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AI＆機械学習のリサーチサービス – 年間サービス

AI & Machine Learning Research Service

調査会社ABIリサーチ
種別英文年間契約型サービス
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ABIリサーチの年間サービス「AI＆機械学習のリサーチサービス – AI & Machine Learning Research Service」は人工知能（AI）と機械学習（マシンラーニング／ML）に関する市場情報を1年を通じて提供しています。

AI & Machine Learning Coverage

Our extensive coverage of AI and ML includes data, trends, forecasts, and benchmark and analysis reports. We assess the key technical and business factors that are essential for shaping AI and ML market activity and business models, including ML as a service, technology and platform as a service, software licensing, and edge AI hardware and applications. We also provide technology implementers with authoritative insight into the various AI and ML applications and use cases they should leverage to best streamline industrial and business processes as AI technology becomes accessible.

Our approach to market coverage is use-case centric as it looks at technology implementation for each use case studied. Aside from verticals that have existing AI implementation, such as consumer electronics and robotics, we also track AI and ML deployment in retail, manufacturing, energy, automotive, public safety and telecommunications. Special attention is dedicated to AI edge solutions.

Reports & Data

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出版レポート一覧

クラウドAIのマーケットデータ　2025年第3四半期：人工知能と機械学習
Artificial Intelligence and Machine Learning: Cloud AI
Market Data | 3Q 2025 | MD-AIMLCL-103 *

Artificial Intelligence and Machine Learning: Personal & Work Devices Market Data Overview: 3Q 2025
Presentation | 3Q 2025 | PT-3881

Artificial Intelligence and Machine Learning: Edge AI Market Data Overview: 3Q 2025
Presentation | 3Q 2025 | PT-3885

Artificial Intelligence and Machine Learning: Personal & Work Devices
Market Data | 3Q 2025 | MD-AIMLED-103

Artificial Intelligence and Machine Learning: Edge AI
Market Data | 3Q 2025 | MD-AIMLOD-103

Artificial Intelligence & Machine Learning: Cloud AI Market Data Overview: 3Q 2025
Presentation | 3Q 2025 | PT-3884

Artificial Intelligence and Machine Learning: TinyML
Market Data | 3Q 2025 | MD-AIMLT-103

人工知能と機械学習のマーケットデータ　2025年第3四半期
Artificial Intelligence and Machine Learning
Market Data | 3Q 2025 | MD-AIML-113

エージェントAIのTOCとROI評価のマーケットデータ　2025年第3四半期
Agentic AI Total Cost of Ownership (TCO) and Return on Investment (ROI) Assessment
Market Data | 3Q 2025 | MD-AGAI-101

エージェントAIのTOCとROI評価のマーケットデータ概観　2025年第3四半期
Agentic AI Total Cost of Ownership (TCO) and Return on Investment (ROI) Assessment Market Data Overview: 3Q 2025
Presentation | 3Q 2025 | PT-3772

Agentic AI Market Update: Product Development, Monetization, and Enterprise Value Creation
Presentation | 3Q 2025 | PT-3859

AIサーバーOEMの競合ランキング　2025年第3四半期
AI Server OEMs
Competitive Ranking | 3Q 2025 | CA-1578

Edge-Focused AI Chip Vendors Expand Their Software Stack to Drive Developer Engagement
Report | 3Q 2025 | AN-6480

Edge AI Software Market Update: How Can Incumbent Hardware Vendors Drive Engagement?
Report | 3Q 2025 | AN-6486

フルスタックソフトウェア投資で差別化を図るTinyMLチップベンダ
TinyML Chip Vendors Target Differentiation with Full Stack Software Investment
Report | 2Q 2025 | AN-6428

人工知能（AI）センシングソフトウェアのマーケットデータ　2025年第2四半期
Artificial Intelligence (AI) Sensing Software
Market Data | 2Q 2025 | MD-AISCV-102 *

人工知能（AI）用ソフトウェアのマーケットデータ概観　2025年第2半期
Artificial Intelligence (AI) Software Market Data Overview: 2Q 2025
Presentation | 2Q 2025 | PT-3735

人工知能（AI）用ソフトウェアのマーケットデータ　2025年第2四半期
Artificial Intelligence (AI) Software
Market Data | 2Q 2025 | MD-AISOFT-103

予測型人工知能（AI）用ソフトウェアのマーケットデータ　2025年第2四半期
Predictive Artificial Intelligence (AI) Software
Market Data | 2Q 2025 | MD-AISP-102

人工知能（AI）用自然言語処理（NLP）ソフトウェアのマーケットデータ　2025年第2四半期
Artificial Intelligence (AI) Natural Language Processing (NLP) Software
Market Data | 2Q 2025 | MD-AISNLP-102

生成的人工知能（生成AI）用ソフトウェアのマーケットデータ　2025年第2四半期
Generative Artificial Intelligence (Gen AI) Software
Market Data | 2Q 2025 | MD-AISG-102

AIサーバー出荷数と収益のマーケットデータ　2025年第2四半期
AI Server Shipments and Revenue
Market Data | 2Q 2025 | MD-AISS-101 *

AI Server Shipments and Revenue Market Data Overview: 2Q 2025
Presentation | 2Q 2025 | PT-3728

AI Chipsets for the IoT: Addressable Markets and Forecast Expectations
Report | 2Q 2025 | AN-6276

Edge AI Hardware Landscape: Key Themes & Takeaways from embedded world 2025 and Beyond
Presentation | 2Q 2025 | PT-6029

Transforming Enterprise AI: From Generative Hype to a Pragmatic Strategy
Presentation | 1Q 2025 | PT-3607

Agentic AI: Opportunities & Challenges
Presentation | 1Q 2025 | PT-3605

AI Regulatory Trends in Southeast Asia
Report | 1Q 2025 | AN-6048

DeepSeek’s AI Market Turmoil: Froth or Fundamental?
Presentation | 1Q 2025 | PT-3647

Artificial Intelligence and Machine Learning
Market Data | 1Q 2025 | MD-AIML-112

Artificial Intelligence and Machine Learning Market Data Overview: 1Q 2025
Presentation | 1Q 2025 | PT-3643

Artificial Intelligence and Machine Learning: Cloud AI Market Data Overview: 1Q 2025
Presentation | 1Q 2025 | PT-3640

Artificial Intelligence and Machine Learning: Cloud AI
Market Data | 1Q 2025 | MD-AIMLCL-102

個人用および仕事用デバイス　2025年第1四半期：人工知能と機械学習ののマーケットデータ
Artificial Intelligence and Machine Learning: Personal & Work Devices
Market Data | 1Q 2025 | MD-AIMLED-102

Artificial Intelligence and Machine Learning: Personal & Work Devices Market Data Overview: 1Q 2025
Presentation | 1Q 2025 | PT-3013

Artificial Intelligence and Machine Learning: Edge AI
Market Data | 1Q 2025 | MD-AIMLOD-102

Artificial Intelligence and Machine Learning: Edge AI Market Data Overview 1Q 2025
Presentation | 1Q 2025 | PT-3638

Artificial Intelligence and Machine Learning: TinyML
Market Data | 1Q 2025 | MD-AIMLT-102

Artificial Intelligence and Machine Learning: TinyML Market Data Overview: 1Q 2025
Presentation | 1Q 2025 | PT-3641

The Transition from Computer Vision to Large Visual Models (LVMs): What Are the Implications for Enterprises and Vendors?
Report | 1Q 2025 | AN-6220

AI/ML Private Sector B2B Spending in Southeast Asia Market Data Overview: 1Q 2025
Presentation | 1Q 2025 | PT-3633

AI/ML Private Sector B2B Spending in Southeast Asia
Market Data | 1Q 2025 | MD-SEAS-101

AI Market: Yearly Roundup & Expectations for 2025
Presentation | 4Q 2024 | PT-6023

AI Server OEM/ODM Market
Report | 4Q 2024 | AN-6284

101 Tech Trends That Will—And Won’t—Shape 2025
Whitepaper | 4Q 2024 | WP-221

Opportunities and Challenges For Compute Express Link
Whitepaper | 4Q 2024 | WP-219

Exploring Open-Source AI Commercial Strategies
Presentation | 4Q 2024 | PT-3022

Open-Source AI Technology Innovation Opportunities & Challenges
Presentation | 4Q 2024 | PT-3023

Commercial and Industrial Machine Vision
Market Data | 3Q 2024 | MD-CIMVR-101

Commercial and Industrial Machine Vision Market Data Overview: 3Q 2024
Presentation | 3Q 2024 | PT-3012

Industrial and Manufacturing Survey 1H 2024: Artificial Intelligence & Machine Learning
Presentation | 3Q 2024 | PT-3336

Understanding NVIDIA: Growth Drivers and Potential Headwinds
Research Report | 3Q 2024 | AN-6287

FPGA AI Market Update: 3Q 2024
Presentation | 3Q 2024 | PT-3004

Artificial Intelligence & Machine Learning: Market Data Overview Q3 2024
Presentation | 3Q 2024 | PT-3299

Artificial Intelligence and Machine Learning
Market Data | 3Q 2024 | MD-AIML-111

タイトル出版時期形式
グリーナーデータセンタ：AIのカーボンフットプリントを最小限にしたグリーナービルディング
Building Greener Data Centers to Minimize AI’s Carbon Footprint
Presentation | 3Q 2024 | PT-3219		2024年7月PDF
クラウドAIのマーケットデータ　2024年第2四半期：人工知能＆機械学習
Artificial Intelligence & Machine Learning: Cloud AI
Market Data | 2Q 2024 | MD-AIMLCL-101		2024年6月Excel
クラウドAIのマーケットデータ概観：人工知能＆機械学習：2024年第2四半期
Artificial Intelligence & Machine Learning: Cloud AI Market Data Overview: 2Q 2024
Presentation | 2Q 2024 | PT-3236		2024年6月PDF
ディスクリート製造向け生成AIソリューション
Generative AI Solutions for Discrete Manufacturing
Presentation | 2Q 2024 | PT-3233		2024年6月PDF
人工知能＆機械学習：エッジAIマーケットデータ概観　2024年第2四半期
Artificial Intelligence & Machine Learning: Edge AI Market Data Overview 2Q 2024
Presentation | 2Q 2024 | PT-3011		2024年5月PDF
エッジAIのマーケットデータ　2024年第2四半期：人工知能と機械学習市場データ
Artificial Intelligence and Machine Learning: Edge AI
Market Data | 2Q 2024 | MD-AIMLOD-101		2024年5月Excel
個人用＆作業用デバイスのマーケットデータ　2024年第2四半期：人工知能と機械学習市場データ
Artificial Intelligence and Machine Learning: Personal & Work Devices
Market Data | 2Q 2024 | MD-AIMLED-101		2024年4月Excel
人工知能＆機械、個人用＆作業用デバイスマーケットデータ概観　2024年第2四半期
Artificial Intelligence and Machine Learning, Personal & Work Devices Market Data Overview: 2Q 2024
Presentation | 2Q 2024 | PT-2603		2024年4月PDF
人工知能と最適化プラットフォーム向け商用＆技術的機会
Commercial and Technical Opportunities for Artificial Intelligence Optimization Platforms
Research Report | 2Q 2024 | AN-6141		2024年4月PDF
分散型コンピュートコンティニュアムでのAI最適化によるチップセット差別化構築
Building Chipset Differentiation with AI Optimization across the Distributed Compute Continuum
Research Report | 2Q 2024 | AN-6140		2024年4月PDF
テックタイタンの対立（無料レポート）
Clash Of The Tech Titans
Whitepaper | 2Q 2024 | WP-201		2024年4月PDF
NVIDIA GTC 2024の重要ポイント
Key Takeaways From NVIDIA GTC 2024
Whitepaper | 1Q 2024 | WP-200		2024年月PDF
AI／ML市場のマーケットデータ　2024年第1四半期
AI/ML Market Tracker
Market Data | 1Q 2024 | MD-AIMLMT-101		2024年3月Excel
人工知能のバリューチェーンのマーケットデータ概観　2024年第1四半期
Artificial Intelligence Value Chain Tracker Market Data Overview: Q1 2024
Presentation | 1Q 2024 | PT-2743		2024年3月PDF
モバイルおよびPC機器向け生産性向上AI
Productivity AI for Mobile and PC Devices
Research Report | 1Q 2024 | AN-6127		2024年2月PDF
ヘテロジニアス・コンピューティングの将来性：瀬戸際の汎用AIと生成AI
Opportunities for Heterogenous Computing: General & Generative AI at the Edge
Research Report | 1Q 2024 | AN-5471		2024年2月PDF
エッジAIアプリケーション向けRISC-V
RISC-V for Edge AI Applications
Research Report | 1Q 2024 | AN-6121		2024年1月PDF
AI／MLハードウェア投資トラッカー 2024年第1四半期
AI/ML Hardware Investment Tracker
Presentation | 1Q 2024 | PT-2793		2024年1月PDF
通信会社によるBSS／OSSのAIトランスフォーメーション向け戦略の定義
Defining Telco Strategy for BSS/OSS Artificial Intelligence Transformation
Presentation | 4Q 2023 | PT-2798		2023年12月PDF
人工知能の重要動向：オンデバイスAI、オープンソース投資、データサービスの資金調達など
Key Trends in AI: On-device AI, Open-Source Investment, Data Service Funding and More
Presentation | 4Q 2023 | PT-2777		2023年10月PDF
人工知能（AI)ソフトウェアのマーケットデータ　2023年第3四半期
Artificial Intelligence (AI) Software
Market Data | 3Q 2023 | MD-AISOFT-101		2023年8月EXCEL
製造業における生成AIのユースケース
Generative AI Use Cases in Manufacturing
Presentation | 3Q 2023 | PT-2763		2023年8月PDF
生成AI：技術提供の収益機会調査
Generative AI: Identifying Technology Supply Side Revenue Opportunities
Research Report | 2Q 2023 | AN-5832		2023年6月PDF
生成AIビジネスの成果のリサーチレポート：法人利用の商業機会
Generative AI Business Outcomes: Identifying Enterprise Commercial Opportunities
Research Report | 2Q 2023 | AN-5861		2023年6月PDF
Industrial/Manufacturing: 30 Action Items for Reducing Carbon Emissions, Water Use, and Waste
Presentation | 2Q 2023 | PT-2732		2Q 2023PDF
Sustainability Assessment: Large Industrial Solution Providers
Competitive Ranking | 2Q 2023 | CA-1398		2Q 2023PDF
Commercial and Industrial Machine Vision
Market Data | 1Q 2023 | MD-CIVM-102		1Q 2023Excel
37 Technology Stats You Need to Know for 2023
Whitepaper | 1Q 2023 | WP-1013		1Q 2023PDF
Artificial Intelligence and Machine Learning
Market Data | 1Q 2023 | MD-AIML-110		1Q 2023Excel
74 Technology Trends that Will-and Will Not-Shape 2023
Whitepaper | 1Q 2023 | WP-1012		1Q 2023PDF

Coverage areas include:

  • Machine learning
  • Artificial intelligence
  • Augmented Intelligence
  • Deep Learning
  • Data analytics
  • Predictive analytics
  • Prescriptive analytics
  • Algorithms and hardware technologies segmentation
  • Analysis of AI Tools and SDKs
  • AI and ML hot technology innovators
  • Edge AI and ML
  • Market segmentation and taxonomy of AI and ML use cases and applications
  • Different implementation approaches of AI and ML
  • AI and ML business models
  • AI and ML use cases in the telecoms industry
  • In-building systems including DAS (Distributed Antenna Systems)
  • RF power semiconductors for pulsed applications
  • Detailed spectrum analysis for 5G networks, sub-6G to mmWave, including regional disparities
  • AI and ML use cases in the manufacturing industry
  • AI and ML use cases in the consumer market
  • AI and ML use cases in the IoT market
  • The role of open source in shaping new applications and business models
  • Emerging trends in speech and image recognition, machine vision, natural language processing, touch/haptics, Generative and Creative Adversarial Networks, automated reasoning and security applications
  • Analysis of edge AI versus cloud AI

Answers To Today’s Critical AI & Machine Learning Questions

We help technology suppliers and implementers answer the most pressing questions about AI & Machine Learning, including:

Technology Suppliers:

  • How are the different ML hardware and algorithms are mapped against requirements of the different use cases addressed?
  • What are the key verticals that will drive AI and ML applications?
  • Should I create my own AI frameworks and solutions or should I adopt existing open frameworks?
  • Who are competitors I should watch and who are those I should partner with?
  • What emerging verticals should my organization target?
  • How big is the revenue opportunity?
  • What major challenges will the industry face when managing a myriad of data generated by billions of connected devices?
  • Who are the companies and organizations my company should partner with to create adequate solutions for the verticals are targeting?
  • Where does my company fit in the AI/ML competitive landscape?
  • How can my organization productize open source code?
  • How can we stream value from it?
  • What are the most successful open-source communities and frameworks for my company to rely on?
  • Do I have any benefit from contributing and using open source and what are the risks?
    What are the most invested in AI R&D projects and frameworks?
    What impact will the move from cloud-based to edge based have on the market dynamics and supplier positioning?

Implementers & End Users:

  • How can I implement AI in my current business activities?
    How will AI create new market opportunities in my sector?
    What is the realistic time to maturity of different AI components?
    What is the best approach for integrating AI into my company’s ecosystem?
    What criteria should I consider when choosing an AI partner?
    What advanced analytics techniques should my company consider adopting?
    What are the main types of algorithms used in ML today and how this is going to evolve in the future?
    How can my company utilize AI to simplify our business and operation processes?
    What is the difference between predictive and prescriptive analytics, and what is the best course of action for my company to take to effectively keep tabs on all our generated data?
    What can my company discern from our generated data through advanced analytics?
    Are there any security concerns my company should be made aware of when relying on advanced analytics?
    How can my company protect our data and our customers’ data? • What is the value of edge computing versus cloud computing?
    Should I be using an open-source AI framework to develop models, and which one would suit my needs?

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