A 400-page report on the current state of the industrial AI market, including detailed market sizing, forecasts, vendor market shares, key trends, use cases, adoption statistics, and more.
The "Industrial AI Market Report 2025-2030" is part of IoT Analytics' ongoing coverage of smart manufacturing and AI topics. The information presented in this report is based on the results of multiple surveys, secondary research as well as qualitative research i.e., interviews with experts and end users in the field. The document includes definitions for industrial AI and related topics (Edge AI, AI in robotics, Generative AI), market projections, adoption drivers, competitive landscapes, key trends and developments, and case studies.
This report is the third installment of our dedicated research coverage on industrial AI and related topics, including predictive maintenance, machine vision & robotics, digital twin, and edge AI.
PREVIEW
Questions answered:
What is industrial AI (i.e., an industrial AI definition)?
Which technologies are used for implementing industrial AI projects (including hardware and software deep-dive)?
What is the current industrial AI market size and its forecast (by sub-markets, regions, technologies, industries)?
Who are the key industrial AI vendors and what are their market shares?
What are the 50 most common industrial AI use cases?
What is the perspective of industrial AI end users? What are the factors that facilitate or limit adoption?
How are selected manufacturers adopting industrial AI and what are the details of representative case studies?
How do manufacturers adopt generative AI, edge AI and agentic AI?
What are the key trends & challenges in industrial AI space?
PREVIEW
The main purpose of this document is to help our readers understand the current industrial AI landscape by defining, sizing and analyzing the market.
The Industrial AI Market Report 2025-2030
The global industrial AI market, a multi-billion dollar market in 2024, is forecast to experience significant double-digit growth through 2030. This report delivers market data and insights helping decisions makers navigate through the market landscape.
Report highlights:
Market sizing & forecasts: A detailed market model and forecast to 2030, segmented by tech stack (hardware, software, services), AI type, industry, region, and by top five countries.
Competitive landscape: In-depth analysis of the 15 largest vendors with market shares and 30+ upcoming companies.
Use case & adoption analysis: Deep dive into 48 key use cases across 10 categories, enriched with end-user perspectives on adoption drivers and barriers.
Strategic insights: A review of 21 key market trends and 6 challenges shaping the industrial AI space.
Technology deep dives: Dedicated chapters providing in-depth analyses of Generative AI & Agentic AI, Edge AI, and AI in Robotics.
In-depth studies: Features 6 detailed use case studies and 4 deep dives into the AI strategies of leading manufacturers.
The market report comes with the full market model data in EXCEL, a list of 670 industrial AI vendor in EXCEL, and a list of industrial AI projects (only team user and enterprise premium license).
What is industrial AI?
Definition of AI
AI (Artificial Intelligence) is defined as machine driven intelligent behavior that involves the ability to acquire and apply knowledge.
AI consists of an analytics (learning) and an outcome (action/decision/prediction) component:
1. Analytics corresponds to the data management processes and data science algorithms through which the device learns.
2. Outcome corresponds to the intelligent behavior, e.g., generating a decision, a prediction, or triggering an action.
Definition of industrial AI
Industrial AI is defined as the application of AI techniques to data generated by operational technology and engineering systems in asset-heavy sectors, optimizing industrial processes at any stage of the product and asset lifecycle.
Operational technology and engineering systems: Control, monitoring, and design platforms that generate real-time and engineering data about physical assets (e.g., PLC, SCADA networks, sensors, CAD/CAE suites, and PLM tools)
Asset-heavy sectors: Industries whose business relies on extensive physical infrastructure and equipment (e.g., discrete and process manufacturing, energy, chemicals, mining, and transportation)
Industrial processes: Technical workflows that create, move, or sustain physical goods and assets (e.g., product design, manufacturing, maintenance, logistics, field service)
Companies mentioned:
A selection from 670 companies mentioned in the report.
AMD
AWS
Accenture
Alibaba
Capgemini
Dell Technologies
Deloitte
Foxconn
Google Cloud
Infosys
Microsoft
NVIDIA
Siemens
Supermicro
TCS
Table of Contents
1. Executive Summary
List of scope or coverage changes compared to the 2021 Industrial AI Market Report
Chapter overview: Introduction
Understanding AI: Definition and components
Understanding AI: Key types and their differences
Types of ML: Overview
Types of ML: Examples
Categories of AI: Overview
2. Introduction
Types of analytics and role of AI: Overview
Focus of this report: Industrial AI
Understanding AI: Non-industrial vs. industrial AI solutions
General and industrial AI timeline: from 1960 to 2024
Industrial AI interest in context: Global searches for industrial AI
Industrial AI interest in context: Vendors' quotes
Industrial AI interest in context: Users' quotes
Industrial AI interest in context: Role of AI for manufacturers
Case in point: Industrial AI at a large automotive supplier
3. Technology overview
Chapter overview: Technology overview
The industrial AI implementation process - Process overview
The industrial AI implementation process - Topics overview
Deep dive 1: Common frameworks to determine AI business value
Deep Dive 2: AI system requirements
Deep Dive 3: AI chips
Deep Dive 4: Build versus buying AI solutions
Deep Dive 5: Data management
Deep Dive 6: Ingest & prepare data
Deep Dive 7: Develop & train models
Deep Dive 8: ML Ops
4. Market size and outlook
Chapter overview: Market size and outlook
General drivers and inhibitors for the industrial AI market 2025
Industrial AI market: What is included and what is not
Global industrial AI market: Overall
Data in perspective: What the average U.S. manufacturer spends on AI
Global industrial AI market: By tech stack
Global industrial AI market: By AI type
Global industrial AI market: Training by hosting type
Global industrial AI market: Inference by hosting type
Global industrial AI market: By use case
Global industrial AI market: By industry
Discrete manufacturing industrial AI market: By ISIC code
Hybrid manufacturing industrial AI market: By ISIC code
Process manufacturing industrial AI market: By ISIC code
Global extended industrial AI market: By region
East Asia & Pacific industrial AI market: By country
Europe & Central Asia industrial AI market: By country
North America industrial AI market: By country
Middle East & North Africa industrial AI market: By country
Latin America & Caribbean industrial AI market: By country
South Asia industrial AI market: By country
Global industrial AI market: By top 10 countries and industry (2024)
China industrial AI market: Overall
China industrial AI market: By tech stack
China industrial AI market: By industry
China industrial AI market: By use case
USA industrial AI market: Overall
USA industrial AI market: By tech stack
USA industrial AI market: By industry
USA industrial AI market: By use case
Germany industrial AI market: Overall
Germany industrial AI market: By tech stack
Germany industrial AI market: By industry
Germany industrial AI market: By use case
Japan industrial AI market: Overall
Japan industrial AI market: By tech stack
Japan industrial AI market: By industry
Japan industrial AI market: By use case
South Korea industrial AI market: Overall
South Korea industrial AI market: By tech stack
South Korea industrial AI market: By industry
South Korea industrial AI market: By use case
5. Competitive landscape
Chapter overview: Competitive landscape
Company landscape: Vendor classifications
Methodology: How individual companies were analyzed
Example: How this report accounts for NVIDIA 2024 revenues
Company landscape: Company database
The 15 largest industrial AI vendors: Overview
Competitive landscape 2024: Market share overview by tech stack
1. Industrial AI hardware: Processors - Market share
Industrial AI hardware: Processors - NVIDIA
Industrial AI hardware: Computing systems - Market share
2. Industrial AI software: How to think about the comp. landscape
Industrial AI software: Platforms - Market share
Industrial AI software: Platforms - Microsoft
Industrial AI software: Platforms - AWS
Industrial AI software: Platforms - Upcoming companies
Industrial AI software: AI-native Applications - Vision/Inspection
Industrial AI software: AI-native Applications - Maintenance
Industrial AI software: AI-native Applications - Others
Industrial AI software: AI-native Applications - Value prop.
Industrial AI software: AI-native Apps - Value prop.
Industrial AI software: AI-native Applications - Value prop.
3. Industrial AI services: Market share
Industrial AI services: Accenture
Industrial AI services: Accenture - AI agent showcase
Industrial AI services: Capgemini
AI Libraries
6. Use cases
Chapter overview: Use cases
Main industrial AI use cases: Share of industrial AI market 2024
Main industrial AI use cases: Definitions
Use case 1: Automated optical inspection
Use case 1: Automated optical inspection - Case study
Use case 2: Predictive maintenance of single assets
Use case 2: Predictive maintenance of single assets - Case study
Use case 3: Autonomous machines/robots
Use case 3: Autonomous machines/robots - Case study
Use case 4: Cybersecurity threat detection
Use case 5: Predictive maintenance of complete systems/plants
Use case 6: Surveillance and physical threat detection
Use case 6: Surveillance and physical threat detection - Case study
Use case 7: Automated non-optical fault detection
Use case 8: Production optimization
Use case 9: Route optimization and scheduling
Use case 9: Route optimization and scheduling - Case study
Use case 10: Autonomous logistics systems
Use case 10: Autonomous logistics systems (ALSs) - Case study
Other notable case studies
Other notable case studies: Focus - Generative AI
7. Generative AI and Agentic AI
Chapter overview: Generative AI and Agentic AI
This chapter looks at GenAI & agentic AI through 5 lenses
Analysis of 530 GenAI projects: Overview
Analysis of 530 GenAI projects: By Department
Analysis of 530 GenAI projects: By department and activity
Analysis of 530 GenAI projects: By industry
Analysis of 530 GenAI projects: By industry and department
Analysis of 530 GenAI projects: Crossing the chasm
How to monetize GenAI applications
Industrial agentic AI: Overview
Industrial agentic AI: Model context protocol (MCP) - Overview
Industrial agentic AI: Model context protocol (MCP) - Adoption