Artificial Intelligence in Manufacturing Market In-Depth Analysis, Growth, Future Opportunities and Forecast (2020-2025)

The hardware segment will continue dominating the artificial intelligence in manufacturing market on account of the increasing demand for AI processors across several industry verticals. Considering the AI processors, the GPUs account for over 45% of the market share pertaining to increasing demand for processing visual content in the manufacturing sector. Moreover, GPUs possess higher processing power as compared to CPUs and are optimized for processing intense graphical contents. Presently the hardware segment holds over 57% of AI in the manufacturing market share.

The growing proliferation of computer vision technology has been driven by the rising need for quality inspection coupled with deployment of automation technologies in the manufacturing industries. The technology helps to achieve high level of precision in every product despite the super paced production lines. The widespread adoption of IoT systems should encourage the use of computer vision technology further driving the segmental growth. The computer vision segment is projected to achieve a substantial CAGR of over 45% during the projected time period.

Get sample copy of this research report @

Rising venture capital investment coupled with surge in the availability of digital data have been propelling artificial intelligence in manufacturing market outlook. The increasing involvement of prominent technology players has been supporting the use of AI-enabled systems in the manufacturing sector.

It is presumed that by 2020 over 1.7 megabytes of new data will be generated every second paving ways for digitalization of the manufacturing sector. Sharp rise in data volumes should encourage the adoption of advanced data analytics solutions and AI technologies among the manufacturers. The AI in Manufacturing Market size projected to surpass USD 16 billion by 2025.

Introduction of industry 4.0 trends has enabled manufacturers to reduce their operational costs and enhance productivity. Thereby, rapid proliferation of industry 4.0 technologies will drive the artificial intelligence in manufacturing market trends over the study timeframe. The use of advanced technologies and data analytics has not only helped improving the process efficiency but has also eased of estimating the customer requirements in real-time, thus creating a balance in supply and demand of the products.

The benefits of cost-effectivity and reliable operation favored by the implementation of technology in the manufacturing processes will boost the industry growth.

Rising pressure to increase productivity of the manufacturing facilities has led toward several instances of machine downtime, which indirectly affects the productivity itself. Thus, maintenance becomes a key parameter to eliminate the chances of machine downtime further enhancing the production value and offering major cost savings benefits. The shocking records from the International Society of Automation (ISA) states that over USD 647 billion is lost annually from the machine downtime.

Growing occurrences of equipment downtime will result in increasing penetration of the technology over the forecast timeline. The technology helps inspecting the equipment status without the need of periodical shutdowns, hence improving the efficiency. Artificial intelligence in manufacturing market size from the predictive maintenance and machine inspection application will display immense traction growing at over 44% CAGR through 2025.

The Asia Pacific artificial intelligence in manufacturing market share is driven by the extensive proliferation of advanced technologies in the manufacturing sector. Increasing adoption of technologies robotics, industrial IoT and big data coupled with cheap availability of labor has led toward the robust development of the manufacturing sector.

Request for customization @

 The widespread adoption of industry 4.0 technologies in the countries including China, Japan, and South Korea will promote the use of AI solutions. In 2018, the Asia Pacific region accounted for over 44% of the global artificial intelligence in manufacturing market share.

Table of Contents (ToC) of the report:

Chapter 1. Methodology & Scope

1.1. Methodology

1.1.1. Initial data exploration

1.1.2. Statistical model and forecast

1.1.3. Industry insights and validation

1.1.4. Scope

1.1.5. Definitions

1.1.6. Methodology & forecast parameters

1.2. Data sources

1.2.1. Secondary Paid Public

1.2.2. Primary

Chapter 2. Executive Summary

2.1. Artificial Intelligence in manufacturing Market 360º synopsis, 2016 - 2025

2.2. Business trends

2.3. Regional trends

2.4. Component trends

2.4.1. Hardware trends Processors trend

2.4.2. Software trends

2.4.3. Service trends

2.5. Technology trends

2.6. Application trends

2.7. End-use trends

Chapter 3. Artificial Intelligence in Manufacturing Market Insights

3.1. Introduction

3.2. Industry segmentation

3.3. Industry landscape, 2016 – 2025

3.3.1. AI processors market

3.3.2. AI in manufacturing market

3.4. Industry ecosystem analysis

3.5. AI in manufacturing evolution

3.6. Regulatory landscape

3.6.1. Health Insurance Portability and Accountability Act (HIPAA)

3.6.2. Payment Card Industry Data Security Standard (PCI DSS)

3.6.3. North American Electric Reliability Corp. (NERC) standards

3.6.4. Federal Information Security Management Act (FISMA)

3.6.5. The Gramm-Leach-Bliley Act (GLB) Act of 1999

3.6.6. The Sarbanes-Oxley Act of 2022

3.7. Technology and innovation landscape

3.8. Use cases

3.8.1. Outside the factory Engineering Supply chain management

3.8.2. Inside the factory Production Maintanence Quality Logistics

3.9. Price comparision of the AI processors

3.10. Industry impact forces

3.10.1. Growth drivers Increasing venture capiatal investemnt in AI Exponential growth in digital data Rapid adoption of industry revolution 4.0 Changing customer behavior and demand

3.10.2. Industry pitfalls & challenges Latency sensitive applications Lack of skilled professtionals

3.11. Growth potential analysis

3.12. Porter’s analysis

3.13. PESTEL analysis

Browse complete Table of Contents (ToC) of this research report @