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1548877

機器學習即服務 (MLaaS)：市場佔有率分析、產業趨勢/統計、成長預測 (2024-2029)

Machine Learning As A Service (MLaaS) - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 140 Pages | 商品交期: 2-3個工作天內

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簡介目錄

機器學習即服務市場規模預計到 2024 年為 337.5 億美元，預計到 2029 年將達到 1545.9 億美元，在預測期內（2024-2029 年）複合年成長率預計為 35.58%。

機器學習即服務 (MLaaS) - 市場

機器學習即服務市場的推動因素是企業擴大採用雲端基礎的服務、物聯網和自動化，企業越來越需要縮短時間、增強決策能力、由於了解消費行為的需求不斷成長，加上消費者的需求不斷成長，自動化流程並推動創新正在迅速發展。

主要亮點

  • MLaaS 模型主導著市場，使用者可以從專注於不同業務需求的各種工具中進行選擇，包括資料視覺化、API、臉部辨識、自然語言處理、預測分析和深度學習，我們正在準備這樣做。資料科學和人工智慧的進步正在加速機器學習的性能。企業越來越意識到這項技術的潛力，MLaaS 的採用率預計在預測期內將會增加。
  • 此外，MLaaS 使公司能夠利用機器學習的潛力，而無需內部專業知識，使其成為推動創新和競爭優勢的寶貴工具。此外，據分析，隨著世界各地的企業尋求在即時場景中利用機器學習的預測能力，尋求改進決策、自動化流程和增強用戶體驗的企業對 MLaaS 平台的需求正在迅速增加。
  • 機器學習即服務 (MLaaS) 是雲端處理的關鍵功能。從資料視覺化和 API 到臉部辨識、NLP、預測分析和深度學習，MLaaS 擁有各種工具，使其成為尋求增強業務的企業的全面解決方案。雲端服務的快速擴張和業務向雲端平台的遷移證實了MLaaS正處於一個充滿希望的軌道上。
  • 機器學習（ML）技術作為一種新的攻擊方法正在引起人們的注意。隨著機器學習越來越融入日常業務，包括醫療保健、金融、行動裝置、汽車系統和家庭安全，它將不可避免地成為網路攻擊者的有吸引力的目標。
  • 疫情過後，企業雲端服務支出顯著成長，推動了 MLaaS 平台在終端用戶領域的採用。例如，根據 Flexera Software 的 2024 年雲端狀況報告，到 2024 年下半年，17% 的企業受訪者表示年度公共雲端支出將超過 600 萬美元到 1,200 萬美元。此外，到 2024 年下半年，10% 的企業受訪者表示，他們的年度公共雲端支出將超過 6,000 萬美元。此外，14% 的企業受訪者表示，他們每年的公共雲端支出在 1,200 萬美元至 2,400 萬美元之間。

機器學習即服務 (MLaaS) 市場趨勢

醫療保健是成長最快的最終用戶

  • 近年來，機器學習技術的應用迅速擴展。世界各地的醫療機構正在轉向機器學習技術來分析大量患者資料、識別模式並為疾病診斷、藥物發現和個人化治療計劃做出更準確的預測。這些因素以及經濟高效地利用機器學習工具和資源的需求正在推動醫療保健產業對 MLaaS 平台的需求。
  • 醫療保健組織對 MLaaS 的需求正在獲得巨大的吸引力，以有效管理員工日程安排。機器學習即服務 (MLaaS) 為醫療保健組織配備了先進的調度演算法。這些演算法旨在分析大量歷史資料並準確預測未來的人員配置需求。此外，醫療保健組織採用 MLaaS 無需在內部開發這些複雜的演算法，從而節省了時間和資源。
  • 2023 年 7 月，Amazon Web Services, Inc. (AWS) 宣布推出符合 HIPAA合格的AWS HealthScribe 服務。該服務使醫療保健軟體提供者能夠創建利用語音辨識和生成人工智慧的臨床應用程式。其目的是透過自動建立臨床文件來簡化臨床醫生的工作流程。由 Amazon Bedrock 提供支援的 AWS HealthScribe 簡化了醫療保健軟體供應商的生成式 AI 功能的整合。
  • 主要的發展是將這一功能引入兩個主要的醫學領域：普通醫學和整形外科，其中提供者正在使用複雜的機器學習基礎設施並開發自己的大規模語言模型（LLM），從而消除了這樣做的需要。這種市場開拓將進一步支持市場成長。
  • 透過應用，對自然語言處理、電腦視覺和情感分析等其他應用進行分析，以在醫療保健領域獲得顯著的吸引力。例如，MLaaS 平台提供電腦視覺功能，可以發現 X 光、 電腦斷層掃描、MRI 和乳房 X 光檢查中的異常情況，幫助醫療保健提供者診斷疾病。此外，MLaaS平台還可以提供情緒分析服務，可以有效衡量患者的情緒、情緒和滿意度。
  • 因此，在醫療保健領域採用MLaaS 平台將幫助醫療保健提供者有效地診斷疾病、監測患者健康狀況、支持藥物發現並提供個人化治療以增強患者護理。場革命。
  • 此外，在預測期內，物聯網（尤其是醫療物聯網設備）的利用率不斷提高，以及全球醫療保健組織擴大採用雲端基礎的服務，將進一步推動醫療保健產業 MLaaS 市場的成長。
  • 企業擴大採用物聯網，這增加了從物聯網設備產生的大量資料中有效提取有意義的見解的需求。這種需求正在推動 MLaaS（機器學習即服務）的快速成長，它日益影響資料探勘並支援創新業務解決方案的創建。例如，根據GSMA資料，到2030年，全球企業物聯網（IoT）連線數量預計將達到240億。

北美佔最大市場佔有率

  • 北美擁有強大的創新生態系統，由聯邦對先進技術的戰略投資推動，並輔以來自世界知名研究機構的富有遠見的科學家和企業家，有望推動 MLaaS 的發展並佔領大量市場佔有率。
  • 例如，2023年5月，美國國家科學基金會（NSF）將與高等教育機構、其他聯邦機構和其他相關人員合作，宣布投資140美元建立7個新的國家人工智慧研究所（AI）。萬。透過這項投資，政府旨在透過推廣人工智慧系統和技術以及在美國培養多元化的人工智慧勞動力，推動對人工智慧相關機會和風險採取一致的方法。地方政府的此類投資預計將為所研究的市場帶來新的成長機會。
  • 此外，2024年3月，英特爾宣布重大投資1,000億美元用於擴張和升級計畫。該計劃包括在美國四個州建立新的製造設施，並在聯邦財政支持下增強現有設施。美國政府將提供 195 億美元的聯邦撥款和 250 億美元的稅收優惠來支持英特爾的擴張。此外，英特爾還計劃未來五年內在俄亥俄州哥倫布市附近建立「全球最大的人工智慧晶片製造地」。此類人工智慧努力可能會進一步推動該地區的研究市場需求。
  • 該地區也大量採用 5G、物聯網和連網型設備。因此，通訊服務供應商(CSP) 必須透過虛擬、網路切片、新用例和服務需求來有效管理日益增加的複雜性。因此，傳統的網路和服務管理方法不再永續，MLaaS解決方案有望得到推廣。據 GSMA 稱，到 2025 年，北美消費者和工業物聯網連接總數預計將成長至 54 億。

機器學習即服務 (MLaaS) 產業概述

MLaaS 市場高度分散，主要企業包括 Microsoft Corporation、IBM Corporation、Google LLC (Alphabet Inc.)、SAS Institute Inc. 和 Fair Isaac Corporation (FICO)。市場上的公司正在採取聯盟和收購等策略來加強其產品供應並獲得永續的競爭優勢。

  • 2024 年 5 月 - 著名的技術服務和顧問公司 Wipro 與 Microsoft 合作，宣布推出三款專為金融領域量身定做的認知助理。這包括 Wipro GenAI 投資者情報、Wipro GenAI 投資者入門和 Wipro GenAI 貸款發放。此認知助理由 Azure OpenAI 提供支持，旨在與當今的數位和行動平台無縫整合。這種整合為金融專業人士及其客戶提供了一個統一、易於使用的資訊中心。
  • 2024 年 3 月 - Hewlett Packard Enterprise 宣布增強 AIOps 網路管理功能。此增強功能包括將多個生成式 AI (GenAI) 大型語言模型 (LLM) 整合到 HPE Aruba Networking Central 中。此雲端原生網路管理解決方案是 HPE GreenLake 雲端平台產品的一部分。這些增強功能主要旨在提高使用者體驗和操作效率，特別關注搜尋回應時間、準確性和資料隱私。

其他好處

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 買方議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度
  • 產業價值鏈分析
  • COVID-19 市場影響評估

第5章市場動態

  • 市場促進因素
    • 物聯網和自動化的採用增加
    • 更多採用雲端基礎的服務
  • 市場限制因素
    • 隱私和資料安全問題
    • 需要熟練的專業人員

第6章 市場細分

  • 按用途
    • 行銷和廣告
    • 預測性維護
    • 自動網路管理
    • 詐欺偵測和風險分析
    • 其他用途
  • 按組織規模
    • 小型企業
    • 主要企業
  • 按最終用戶
    • 資訊科技和電訊
    • 車
    • 衛生保健
    • 航太/國防
    • 零售
    • 政府機構
    • BFSI
    • 其他最終用戶
  • 按地區
    • 北美洲
    • 歐洲
    • 亞洲
    • 澳洲/紐西蘭
    • 拉丁美洲
    • 中東/非洲

第7章 競爭格局

  • 公司簡介
    • Microsoft Corporation
    • IBM Corporation
    • Google LLC（Alphabet Inc.）
    • SAS Institute Inc.
    • Fair Isaac Corporation（FICO）
    • Hewlett Packard Enterprise Company
    • Yottamine Analytics LLC
    • Amazon Web Services Inc.（Amazon.Com, Inc.）
    • BigML Inc.
    • Iflowsoft Solutions Inc.
    • Monkeylearn Inc.
    • Sift Science Inc.
    • H2O.ai Inc.

第8章投資分析

第9章市場的未來

簡介目錄
Product Code: 55039

The Machine Learning As A Service Market size is estimated at USD 33.75 billion in 2024, and is expected to reach USD 154.59 billion by 2029, growing at a CAGR of 35.58% during the forecast period (2024-2029).

Machine Learning As A Service (MLaaS) - Market

The Machine Learning as a Service market is evolving rapidly owing to the growing adoption of cloud-based services, IoT, and automation in businesses, the growing need among businesses for accelerated time to market for intelligent applications, the rising need to understand consumer behavior coupled with the growing need to enhance decision-making, automate processes, and drive innovation.

Key Highlights

  • MLaaS model is poised to dominate the market, with users having the option to choose from a wide variety of tools such as data visualization, APIs, face recognition, natural language processing, predictive analytics, and deep learning focused on different business needs. Advancements in data science and artificial intelligence have propelled the pace of machine learning's performance. Companies are increasingly recognizing the technology's potential, indicating a projected uptick in adoption rates of MLaaS over the forecast period.
  • Moreover, MLaaS empowers businesses to leverage the potential of machine learning without the need for extensive in-house expertise, thus making it a valuable tool in fostering innovation and competitive advantage. Further, as businesses worldwide seek to leverage the predictive capabilities of machine learning in real-time scenarios, the demand for MLaaS platforms is analyzed to grow at a rapid pace among businesses to improve decision-making, automate processes, and enhance user experiences.
  • Machine learning-as-a-service (MLaaS) is a pivotal feature within cloud computing offerings. With its array of tools, from data visualization and APIs to facial recognition, NLP, predictive analysis, and deep learning, MLaaS stands out as a comprehensive solution for businesses seeking to enhance their operations. The rapid expansion of cloud services and businesses increasingly transitioning to cloud platforms underscores a promising trajectory for MLaaS.
  • Machine learning (ML) technology introduces a novel attack surface, garnering significant research attention. As ML integrates further into daily operations, spanning healthcare, finance, mobile devices, automotive systems, and home security, it inevitably becomes a prime target for cyber attackers.
  • Post-pandemic, the spending on cloud services across enterprises is witnessing significant growth, which is analyzed to bolster the adoption of MLaaS platforms in the end-user sectors. For instance, according to Flexera Software's State of the Cloud Report 2024, by late 2024, 17% of enterprise respondents reported annual public cloud expenditures ranging from over USD 6 million to USD 12 million. Furthermore, by late 2024, 10% of enterprise respondents reported annual public cloud expenditures of more than USD 60 million. Moreover, 14% of enterprise respondents reported annual public cloud expenditures between USD 12 million and USD 24 million.

Machine Learning As A Service (MLaaS) Market Trends

Healthcare to be the Fastest Growing End User

  • The application of machine learning technology has been expanding at a significant pace in the past few years. Healthcare organizations worldwide are demanding machine learning technology to analyze vast amounts of patient data to identify patterns and make more accurate predictions about disease diagnosis, drug discovery, and personalized treatment plans. Due to these factors, the need to access machine learning tools and resources cost-effectively has driven the demand for MLaaS platforms in the healthcare sector.
  • The demand for MLaaS is gaining significant traction in healthcare organizations to manage staff schedules effectively. Machine Learning as a Service (MLaaS) equips healthcare organizations with advanced scheduling algorithms. These algorithms are designed to analyze extensive historical data, enabling precise predictions of future staffing requirements. Further, the adoption of MLaaS in healthcare organizations eliminates the need to develop these complex algorithms in-house, saving them time and resources.
  • In July 2023, Amazon Web Services Inc. (AWS) unveiled AWS HealthScribe, a HIPAA-eligible service. This service equips healthcare software providers to create clinical applications that leverage speech recognition and generative AI. The goal is to streamline clinicians' workflows by automating the generation of clinical documentation. AWS HealthScribe, backed by Amazon Bedrock, simplifies the integration of generative AI features for healthcare software providers.
  • Notably, it offers this functionality for two key medical specialties-general medicine and orthopedics-eliminating the need for providers to handle the complex machine-learning infrastructure or develop their own large language models (LLMs). Such developments further support the market growth.
  • By application other applications such as NLP, computer vision, and sentiment analysis are analyzed to gain significant traction in the healthcare sector. For instance, MLaaS platforms offer computer vision capabilities, spotting irregularities in X-rays, CT scans, MRIs, and mammograms, thus helping healthcare providers in diagnosing diseases. Furthermore, MLaaS platforms can also offer sentiment analysis services that can effectively measure patients' emotions, moods, or satisfaction levels.
  • Therefore, the adoption of MLaaS platforms in the healthcare sector is analyzed to revolutionize the healthcare sector by helping healthcare providers to effectively diagnose diseases, monitor patients' health, drug discovery, and offer personalized treatment to enhance patient care.
  • Additionally, the expanding use of IoT, notably medical IoT devices, and the growing adoption of cloud-based services in healthcare organizations worldwide will further bolster the growth of the MLaaS market in the healthcare sector over the forecast period.
  • The increasing adoption of IoT in businesses fuels a heightened need to effectively extract meaningful insights from the vast data generated by IoT devices. This demand is propelling the rapid growth of Machine Learning as a Service (MLaaS), which is increasingly shaping data mining and enabling the creation of innovative business solutions. For instance, according to the data from GSMA, the number of enterprise Internet of Things (IoT) connections worldwide is forecasted to reach 24 billion by 2030.

North America Holds Largest Market Share

  • North America is expected to hold a significant share of the market owing to its robust innovation ecosystem, fueled by strategic federal investments into advanced technology and complemented by the presence of visionary scientists and entrepreneurs coming together from globally renowned research institutions, which has propelled the development of MLaaS.
  • For instance, in May 2023, The US National Science Foundation (NSF), in collaboration with higher education institutions, other federal agencies, and other stakeholders, announced an investment of USD 140 million to establish seven new National Artificial Intelligence Research Institutes (AI) institutes. Through this investment, the government aims to promote AI systems and technologies and develop a diverse AI workforce in the United States to advance a cohesive approach to AI-related opportunities and risks. Such investments by the regional government are expected to create new growth opportunities for the market studied.
  • In addition, in March 2024, Intel announced a significant USD 100 billion investment in an expansion and upgrade initiative. This initiative includes establishing new manufacturing plants in four US states and enhancing current facilities, bolstered by the federal government's financial backing. The US government committed USD 19.5 billion in federal grants and an additional USD 25 billion in tax incentives to bolster Intel's expansion. Furthermore, Intel plans to construct "the world's largest AI chip manufacturing site" near Columbus, Ohio, within the next five years. Such initiatives in AI may further propel the studied market demand in the region.
  • The region also witnessed a significant proliferation of 5G, IoT, and connected devices. As a result, communications service providers (CSPs) need to manage an ever-growing complexity efficiently through virtualization, network slicing, new use cases, and service requirements. This is expected to drive MLaaS solutions as traditional network and service management approaches are no longer sustainable. According to GSMA, North America's total number of consumer and industrial IoT connections is forecast to grow to 5.4 billion by 2025.

Machine Learning As A Service (MLaaS) Industry Overview

The MLaaS market is highly fragmented, with the presence of major players like Microsoft Corporation, IBM Corporation, Google LLC (Alphabet Inc.), SAS Institute Inc., and Fair Isaac Corporation (FICO). Players in the market are adopting strategies such as partnerships and acquisitions to enhance their product offerings and gain sustainable competitive advantage.

  • May 2024 - Wipro, a prominent technology services and consulting firm, partnered with Microsoft to launch a trio of cognitive assistants tailored for the financial sector. It includes Wipro GenAI Investor Intelligence, Wipro GenAI Investor Onboarding, and Wipro GenAI Loan Origination. The cognitive assistants leveraging Azure OpenAI are designed to merge with current digital and mobile platforms seamlessly. This integration offers a unified and user-friendly information hub for financial professionals and their clientele.
  • March 2024 - Hewlett Packard Enterprise unveiled an expansion of its AIOps network management capabilities. This enhancement involves the integration of multiple Generative AI (GenAI) Large Language Models (LLMs) into HPE Aruba Networking Central. This cloud-native network management solution is part of HPE's offerings on the HPE GreenLake Cloud Platform. These enhancements primarily aim to elevate user experience and operational efficiency, with a specific emphasis on search response times, accuracy, and data privacy.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Buyers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Industry Value Chain Analysis
  • 4.4 Assessment of COVID-19 Impact on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Adoption of IoT and Automation
    • 5.1.2 Increasing Adoption of Cloud-based Services
  • 5.2 Market Restraints
    • 5.2.1 Privacy and Data Security Concerns
    • 5.2.2 Need for Skilled Professionals

6 MARKET SEGMENTATION

  • 6.1 By Application
    • 6.1.1 Marketing and Advertisement
    • 6.1.2 Predictive Maintenance
    • 6.1.3 Automated Network Management
    • 6.1.4 Fraud Detection and Risk Analytics
    • 6.1.5 Other Applications
  • 6.2 By Organization Size
    • 6.2.1 Small and Medium Enterprises
    • 6.2.2 Large Enterprises
  • 6.3 By End User
    • 6.3.1 IT and Telecom
    • 6.3.2 Automotive
    • 6.3.3 Healthcare
    • 6.3.4 Aerospace and Defense
    • 6.3.5 Retail
    • 6.3.6 Government
    • 6.3.7 BFSI
    • 6.3.8 Other End Users
  • 6.4 By Geography
    • 6.4.1 North America
    • 6.4.2 Europe
    • 6.4.3 Asia
    • 6.4.4 Australia and New Zealand
    • 6.4.5 Latin America
    • 6.4.6 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Microsoft Corporation
    • 7.1.2 IBM Corporation
    • 7.1.3 Google LLC (Alphabet Inc.)
    • 7.1.4 SAS Institute Inc.
    • 7.1.5 Fair Isaac Corporation (FICO)
    • 7.1.6 Hewlett Packard Enterprise Company
    • 7.1.7 Yottamine Analytics LLC
    • 7.1.8 Amazon Web Services Inc. (Amazon.Com, Inc.)
    • 7.1.9 BigML Inc.
    • 7.1.10 Iflowsoft Solutions Inc.
    • 7.1.11 Monkeylearn Inc.
    • 7.1.12 Sift Science Inc.
    • 7.1.13 H2O.ai Inc.

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET