The Global Generative Artificial Intelligence (AI) market is anticipated to grow at a significant CAGR of 48.5% during the forecast period (2022-2030). Generative AI is used extensively across modalities including, text (in content writing, chatbots and assistants, search, analysis, and synthesis), code (in code generation, application and prototype and design, and data set generation), image (in stock image generator and image editor), audio (text to voice generation, sound creation and audio editing), 3-D object generation and product design and discovery, video (in creation, editing, translations and adjustments, and face swaps and adjustments) and other.
Browse the full report description of “Generative AI Market Size, Share & Trends Analysis Report Market by Offering (Software and Services), by Application (Text, Image, Video, and Others (Audio)), Business Function (Marketing and Sales, Finance, Human Resource, Research and Development, and Others (Customer service and Education)), Vertical (BFSI, IT and Telecommunication, Healthcare, Media and Entertainment, Retail and E-Commerce, Manufacturing, Construction and Real Estate, and Others)) Forecast Period (2022-2030)” at https://www.omrglobal.com/industry-reports/generative-ai-market
Generative AI Market: A Synopsis
- The generative AI technologies are being trained to render human-level performance in coordination with multiple agents, creativity, logical reasoning, and problem-solving, natural- language generation, natural-language understanding, output articulation, and presentation, generating novel patterns and categories, sensory perception, social and emotional output, social and emotional reasoning and social and emotional sensing. For most of these technical capabilities, gen AI will perform at a median level of human performance by the end of this decade.
- The developments in technical capabilities are majorly bringing automation to the knowledge industry including educators, professionals, law, and creatives. This has a huge impact on decision-making and collaboration. The other fields to be a part of the change would be community services, office support, managers, health professionals, customer service and sales, property maintenance, health aides, technicians and wellness, production work, food services, transportation services, mechanical installation and repair, agriculture, builders and others.
- The impact of generative AI would depend on a variety of factors such as business function mix the significance of each function and the scale and revenue of the industry. However, the deployment of the technology for marketing and sales would optimize processes across all industries, with the highest impact on high-tech and banking sectors, attributed to the development of competent software. The other industries would include pharmaceutical and medical products, education, telecommunication, healthcare, insurance, media and entertainment, advanced manufacturing, consumer packaged goods, advanced electronics and semiconductors, and others.
- The use cases of Generative AI with the highest potential would be evident in banking, life sciences, and retail and consumer-packaged-goods industries.
- The generative AI technologies are used in various branches of marketing and sales such as lead identification, marketing optimization, personalized outreach, dynamic content creation, up-selling and cross-selling, success analytics, marketing analytics, dynamic customer-journey mapping, automated marketed workflows, sales analytics, and sales coaching.
The major players of the market include Amazon Web Services, Inc., Microsoft, Corp., Google LLC., and IBM Corp., among others. One of the challenges associated with the industry growth is that although the commercial leaders are already leveraging generative AI, however, the technology is still underutilized. This not adoption can largely be attributed to inaccuracy, cybersecurity, and intellectual-property infringement concerns. However, it should be noted that the efficient adoption of the technology is potent to boost labor productivity, contributing significantly towards the business revenue and GDP of the economy.
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