市場調查報告書
商品編碼
1184244
生成式 AI 全球市場規模/份額/行業趨勢分析報告:展望/按組件、技術、最終用途、地區預測,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 |
在預測期內,全球生成式人工智能市場規模預計將以 32.2% 的複合年增長率增長,到 2028 年達到 539 億美元。
這可以通過一種稱為生成設計的技術來完成,您可以在其中設置指導方針和限制,開始工作,並給自己一些時間。 通過查看生成的圖紙,個人可以找到問題的解決方案並學習新的觀點。 生成式 AI 正在為人們開闢新的工作、娛樂和創造方式。
對於消費者、企業、政府和非營利組織而言,該領域前景廣闊。 機器使用錄音、文本和圖形等元素創建內容的程序被稱為生成 AI(人工智能)。 據麻省理工學院稱,過去十年人工智能領域最激動人心的發展之一是生成式人工智能。
COVID-19 影響分析
2020 年 COVID-19 的影響影響了許多地方的商業活動和經濟。 為阻止疾病傳播而關閉的商業活動導致企業(尤其是小型企業)的 IT 投資減少。 然而,COVID-19 大流行對基於雲的軟件供應商來說是一個福音。 這是因為大多數 IT 員工現在在家管理各種業務流程。 預計這些因素將在預測期內支持生成人工智能市場。
市場增長因素
服務商之間的欺詐檢測
利用合成數據有可能解決銀行業當前的問題,尤其是數據保護方面的問題。 合成數據可用於創建可共享數據,以代替因隱私問題而無法共享的客戶數據。 人工消費者數據也是訓練機器學習 (ML) 模型的理想選擇,可幫助銀行評估他們是否以及如何向客戶提供信貸和抵押貸款。
風險管理
為了讓銀行保持足夠的風險敞口、識別潛在風險領域並採取措施保持盈利能力,它需要製定風險管理計劃。 如果銀行的流動性、信貸、運營和其他風險沒有得到妥善管理,它們可能會蒙受損失。 由於這些優勢,生成式人工智能現在得到廣泛應用,尤其是在 BFSI 行業。
市場約束
人工智能生成內容的倫理
人們經常成為 AI 生成的宣傳、淫穢內容和欺詐視頻的目標。 這引發了隱私和同意的問題。 此外,如果 AI 可以像人一樣製作內容,無論是否徵得該人的同意,個人失業的可能性都會變得真實。 由於生成人工智能的這些局限性,公司可能會猶豫是否使用它並阻礙市場擴張。
組件視角
基於組件,生成 AI 市場分為軟件和服務。 2021 年收入份額最大的軟件部分將推動生成人工智能市場。 該軟件利用先進的機器學習算法,根據先前的單詞序列預測下一個單詞,並根據描述先前圖像的單詞預測下一張圖像。 軟件市場的擴張可能受到各種變量的驅動,包括欺詐增加、技能被高估、意想不到的後果以及對數據隱私的日益關注。
技術展望
生成式 AI 市場根據技術細分為生成式對抗網絡 (GAN)、變換器、變分自動編碼器和擴散網絡。 生成 AI 市場的擴散網絡部分在 2021 年實現了顯著的收入增長。 成像對圖像合成的需求不斷增長,因為它可以為 BFSI、醫療保健、汽車和運輸、媒體和娛樂以及國防等許多行業的企業、政府和公眾提供高價值。它變得極其重要跟上上漲趨勢。
結束使用 Outlook
根據最終用途,生成式 AI 市場分為媒體和娛樂、BFSI、IT 和通信、醫療保健、汽車和運輸等。 2021 年,生成式人工智能市場將在醫療保健領域實現可喜的增長。 當被 3D 打印和 CRISPR 等技術激活時,生成人工智能可以憑空創造有機分子、假肢等。 此外,潛在惡性腫□□瘤的早期檢測允許更好的治療策略。 為了找到治愈 COVID-19 的方法,IBM 目前正在使用這項技術研究抗菌□ (AMP)。
區域展望
按地區劃分,生成式 AI 市場分為北美、歐洲、亞太地區和 LAMEA。 北美地區將產生最大的收入份額,從而在 2021 年主導全球生成人工智能市場。 這是由於醫療保健和偽圖像的興起以及銀行欺詐的興起等因素造成的。 此外,美國的 Microsoft、Meta 和 Google LLC 等主要市場進入者以及先進的技術公司和專家的存在預計將推動區域生成 AI 市場的發展。
市場進入者採取的主要策略是“收購”。 根據基數矩陣中的分析,Google LLC 和 Microsoft Corporation 是生成式 AI 市場的先驅。 Amazon.com, Inc.、Adobe, Inc. 和 IBM Corporation 等公司是生成人工智能市場的主要創新者。
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