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市場調査レポート
商品コード
1184244
ジェネレーティブAIの世界市場規模・シェア・産業動向分析レポート:コンポーネント別、技術別、エンドユース別、地域別展望・予測、2022年~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 |
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ジェネレーティブAIの世界市場規模・シェア・産業動向分析レポート:コンポーネント別、技術別、エンドユース別、地域別展望・予測、2022年~2028年 |
出版日: 2022年12月30日
発行: KBV Research
ページ情報: 英文 232 Pages
納期: 即納可能
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世界のジェネレーティブAI市場規模は、予測期間中にCAGR32.2%で成長し、2028年には539億米ドルに達すると予想されています。
これはジェネレーティブデザインと呼ばれる手法で行うことができ、ガイドラインや制限を設定して作業を開始し、しばらく時間を置きます。生成された図面を見ることで、個人が問題に対する解決策を見出したり、新たな視点を学んだりすることができるのです。ジェネレーティブAIによって、人々の働き方、遊び方、作り方に新しい道が開かれつつあります。
消費者、企業、政府、非営利団体にとって、この分野は非常に有望です。録音、テキスト、グラフィックなどの要素を用いて機械がコンテンツを作成するプログラムは、ジェネレーティブAI(人工知能)として知られています。MITによると、過去10年間のAI分野における最もエキサイティングな開発の1つがジェネレイティブAIです。
COVID-19影響度分析
2020年に発生したCOVID-19の影響で、多数の場所の商業活動や経済が影響を受けた。病気の蔓延を食い止めるために商業活動を閉鎖した結果、企業、特に中小企業によるIT投資の低下が指摘されました。しかし、COVID-19の大流行は、クラウドベースのソフトウェアサプライヤーにとっては大きな収穫となっています。なぜなら、ほとんどのIT従業員が自宅でさまざまなビジネスプロセスを管理するようになったからです。予測期間中、これらの要因がジェネレーティブAIの市場を支えることになると予想されます。
市場の成長要因
促進要因の中の不正の検出
合成データの活用は、銀行業界が現在抱えている問題、特にデータ保護に関する問題を解決する可能性を秘めています。プライバシーの問題で共有できない顧客データの代わりに、合成データを用いて共有可能なデータを作成することができます。また、人工的な消費者データは、機械学習(ML)モデルの学習に最適で、銀行が顧客に与信や住宅ローンを提供できるかどうか、どの程度提供できるかを評価するのに役立ちます。
リスク管理
銀行が適切なリスクエクスポージャーを維持し、潜在的なリスク領域を特定し、収益性を維持するために行動を起こすには、リスク管理計画を策定する必要があります。流動性リスク、信用リスク、オペレーショナルリスク、その他のリスクが適切に管理されていない場合、銀行は損失を被る可能性があります。このような利点があるため、現在、特にBFSI業界では生成型AIが広く利用されています。
市場の抑制要因
AIが生成するコンテンツの倫理性
AIが制作したプロパガンダ、わいせつコンテンツ、詐欺動画などのターゲットに人々がなることが多いです。これにより、プライバシーや同意の問題が持ち上がります。さらに、AIがその人の同意の有無にかかわらず、その人のやり方でコンテンツを制作できるようになれば、個人が仕事を失う可能性も現実味を帯びてきます。こうした生成型AIの制約から、企業が利用をためらい、市場の拡大を阻害する可能性があります。
コンポーネントの展望
コンポーネントに基づいて、ジェネレーティブAI市場はソフトウェアとサービスに分類されます。2021年の売上高シェアが最も大きいソフトウェア分野は、ジェネレーティブAI市場を牽引しています。過去の単語列から次の単語を予測したり、過去の画像を説明する単語から次の画像を予測したりするために、ソフトウェアは高度な機械学習アルゴリズムを活用します。ソフトウェア市場の拡大には、不正行為の増加、スキルの過大評価、予期せぬ結果、データプライバシーへの懸念の高まりなど、さまざまな変動要因があると考えられます。
技術の展望
ジェネレーティブAI市場は、技術に基づいて、生成敵対的ネットワーク(GAN)、トランスフォーマー、変分オートエンコーダー、拡散ネットワークに分類されます。ジェネレーティブAI市場の拡散ネットワーク部門は、2021年に大きく収益を伸ばしました。画像生成は、BFSI、ヘルスケア、自動車&輸送、メディア&エンターテインメント、防衛など多くの産業で、企業、政府、一般市民に高い価値を提供するための設備を備えているため、画像合成の需要の高まりに対応するために極めて重要になってきています。
最終用途の展望
エンドユースに基づいて、ジェネレーティブAI市場は、メディア&エンターテインメント、BFSI、IT&コミュニケーション、ヘルスケア、自動車&輸送、その他に分類されます。ジェネレーティブAIの市場は、2021年にヘルスケア分野で有望な成長率を記録しています。3DプリンティングやCRISPRなどの技術によって活性化されると、ジェネレーティブAIは有機分子や義肢などを無から作り出すことができます。さらに、悪性腫瘍の可能性を早期に発見することで、より優れた治療戦略が可能になります。COVID-19の治療法を見つけるために、IBMは現在、この技術を使って抗菌ペプチド(AMP)を研究しています。
地域別の展望
地域別に、ジェネレーティブAI市場は、北米、欧州、アジア太平洋、LAMEAに分類されます。北米地域は最大の収益シェアを生み出し、それによって2021年のジェネレーティブAI市場を世界的に支配しています。これは、医療や擬似イメージの上昇、銀行詐欺の増加といったことが理由です。また、米国のマイクロソフト、メタ、グーグルLLCなどの主要な市場参入企業や、洗練されたテクノロジー企業、専門家の存在により、地域のジェネレーティブAI市場は増加すると予測されます。
市場参入企業がとる主な戦略は、「買収」です。カーディナルマトリックスで提示された分析に基づき、Google LLCとMicrosoft Corporationは、ジェネレーティブAI市場の先駆者です。Amazon.com, Inc.、Adobe, Inc.、IBM Corporationなどの企業は、ジェネレーティブAI市場の主要なイノベーターです。
List of Figures
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