Rising applications of technologies value the global generative AI market at $8 billion in 2021. The growing demand to modernize workflow across industries also drives this market. It is projected to grow at a CAGR of 34.6% from 2022 to 2030.
The COVID-19 pandemic has had a positive impact on the generative AI market. Businesses shifted to online work and increased digital transformation. As a result, 53% of IT professionals seeded up the roll-out of AI in response to the pandemic.
Generative AI utilizes unsupervised learning algorithms for tasks such as spam detection and image compression. It also applies for preprocessing data like removing noise from visual data to improve picture quality. It also uses supervised learning algorithms for medical imaging and image categorizing. Generative AI has potential applications in various industries such as BFSI, healthcare, automotive & transportation, IT & communication system, media & entertainment, and others.
However, the market is at a developing stage which requires a skilled workforce and high investment in implementation for development. This may slow down the pace of development.
The global generative AI market is segmented into media & entertainment, BFSI, IT & communication system, healthcare, automotive & transportation, and others, with the media & entertainment segment accounting for the largest revenue in 2021 and expected to grow at a CAGR of 33.5%.
The BFSI segment is expected to witness the fastest growth rate of 36.4% during the forecast period, due to the increasing implementation of AI & ML in the sector to prevent fraudulent activities, secure data and meet the dynamic needs of various stakeholders in financial services.
The generative AI market is competitive with many global and regional players investing in R&D to gain a competitive edge. They are also entering into partnerships and M&A as the market is rapidly changing. IBM acquired SXiQ, a digital transformation company, in November 2021 to improve its AI strategy and hybrid cloud capabilities. Deepbrain AI, Synthesia, Mostly AI Inc, Genie AI Ltd, Amazon Web Services, IBM, Google LLC, Microsoft, Adobe, Rephrase.ai, and D-ID are key players in the generative AI market.
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The generative AI market is highly competitive and is expected to reach $38.8 billion by 2026, growing at a CAGR of 36.2% during the forecast period. Many global and regional players are vying for a share of the market. Among these players, DeepBrain AI stands out as a leader in the field, providing a broad range of AI-based products and services, from chip design to cloud services.
With a strong presence across multiple sectors, companies are taking advantage of the growth opportunities in the market. These sectors include text, audio, image, chatbot, and video. Their expertise in these areas gives them a competitive advantage over other players in the market. Additionally, their ability to stay on top of industry trends also gives them an edge. For instance, companies that are investing in natural language processing (NLP) and computer vision (CV) are expected to have a competitive advantage in the market.
As a result, companies are actively taking advantage of the growth opportunities in the generative AI market. They continue to drive its growth by capitalizing on these opportunities. The increasing adoption of AI in various industries, such as healthcare, retail, and finance, is driving the growth of the generative AI market. Furthermore, the increasing demand for personalization and automation is also expected to drive the market growth.
Generative AI is a powerful tool that people use for a wide range of tasks beyond traditional natural language processing. OpenAI released ChatGPT, which people already use for a variety of applications including search engine optimization, creating personalized therapy bots, and explaining complex algorithms.
Text-to-image programs such as DALL-E and Stable Diffusion are transforming the way art, animation, and other industries are being created. Generative AI aids in the creative process for artists and designers and also has transformative capabilities in complex sciences such as computer engineering.
n conclusion, generative AI models have the potential to revolutionize creativity and workflows. However, it is crucial that society is aware of the potential downsides and actively works to mitigate them. This includes addressing issues of job displacement, biased and false content generation, and ensuring responsible use and governance of these powerful tools. It is important for society to strike a balance between the benefits and risks associated with generative AI, to ensure that the technology is used for the betterment of society.
A generative AI model created by OpenAI, has the ability to generate new scientific knowledge, but it also generated content that was racist, inaccurate, and nonsensical, causing the company to take the platform offline. This highlights the need for trust and oversight when using this models, as they are not capable of truly creating something new and can present incorrect information.
The public and private sectors are currently grappling with how to govern and regulate generative AI models, with some companies self-governing through limited release strategies and controlled access, while others believe in open sourcing to democratize access. The lack of regulation in the space has led to concerns about intellectual property and copyright infringement, as well as the potential for the generation of harmful content.
