산업용 AI 소프트웨어 시장 : 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, industrial AI software market size in 2026 is estimated at USD 23.52 billion, growing from 2025 value of USD 20 billion with 2031 projections showing USD 52.97 billion, growing at 17.62% CAGR over 2026-2031.

This report is Segmented by Deployment Type (Cloud-Based and On-Premise), End-User Industry (Automotive and Transportation, Retail and CPG, Healthcare and Life Sciences, Aerospace and Defense, and More), Application (Predictive Maintenance, Quality Inspection and Vision, Process Optimization, and More), and Geography.

Global Industrial AI Software Market Trends and Insights

Predictive-maintenance adoption cuts unplanned downtime

Plants now slash maintenance budgets by 25-30% and breakdowns by 70-75% after switching from calendar-based to AI-led routines. Tennessee Valley Authority spared 40,000 customer outages in two months by using AI-driven grid controls, proving that cost avoidance scales well in capital-intensive utilities. Bosch's Ansbach site moved defect detection to edge-based vision AI, keeping latency low and inspectors focused on higher-value tasks. Forward-looking operators view these gains as vital because every hour of unplanned stoppage can cost USD 50,000 or more.

Growing volumes of industrial big-data streams

Single factories now generate terabytes of sensor output per day, creating fertile ground for machine-learning models. Ndustrial processes 100 million data points daily across 122 plants, illustrating why data infrastructure is edging toward cloud-native lakes that feed AI pipelines. Yet inconsistent naming conventions and siloed historians remain bottlenecks, urging CIOs to invest in semantic layers that boost model accuracy and shorten training cycles.

Data-sovereignty and IP-protection concerns

The EU AI Act categorizes many factory-floor algorithms as high-risk, mandating local data retention and audit trails. Multinational manufacturers, therefore, spin up sovereign clouds, AWS earmarked EUR 7.8 billion for such European zones, to meet residency rules while still tapping hyperscale AI services aws.amazon.com. Separate deployments inflate costs, but firms weigh them against the penalties of non-compliance.

Other drivers and restraints analyzed in the detailed report include:

1. National Industry 4.0 incentive programs
2. Generative-AI copilots ease engineering labor shortages
3. Scarcity of OT-AI integration talent

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Cloud-based solutions accounted for 60.58% of the Industrial AI Software market share in 2025 and posted the strongest trajectory at 19.65% CAGR through 2031 as firms consolidate workloads on scalable, pay-as-you-grow platforms. The Industrial AI Software market size for cloud deployments is forecast to reach USD 35.54 billion by 2031, reflecting rising confidence in multi-tenant security models. Hybrid architectures further alleviate sovereignty fears by isolating sensitive datasets on regional nodes while feeding anonymized features to central model training hubs.

On-premise installations remain critical in regulated verticals that demand deterministic latency and strict asset control. Fortune 2000 manufacturers often retain on-site clusters to dodge unpredictable egress fees from cloud activity spikes, yet they increasingly orchestrate these clusters through the same containerized stacks used in the cloud. Consequently, both deployment archetypes now complement rather than cannibalize each other, stimulating continual spending across the Industrial AI Software market.

Complete Report Scope:

• By Deployment Type
  • Cloud-based
  • On-premise
• By End-user Industry
  • Automotive and Transportation
  • Retail and CPG
  • Healthcare and Life Sciences
  • Aerospace and Defense
  • Energy and Utilities
  • Other Industries
• By Application
  • Predictive Maintenance
  • Quality Inspection and Vision
  • Process Optimization
  • Supply-chain and Asset Tracking
  • Safety and Compliance Analytics
• By Geography
  • North America
  • South America
  • Europe
  • Asia-Pacific
  • Middle East and Africa

Geography Analysis

North America contributed 36.45% of the Industrial AI Software market size in 2025, thanks to strong vendor-customer ecosystems and deep cloud penetration. IBM alone booked USD 6 billion in generative-AI orders in 2025 as manufacturers prioritized cognitive upgrades over traditional IT refresh cycles. Microsoft surpassed USD 245 billion in revenue by integrating AI copilots into its software stack, supporting industrial developers with pre-trained models.

Asia-Pacific is the speed leader, expanding at 20.55% CAGR to 2031. Japan's factories pilot AI-augmented robotics that showcase near-zero downtime, while Chinese state programs funnel subsidies into smart manufacturing clusters. Regional AI investments are set to reach USD 3.4 billion in 2025, nearly triple 2024 outlays, and a 160% bump in China alone illustrates policy-driven urgency.

Europe follows close behind, shaped by rigor around data sovereignty. The Industrial AI Software market here pivots on secure data-spaces such as GAIA-X that let suppliers share telemetry without ceding control to platform operators. Middle East, Africa, and South America charts show mixed but rising adoption. Oil-rich Gulf nations adopt AI to optimize refinery throughput, whereas Latin American producers leapfrog legacy MES layers by directly adopting cloud-native AI suites, sidestepping the technical debt faced in mature economies.

1. IBM Corporation
2. Intel Corporation
3. NVIDIA Corporation
4. Microsoft Corporation
5. Siemens AG
6. Oracle Corporation
7. Cisco Systems Inc.
8. Veritone Inc.
9. Advanced Micro Devices
10. Google LLC
11. GE Vernova
12. Honeywell International
13. ABB Ltd.
14. Schneider Electric SE
15. Rockwell Automation
16. Bosch Rexroth AG
17. Amazon Web Services
18. Hitachi Ltd.
19. PTC Inc.
20. AspenTech

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 LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Predictive-maintenance adoption cuts unplanned downtime
  • 4.2.2 Growing volumes of industrial big-data streams
  • 4.2.3 National Industry 4.0 incentive programs
  • 4.2.4 Generative-AI copilots ease engineering labor shortages
  • 4.2.5 Carbon-accounting mandates for Scope-3 emissions
• 4.3 Market Restraints
  • 4.3.1 Data-sovereignty and IP-protection concerns
  • 4.3.2 Scarcity of OT-AI integration talent
  • 4.3.3 Legacy automation infrastructure lock-in
  • 4.3.4 GPU-hardware supply volatility
• 4.4 Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Deployment Type
  • 5.1.1 Cloud-based
  • 5.1.2 On-premise
• 5.2 By End-user Industry
  • 5.2.1 Automotive and Transportation
  • 5.2.2 Retail and CPG
  • 5.2.3 Healthcare and Life Sciences
  • 5.2.4 Aerospace and Defense
  • 5.2.5 Energy and Utilities
  • 5.2.6 Other Industries
• 5.3 By Application
  • 5.3.1 Predictive Maintenance
  • 5.3.2 Quality Inspection and Vision
  • 5.3.3 Process Optimization
  • 5.3.4 Supply-chain and Asset Tracking
  • 5.3.5 Safety and Compliance Analytics
• 5.4 By Geography
  • 5.4.1 North America
  • 5.4.2 South America
  • 5.4.3 Europe
  • 5.4.4 Asia-Pacific
  • 5.4.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
  • 6.4.1 IBM Corporation
  • 6.4.2 Intel Corporation
  • 6.4.3 NVIDIA Corporation
  • 6.4.4 Microsoft Corporation
  • 6.4.5 Siemens AG
  • 6.4.6 Oracle Corporation
  • 6.4.7 Cisco Systems Inc.
  • 6.4.8 Veritone Inc.
  • 6.4.9 Advanced Micro Devices
  • 6.4.10 Google LLC
  • 6.4.11 GE Vernova
  • 6.4.12 Honeywell International
  • 6.4.13 ABB Ltd.
  • 6.4.14 Schneider Electric SE
  • 6.4.15 Rockwell Automation
  • 6.4.16 Bosch Rexroth AG
  • 6.4.17 Amazon Web Services
  • 6.4.18 Hitachi Ltd.
  • 6.4.19 PTC Inc.
  • 6.4.20 AspenTech

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-need Assessment