カテゴリー： 世界, MarketsandMarkets

世界の製造業における人工知能(AI)市場（～2030年）

【英語タイトル】Artificial Intelligence in Manufacturing Market by Processor (MPUS, GPUs, FPGA, ASICs), Software (On-premises, Cloud), Technology (Machine Learning, NLP, Context-aware Computing, Computer Vision, Generative Al), Application - Global Forecast to 2030

MarketsandMarketsが出版した調査資料（SE 5470）・商品コード：SE 5470
・発行会社（調査会社）：MarketsandMarkets
・発行日：2025年8月
・ページ数：250
・レポート言語：英語
・レポート形式：PDF
・納品方法：Eメール（受注後1営業日）
・調査対象地域：グローバル
・産業分野：IT
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❖ レポートの概要 ❖

AI導入が進む製造業市場は、2024年の234億ドル規模から2025年には341.8億ドル、2030年には1,550.4億ドルへと年平均35.3％で急成長が見込まれています。予知保全や自律型品質管理、サプライチェーン最適化など、リアルタイムデータによる効率化とダウンタイム削減ニーズが拡大を後押しし、IIoT・エッジ・クラウド基盤の普及がデータ駆動型の工場運営を可能にしています。一方で、レガシー設備が生むデータ欠損やサイロ化、標準化不足はAI活用を阻害する主要課題となっています。
複数拠点を遠隔で最適制御する需要が高まるなか、AIは設備状態監視や負荷分散、予測分析を通じて柔軟性を強化できるものの、マイクロ秒レベルのフィードバックループを維持するためにはエッジ処理能力とネットワーク遅延解消が不可欠です。
地域別ではアジア太平洋が2025年に最大シェアを占め、中国が最速成長を示す見通しです。政府主導のスマートファクトリー施策とロボティクス投資が加速しており、自動車・電子部品・半導体などが導入を牽引します。用途別では高精度検査ニーズの高まりを背景に品質管理が最も高い成長率を示し、産業別では量産体制と安全基準が厳しい自動車業界が最大市場を維持します。
主要プレーヤーはNVIDIA、IBM、Siemens、Intel、AWSなどで、GPUリソース最適化強化を狙ったNVIDIAのRun:ai買収（2024年12月）や、SiemensによるAltair買収（同10月）、IBMの生成AIモデル「Granite 3.0」（2025年7月）など大型投資が相次ぎ、AIプラットフォームの統合が進展しています。これらの動向は品質向上、コスト削減、サステナビリティ要求への対応を支え、AIが次世代製造戦略の中核インフラとして定着することを示しています。

The Artificial Intelligence (AI) in Manufacturing market was valued at USD 23.40 billion in 2024 and is expected to climb to USD 155.04 billion by 2030, reflecting a 35.3% CAGR. Growth is fueled by AI’s ability to improve predictive maintenance, adaptive quality control, supply-chain orchestration, and overall production optimization, especially as industrial IoT, edge computing, and cloud adoption generate richer data streams for continuous learning.

Asia Pacific will lead both market share and growth through 2030, driven by heavy investments in smart factories, supportive government policies, and strong automation vendors in China, Japan, South Korea, and India. Automotive, electronics, aerospace, and food & beverage manufacturers are among the fastest adopters of AI to automate complex tasks, cut waste, and enhance product quality.

Key market drivers include the proliferation of connected devices that deliver real-time equipment data, enabling faster, data-driven decisions and reduced downtime. Major restraints center on poor data quality and siloed legacy systems that hinder scalable AI deployment. Opportunities arise from the shift toward remote, multisite operations where AI provides real-time visibility and coordination. A pressing challenge remains the management of real-time feedback loops; latency or fragmented data flow can disrupt tightly synchronized production lines.

Quality control is projected to be the fastest-growing application, as computer vision and machine learning outperform manual inspection in detecting defects and tracing root causes. The automotive sector currently commands the largest industry share, leveraging AI for design, assembly, predictive maintenance, and digital-twin simulations—trends amplified by electric and autonomous vehicle production.

Recent milestones include IBM’s Granite 3.0 model suite (July 2025), NVIDIA’s acquisition of Run:ai (Dec 2024), Siemens’ purchase of Altair Engineering (Oct 2024), the Microsoft–Siemens Azure AI partnership (Oct 2024), and Intel’s Gaudi 3 AI accelerator launch (Sept 2024). Leading vendors shaping the ecosystem include NVIDIA, Siemens, IBM, Intel, AWS, Microsoft, GE Vernova, and ABB, among others.

❖ レポートの目次 ❖

INTRODUCTION
15
  • 1.1 STUDY OBJECTIVES
  • 1.2 MARKET DEFINITION AND SCOPE
     INCLUSIONS AND EXCLUSIONS
  • 1.3 STUDY SCOPE
     MARKETS COVERED
     GEOGRAPHIC SEGMENTATION
     YEARS CONSIDERED FOR THE STUDY
  • 1.4 CURRENCY
  • 1.5 LIMITATIONS
  • 1.6 STAKEHOLDERS
  • 1.7 SUMMARY OF CHANGES
RESEARCH METHODOLOGY
20
  • 2.1 RESEARCH DATA
     SECONDARY DATA
    – Major Secondary Sources
    – Key Data from Secondary Sources
     PRIMARY DATA
    – Primary Interviews with Experts
    – Key Data from Primary Sources
    – Key Industry Insights
    – Breakdown of Primaries
  • 2.2 MARKET SIZE ESTIMATION
     BOTTOM-UP APPROACH
    – Approach for Capturing Market Share by Bottom-Up Analysis (Demand Side)
     TOP-DOWN APPROACH
    – Approach for Capturing Market Share by Top-Down Analysis (Supply Side)
  • 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
  • 2.4 RESEARCH ASSUMPTIONS
  • 2.5 RISK ASSESSMENT
  • 2.6 LIMITATIONS OF RESEARCH
EXECUTIVE SUMMARY
25
PREMIUM INSIGHTS
30
MARKET OVERVIEW
35
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER’S BUSINESS
  • 5.4 PRICING ANALYSIS
     AVERAGE SELLING PRICE TREND, BY REGION (2021–2024)
     AVERAGE SELLING PRICE TREND OF TYPE, BY KEY PLAYERS (2021–2024)
  • 5.5 VALUE CHAIN ANALYSIS
  • 5.6 ECOSYSTEM ANALYSIS
  • 5.7 INVESTMENT AND FUNDING SCENARIO
  • 5.8 TECHNOLOGY ANALYSIS
     KEY TECHNOLOGY
    – Reinforcement Learning
     COMPLEMENTARY TECHNOLOGIES
    – IoT
    – Edge Computing
     ADJACENT TECHNOLOGIES
    – Additive Manufacturing
    – Digital Twin
  • 5.9 PATENT ANALYSIS
  • 5.10 TRADE ANALYSIS
  • 5.11 KEY CONFERENCES AND EVENTS (2025-2026)
  • 5.12 CASE STUDY ANALYSIS
  • 5.13 REGULATORY LANDSCAPE
     Regulatory Bodies, Government Agencies, and Other Organizations
     Key Regulations
  • 5.14 PORTERS FIVE FORCE ANALYSIS
     Threat from New Entrants
     Threat of Substitutes
     Bargaining Power of Suppliers
     Bargaining Power of Buyers
     Intensity of Competitive Rivalry
  • 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA
     Key Stakeholders in Buying Process
     Buying Criteria
  • 5.16 IMPACT OF 2025 US TARIFF- AI IN MANUFACTURING MARKET
     Introduction
     Key Tariff Rates
     Price Impact Analysis
     Key Impact on Various Regions
    – Us
    – Europe
    – Asia Pacific
     Impact on Applications/End-use Verticals
  • 5.17 STRATEGIC ROADMAP FOR AI ADOPTION IN MANUFACTURING (2024–2030)
  • 5.18 EMERGING REGIONAL HOTSPOTS (TIER-2 CITIES, SOUTHEAST ASIA, ETC.)
  • 5.19 WHAT’S NEXT IN AI FOR MANUFACTURING – EXPERT ROUNDTABLE INSIGHTS
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY OFFERING
50
  • 6.1 INTRODUCTION
  • 6.2 HARDWARE
     PROCESSORS
     MEMORY DEVICES
     NETWORK DEVICES
  • 6.3 SOFTWARE
     AI SOLUTIONS
     AI PLATFORMS
  • 6.4 SERVICES
     DEPLOYMENT & INTEGRATION
     SUPPORT & MAINTENANCE
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY TECHNOLOGY
70
  • 7.1 INTRODUCTION
  • 7.2 MACHINE LEARNING
  • 7.3 NATURAL LANGUAGE PROCESSING
  • 7.4 CONTEXT-AWARE COMPUTING
  • 7.5 COMPUTER VISION
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY APPLICATION
90
  • 8.1 INTRODUCTION
  • 8.2 INVENTORY OPTIMIZATION
  • 8.3 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION
  • 8.4 PRODUCTION PLANNING
  • 8.5 FIELD SERVICES
  • 8.6 RECLAMATION
  • 8.7 QUALITY CONTROL
  • 8.8 CYBERSECURITY
  • 8.9 INDUSTRIAL ROBOTS
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY INDUSTRY
120
  • 9.1 INTRODUCTION
  • 9.2 AUTOMOTIVE
  • 9.3 ENERGY & POWER
  • 9.4 PHARMACEUTICALS
  • 9.5 METALS & HEAVY MACHINERY
  • 9.6 SEMICONDUCTOR & ELECTRONICS
  • 9.7 FOOD AND BEVERAGE
  • 9.8 OTHER INDUSTRIES
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY REGION
130
  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
     MACRO-ECONOMIC OUTLOOK
     US
     CANADA
     MEXICO
  • 10.3 EUROPE
     MACRO-ECONOMIC OUTLOOK
     GERMANY
     UK
     FRANCE
     ITALY
     SPAIN
     POLAND
     NORDICS
     REST OF EUROPE
  • 10.4 ASIA PACIFIC
     MACRO-ECONOMIC OUTLOOK
     CHINA
     JAPAN
     INDIA
     SOUTH KOREA
     AUSTRALIA
     INDONESIA
     MALAYSIA
     THAILAND
    – Vietnam
    – Rest of Asia Pacific
  • 10.5 ROW
     MACRO-ECONOMIC OUTLOOK
     MIDDLE EAST
    – Bahrain
    – Kuwait
    – Oman
    – Qatar
    – Saudi Arabia
    – United Arab Emirates (UAE)
    – Rest of Middle East
     AFRICA
    – South Africa
    – Other African Countries
     SOUTH AMERICA
    – Brazil
    – Argentina
    – Rest of South American Countries
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, COMPETITIVE LANDSCAPE
160
  • 11.1 KEY PLAYER STRATEGIES/RIGHT TO WIN
  • 11.2 REVENUE ANALYSIS, 2021–2024
  • 11.3 MARKET SHARE ANALYSIS, 2024
  • 11.4 COMPANY VALUATION AND FINANCIAL METRICS
  • 11.5 PRODUCT/BRAND COMPARISON
  • 11.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
     STARS
     EMERGING LEADERS
     PERVASIVE PLAYERS
     PARTICIPANTS
     COMPANY FOOTPRINT: KEY PLAYERS, 2024
    – Company Footprint
    – Region Footprint
    – Offering Footprint
    – Application Footprint
    – Industry Footprint
  • 11.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
     PROGRESSIVE COMPANIES
     RESPONSIVE COMPANIES
     DYNAMIC COMPANIES
     STARTING BLOCKS
     COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    – Detailed List of Key Startups/SMEs
    – Competitive Benchmarking of Key Startups/SMEs
  • 11.8 COMPETITIVE SITUATION AND TRENDS
ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, COMPANY PROFILES
200
  • 12.1 KEY PLAYERS
     NVIDIA CORPORATION
     IBM
     INTEL CORPORATION
     SIEMENS
     GE VERNOVA
     GOOGLE
     MICROSOFT
     MICRON TECHNOLOGY, INC.
     AMAZON WEB SERVICES, INC. (AWS)
    – Sight Machine
  • 12.2 OTHER PLAYERS
     PROGRESS SOFTWARE CORPORATION (DATARPM)
     ROCKWELL AUTOMATION
     HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
     CISCO SYSTEMS, INC.
     MITSUBISHI ELECTRIC CORPORATION
     ORACLE
     SAP
     UBTECH ROBOTICS CORP LTD
     AQUANT
    – Bright Machines, Inc.
    – ABB
    – Avathon, Inc
    – Dassault Systèmes
    – Honeywell International Inc.
    – Zebra Technologies Corp.


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