市场调查报告书
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生成式 AI 全球市场规模/份额/行业趋势分析报告:展望/按组件、技术、最终用途、地区预测,2022-2028 年Global Generative AI Market Size, Share & Industry Trends Analysis Report By Component, By Technology, By End Use, By Regional Outlook and Forecast, 2022 - 2028 |
在预测期内,全球生成式人工智能市场规模预计将以 32.2% 的复合年增长率增长,到 2028 年达到 539 亿美元。
这可以通过一种称为生成设计的技术来完成,您可以在其中设置指导方针和限制,开始工作,并给自己一些时间。 通过查看生成的图纸,个人可以找到问题的解决方案并学习新的观点。 生成式 AI 正在为人们开闢新的工作、娱乐和创造方式。
对于消费者、企业、政府和非营利组织而言,该领域前景广阔。 机器使用录音、文本和图形等元素创建内容的程序被称为生成 AI(人工智能)。 据麻省理工学院称,过去十年人工智能领域最激动人心的发展之一是生成式人工智能。
COVID-19 影响分析
2020 年 COVID-19 的影响影响了许多地方的商业活动和经济。 为阻止疾病传播而关闭的商业活动导致企业(尤其是小型企业)的 IT 投资减少。 然而,COVID-19 大流行对基于云的软件供应商来说是一个福音。 这是因为大多数 IT 员工现在在家管理各种业务流程。 预计这些因素将在预测期内支持生成人工智能市场。
市场增长因素
服务商之间的欺诈检测
利用合成数据有可能解决银行业当前的问题,尤其是数据保护方面的问题。 合成数据可用于创建可共享数据,以代替因隐私问题而无法共享的客户数据。 人工消费者数据也是训练机器学习 (ML) 模型的理想选择,可帮助银行评估他们是否以及如何向客户提供信贷和抵押贷款。
风险管理
为了让银行保持足够的风险敞口、识别潜在风险领域并采取措施保持盈利能力,它需要製定风险管理计划。 如果银行的流动性、信贷、运营和其他风险没有得到妥善管理,它们可能会蒙受损失。 由于这些优势,生成式人工智能现在得到广泛应用,尤其是在 BFSI 行业。
市场约束
人工智能生成内容的伦理
人们经常成为 AI 生成的宣传、淫秽内容和欺诈视频的目标。 这引发了隐私和同意的问题。 此外,如果 AI 可以像人一样製作内容,无论是否征得该人的同意,个人失业的可能性都会变得真实。 由于生成人工智能的这些局限性,公司可能会犹豫是否使用它并阻碍市场扩张。
组件视角
基于组件,生成 AI 市场分为软件和服务。 2021 年收入份额最大的软件部分将推动生成人工智能市场。 该软件利用先进的机器学习算法,根据先前的单词序列预测下一个单词,并根据描述先前图像的单词预测下一张图像。 软件市场的扩张可能受到各种变量的驱动,包括欺诈增加、技能被高估、意想不到的后果以及对数据隐私的日益关注。
技术展望
生成式 AI 市场根据技术细分为生成式对抗网络 (GAN)、变换器、变分自动编码器和扩散网络。 生成 AI 市场的扩散网络部分在 2021 年实现了显着的收入增长。 成像对图像合成的需求不断增长,因为它可以为 BFSI、医疗保健、汽车和运输、媒体和娱乐以及国防等许多行业的企业、政府和公众提供高价值。它变得极其重要跟上上涨趋势。
结束使用 Outlook
根据最终用途,生成式 AI 市场分为媒体和娱乐、BFSI、IT 和通信、医疗保健、汽车和运输等。 2021 年,生成式人工智能市场将在医疗保健领域实现可喜的增长。 当被 3D 打印和 CRISPR 等技术激活时,生成人工智能可以凭空创造有机分子、假肢等。 此外,潜在恶性肿□□瘤的早期检测允许更好的治疗策略。 为了找到治愈 COVID-19 的方法,IBM 目前正在使用这项技术研究抗菌□ (AMP)。
区域展望
按地区划分,生成式 AI 市场分为北美、欧洲、亚太地区和 LAMEA。 北美地区将产生最大的收入份额,从而在 2021 年主导全球生成人工智能市场。 这是由于医疗保健和伪图像的兴起以及银行欺诈的兴起等因素造成的。 此外,美国的 Microsoft、Meta 和 Google LLC 等主要市场进入者以及先进的技术公司和专家的存在预计将推动区域生成 AI 市场的发展。
市场进入者采取的主要策略是“收购”。 根据基数矩阵中的分析,Google LLC 和 Microsoft Corporation 是生成式 AI 市场的先驱。 Amazon.com, Inc.、Adobe, Inc. 和 IBM Corporation 等公司是生成人工智能市场的主要创新者。
The Global Generative AI Market size is expected to reach $53.9 billion by 2028, rising at a market growth of 32.2% CAGR during the forecast period.
The term "generative AI" refers to a new branch of machine learning that builds new things using neural networks, which are models based on the organization of animal brains. Traditional machine learning algorithms can only interpret the data that was provided to them by their human designers; they are not capable of producing new data on their own.
In contrast to conventional machine learning, generative AI may produce creative material, such as songs, artwork, and even complete words. People will be able to be more inventive, creative, and innovative owing to generative AI. It has the capacity to break down the boundaries of human imagination and produce new concepts that were previously unimaginable.
This can be done using a technique called generative design, where one commences with a set of guidelines or restrictions and then give it some time to work. The drawings it generates can then be viewed to help individuals either come up with a solution to the problem or learn fresh perspectives on it. New avenues for how people work, play, and create are emerging thanks to generative AI.
For consumers, companies, governments, and nonprofit groups, this field is very promising. Programs that enable machines to create content using elements like audio recordings, text, and graphics are known as generative artificial intelligence (AI). One of the most exciting developments in the field of AI over the past ten years, according to MIT, is generative AI.
COVID-19 Impact Analysis
The commercial operations and economies of numerous locations were impacted by the COVID-19 outbreak in 2020. Lower IT investment by firms, particularly small businesses, was noted as a result of the closure of commercial activities to stop the disease's spread. 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.
Market Growth Factors
Detecting Fraud Among Drivers
The use of synthetic data has the potential to solve the problems the banking sector is now experiencing, particularly with regard to data protection. In place of client data that cannot be shared owing to privacy issues, shareable data can be created using synthetic data. Additionally, artificial consumer data are perfect for training machine learning (ML) models that help banks assess whether and how much they can offer a client in the way of credit or a mortgage loan.
Management Of Risk
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. Whenever liquidity, credit, operational, and other risks really aren't properly managed, banks could experience losses. Because of this advantage, generative AI is widely used nowadays, particularly in the BFSI industry.
Market Restraining Factors
Ethics Of Ai-Generated Content
People are frequently the target of propaganda, obscene content, and fraudulent videos produced by AI. Privacy and consent issues are brought up by this. Additionally, there is a real chance that once AI can produce content in a person's manner, with or without that person's consent, individuals will lose their jobs. Due to these generative AI limitations, businesses may be hesitant to use them, which would hinder the market's expansion.
Component Outlook
Based on the component, the generative AI market is classified into software and services. With the largest revenue share in 2021, the software sector led the generative AI market. In order to anticipate the following word from past word sequences or the following image from words describing prior images, the software makes use of sophisticated machine learning algorithms. The expansion of the software market can be ascribed to a number of variables, including an increase in fraud, an overestimation of skills, unexpected results, and increased data privacy concerns.
Technology Outlook
Based on the technology, the generative AI market is categorized into generative adversarial networks (GANs), transformers, variational auto-encoders, and diffusion networks. The generative AI market's diffusion network segment grew significantly in revenue in 2021. Image generation has become crucial for many industries, including BFSI, healthcare, automotive & transportation, media & entertainment, defense, and many others, in order to meet the growing demands of image synthesis because these sectors are equipped to offer high-value to enterprises, the government, and the general public.
End-use Outlook
On the basis of End-use, generative AI market is categorized into Media & entertainment, BFSI, IT & communications, healthcare, automotive & transportation, and others. The market for generative AI has experienced a promising growth rate in the healthcare sector in 2021. When activated by 3D printing, CRISPR, and other technologies, generative AI can be used to create organic molecules, prosthetic limbs, and other things from nothing. Additionally, early detection of possible malignancy can lead to better treatment strategies. In order to find treatments for COVID-19, IBM is now using this technology to study antimicrobial peptides (AMP).
Regional Outlook
Based on geography, the generative AI market is classified as North America, Europe, Asia Pacific, and LAMEA. The North American region generated the largest revenue share, thereby dominating the generative AI market in 2021 globally. This is because of things like rising medical care and pseudo-imagination, as well as rising banking frauds. The regional generative AI market is also projected to increase due to the existence of key market participants, including the U.S.-based Microsoft, Meta, and Google LLC, as well as sophisticated technology companies and the availability of specialists.
The major strategies followed by the market participants are Acquisition. Based on the Analysis presented in the Cardinal matrix; Google LLC and Microsoft Corporation are the forerunners in the Generative AI Market. Companies such as Amazon.com, Inc., Adobe, Inc., and IBM Corporation are some of the key innovators in Generative AI Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Google LLC, Amazon Web Services, Inc. (Amazon.com, Inc.), IBM Corporation, Microsoft Corporation, Adobe, Inc, MOSTLY AI Solutions MP GmbH, Synthesia Limited, Genie AI, Inc, Rephrase.ai, and De-Identification Ltd.
Strategies Deployed in Generative AI Market
Nov-2022: Microsoft came into collaboration with NVIDIA, an American multinational technology company. This collaboration would aim to create one of the most powerful AI supercomputers, powered by Microsoft Azure's advance. Moreover, this collaboration opens the door to a supercomputer platform that benefits every enterprise on the Microsoft Azure platform.
Oct-2022: Adobe is introducing Generative AI, an AI-based technology. The product features Photoshop, Adobe Express, and Lightroom. Additionally, the latest technology would enable creators to give their idea to Artificial Intelligence and the machine would process certain images.
Oct-2022: Google completed the acquisition of Alter, an artificial intelligence (AI) avatar startup engaged in helping brands and creators express themselves. Through this acquisition, Google would improve both the quality and quantity of the content provided to consumers.
Jun-2022: Google added new features to its previously launched product Vertex. The addition of new features in Vertex AI would boost the deployment of machine learning models in organizations and democratize AI so more people can distribute models in production, driving business impact and continuous monitoring with AI.
Jun-2022: Amazon released CodeWhisperer, an AI pair programming tool that is capable of performing the entire function set only by pressing certain keynotes or based on the comment. The launched product works on Python, Java, and JavaScript as well as on numerous publicly available open-source codes and documents and its database of codes.
Dec-2021: Amazon Web Services, Inc. collaborated with Meta, an American multinational technology conglomerate to provide cloud services to AWS. Under this collaboration, both companies would work together to enhance the functioning of customers running PyTorch on AWS and boost how developers create, train, deploy and operate machine learning/artificial intelligence models.
Apr-2021: IBM took over Turbonomic, a company engaged in offering tools to manage application performance. With this move, IBM would enhance its footprint by offering enterprises AI-based services to manage their workloads and networks.
Apr-2021: Microsoft completed the acquisition of Nuance, an American multinational computer software technology corporation. This acquisition would integrate specializations and expertise to provide new AI and cloud abilities across healthcare and other areas.
Mar-2021: IBM launched Molecule Generation Experience (MolGX), a cloud-based AI-driven molecular design platform that itself invents new molecular structures. This newly launched product boosts the discovery of new materials by 10 to 100 times as well as finds materials from the property targets of a given product.
May-2020: Mircosoft took over Softomotive, a leading provider of robotic process automation. Under this acquisition, Microsoft would combine Softomotive's desktop automation with the present Microsoft Power Automate abilities, at a uniquely low cost. Additionally, Microsoft would balance RPA and allow everyone to build bots to automate manual business processes.
Sep-2018: Microsoft took over Lobe, a start-up that makes it easier to build an A.I. model with its drag-and-drop interface. With this acquisition, Microsoft would create its own effort to design AI models easier as well for some time Lobe would operate as before.
Jul-2018: IBM Watson Health, a division of IBM Corporation, partnered with Guerbet, a manufacturer of contrast agents used in medical imaging. Through this partnership, the companies would use AI for the medical imagining of the liver. Additionally, both companies together would develop advanced clinical decision support solutions.
Market Segments covered in the Report:
By Component
By Technology
By End-Use
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures