Generative AI Market Update 2023: Predicted to Achieve US$ 30 4 Billion Revenue by 2028 CAGR of 20.01%

This new category is called “Generative AI,” meaning the machine is generating something new rather than analyzing something that already exists. The competitive landscape includes key players (tier 1, tier 2, and local) having a presence across the globe. Companies such as Synthesia, Adobe, D-ID, Google LLC, and MOSTLY AI Inc are some of the leading players in the global  Generative AI Industry. These players have adopted partnership, acquisition, expansion, and new product development, among others as their key strategies.

We can think of Generative AI apps as a UI layer and “little brain” that sits on top of the “big brain” that is the large general-purpose models. For developers who had been starved of access to LLMs, the floodgates are now open for exploration and application development. Based on region, the market has been divided into North America, Europe, Asia-Pacific, the Middle East & Africa, and Latin America.

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As tools that use breakthroughs in natural language processing make their way into businesses and society, they could boost the global GDP by 7% (or almost USD 7 trillion) and increase economic growth by 1.5% over ten years. The continuous advancements in deep learning have been a key driver for the growth of the generative AI market. Deep learning algorithms, especially those based on Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have revolutionized the field of generative modeling. GANs have been particularly instrumental in generating realistic and high-quality synthetic data.

DALL-E, a multimodal (text-to-image) foundation model, can be modified to make new images, enlarge old ones, or produce variants of paintings that already exist. In 2020, during the COVID-19 pandemic, the growth of the global generative AI market witnessed significant growth due to rapid digitization across the world. However, in 2021, the initiation of large-scale vaccination drives lifted the lockdown and travel restrictions, and people are more aware of digitization and their business and are adopting generative AI for large and small businesses.

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Based on the Application, the market has been divided into Natural Language Processing, ML-based Predictive Modeling, Computer Vision, Robotics and Automation, and Others. The Natural Language Processing (NLP) segment is expected to hold the largest market share in the Generative AI market due to the growing demand for advanced language-based applications across various industries. NLP-powered Generative AI models have revolutionized how machines understand, interpret, and generate human language, enabling applications such as chatbots, language translation, content generation, sentiment analysis, and voice assistants. The rapid advancements in artificial intelligence, specifically in the field of Generative AI, have been a significant driver for market growth. These advancements have opened up new possibilities for various industries, including entertainment, gaming, healthcare, design, and more, leading to increased demand for Generative AI solutions. LLMs expand content production, language translation, sentiment analysis, and data analysis.

Generative AI is one way of creating synthetic data, which is a class of data that is generated  rather than obtained from direct observations of the real world. This ensures the privacy of the original sources of the data that was used to train the model. For example, healthcare data can be artificially generated for research and analysis without revealing the identity of patients whose medical records were used to ensure privacy. With a strong presence across different verticals and geographies, the Generative AI market is highly competitive and partially dominated by established and pure-play vendors. Over 20 vendors cater to this market, and they continually innovate their solutions to meet the evolving needs of businesses by adopting new technologies to make business more effective. These vendors have a robust geographic footprint and partner ecosystem to cater to diverse customer segments.

Another key component that is included in the report is the regional analysis to assess the global presence of the Generative AI market. You can also opt for a yearly subscription of all the updates on the Generative AI market. These companies have made significant investments in research & development and have created advanced technologies that are capable of producing accurate and effective results. In addition, the region has a well-established academic & research infrastructure, which has produced a large number of skilled professionals with expertise in artificial intelligence and related fields. Above all, Software experienced noteworthy growth in demand during the historical years by making generative AI more accessible & easier to use for businesses & organizations. It offers scalability, efficiency, customization, and user-friendly interference to the consumer, which can result in cloud-based infrastructure & distributed computing.

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.

Therefore, media & entertainment companies are planning to invest in this technology to reduce the developing time of the content, which results in the low operation cost for the companies. Generative AI can empower marketers to automate various aspects Yakov Livshits of content creation, saving time and resources for faster time-to-market. From generating social media posts and blog articles to crafting email campaigns, AI models can produce draft content that human marketers can refine and personalize.

• We could even soon witness a famous actress licence her image to a production company, which then uses a generative AI model to do the actual acting in an advertisement.
• Moreover, countries like China, India, Japan, and South Korea have emerged as key players in AI innovation, with numerous startups and established companies focusing on Generative AI applications.
• Generative AI is a powerful tool that can be used to create new ideas, solve problems, and create new products.
• • Investing in upskilling and reskilling efforts will equip B2B professionals to collaborate effectively with generative AI and shape the future of content creation.
• Asia Pacific is anticipated to grow at the fastest CAGR of 36.5% during the forecast period.

The BFSI segment is projected to grow at a considerable growth rate throughout the projected period, as the industry is witnessing rapid growth in the adoption of big data and machine learning algorithms and high growth in investment in fintech sector. In addition, integration of artificial intelligence in BFSI toolchain across several digital financial services and prevalence of customer relationship management has accelerated the demand for AI in BFSI solutions. Anticipated for 2023, North America is poised to take the lead in the Yakov Livshits, with the US spearheading this trajectory within the region.

Generative AI in Content Marketing

Instances abound wherein these models yield outputs of suboptimal quality, marked by inaccuracies, irrelevance, and questionable outcomes, among other deficiencies. Notably, LLMs such as ChatGPT offer a case in point, exhibiting limitations in addressing recent Yakov Livshits events and delivering answers that are at times ambiguous and repetitive. Similarly, Google’s Bard drew criticism for an advertisement that falsely claimed the James Webb Space Telescope captured the first images of a planet beyond our solar system.

The data present at the disposal of the AI model decides the authenticity and reliability of the produced content. With the whole lot of data used to train the AI models, the content created may be irrelevant, unreliable, and inauthentic if the data is biased or inaccurate. “In my opinion, getting beyond your writer’s block is the greatest benefit of employing generative AI in content marketing.”, says  Jamie Irwin, Digital Marketing Expert at TutorCruncher. While the focus of text-based generative AI tools is to help marketers create the first draft of the content, these tools can also help in editing and proofreading the final draft of a piece of content.

Here at PixelPlex, we understand the significance of generative AI and its boundless potential. Generative AI has been around for decades, but its popularity skyrocketed with the introduction of ChatGPT in 2022. Creators use it to generate content, writers — for idea inspiration, marketing managers for creating copies, conducting market research, and devising new strategies. There are also surprising applications, such as creating travel plans based on your budget or simply engaging in conversation, almost like having a free therapy session. North America’s strong emphasis on innovation and digital transformation has created a fertile ground for the adoption of generative AI technologies.

For instance, the total number of digital fraud attempts rose by over 25% in the United States in the first four months of 2021 from the same period in 2020. Digital fraud against financial services companies increased by about 109% in the United States in the same period. The transformative potential of Generative AI technology is clear for individuals, businesses, and society as a whole. Its swift advancement can democratise various industries and revolutionise content creation and creative processes. However, businesses must exercise caution and prioritise human leadership when integrating Generative AI into their operations. Addressing the societal, economic, and environmental impacts of Generative AI necessitates investments in staff training, the development of ethical frameworks, and the implementation of regulations.

Moreover, generative AI techniques for image generation have made significant advancements in recent years. These techniques have become more sophisticated and capable of generating high-quality, realistic, and diverse images. AI-powered tools also assist in software development, handling tasks such as composing user stories, editing and reviewing code, identifying bugs, and testing software. These tools contribute to more efficient workflows, heightened productivity, and expedited time-to-market. Some applications of Generative AI encompass text-to-code generation, code auto-completion, and code summarisation or explanation.