augmented generation segment is expected to be the fastest-growing segment during the forecast period. This growth can be attributed to the increasing demand for more controllable and contextually relevant content generation. Retrieval augmented generation combines the power of retrieval models and generative models, allowing users to specify desired attributes or content from existing data, which the generative model then incorporates to create tailored outputs. This technology finds applications in personalized content generation, recommendation systems, and interactive AI-driven interfaces.

The COVID-19 pandemic has, however, been a big win for cloud-based software suppliers since most IT employees now manage various business processes from home. Over the course of the forecast period, these factors are anticipated to support the market for generative AI. For consumers, companies, governments, and nonprofit groups, this field is very promising.