Artificial Intelligence in Manufacturing Market by Technology (Deep Learning, Machine Learning Platforms, Machine Vision), Application (Cybersecurity, Field Services, Industrial Robots), End-User - Global Forecast 2024-2030

Artificial Intelligence in Manufacturing Market by Technology (Deep Learning, Machine Learning Platforms, Machine Vision), Application (Cybersecurity, Field Services, Industrial Robots), End-User - Global Forecast 2024-2030

The Artificial Intelligence in Manufacturing Market size was estimated at USD 5.74 billion in 2023 and expected to reach USD 7.90 billion in 2024, at a CAGR 39.04% to reach USD 57.75 billion by 2030.

Artificial Intelligence (AI) in the manufacturing market comprises a variety of intelligent technologies, tools, and platforms that integrate advanced capabilities such as machine learning, natural language processing, robotics, and computer vision. These technologies aim to optimize production processes, enhance product quality, reduce operational costs, and improve overall efficiency across industries including automotive, aerospace & defense, electronics & semiconductors, pharmaceuticals, textiles, food & beverages. Several factors influence the growth of AI in manufacturing, including the growing need for automation, rapidly evolving industries, and increasing emphasis on operational efficiency and reducing cost. Additionally, advancements in the Industrial Internet of Things (IIoT), big data analytics (BDA), and cloud computing services have facilitated the seamless integration of AI solutions with traditional manufacturing systems. These novel technologies offer potential opportunities for enhancing supply chain management (SCM), predictive maintenance (PdM), inventory optimization & control (IOC), and material handling (MH), among other core applications. On the other hand, limitations include high upfront investments required for implementing advanced hardware infrastructure suitable for AI tools, and concerns regarding latency-sensitive applications, and limited skilled workforce. This challenges small- and medium-sized enterprises with limited financial resources. However, the growing adoption of AI technology in machinery inspection and predictive maintenance and promising government initiatives & investments for AI in manufacturing creates an opportunity for AI in the manufacturing market to grow in the coming years.

Regional Insights

The adoption of AI in manufacturing is gaining momentum worldwide as industries seek enhanced productivity and reduced operational costs. The Americas, particularly the United States, has been a significant hub for AI adoption in manufacturing. The market has been expanding steadily due to increasing labor costs, a need for efficiency, and a focus on innovation. APAC has seen rapid growth in AI adoption in manufacturing, driven by countries, such as China, Japan, South Korea, and India, as it is focusing on automation and smart manufacturing, leveraging AI for tasks, including robotic assembly, process optimization, and quality control. The governments of China, Japan, Singapore, and India are investing in artificial intelligence and boosting AI in the manufacturing industry for smart factories and Industry 4.0. In the EMEA region, AI in the manufacturing market is growing owing to increasing infrastructure development and chemical production. The European Commission has proposed adopting AI for manufacturing and boosting digital technologies in the sector. In the Middle East and Africa, the manufacturers of oil & gas are adopting AI to streamline their production processes while improving productivity. The global manufacturing industry is poised for unprecedented growth driven by AI advancements as manufacturers and governments navigate the challenges developed nations face and embrace opportunities emerging economies present.

Market Insights

Market Dynamics

The market dynamics represent an ever-changing landscape of the Artificial Intelligence in Manufacturing Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

Market Drivers

• Growing need for automation and rapidly evolving industries
• Evolving IoT technology across manufacturing industries
• Increasing emphasis on operational efficiency and reducing cost

Market Restraints

• High initial investment for installation and implementation of technology

Market Opportunities

• Growing adoption of AI technology in machinery inspection and predictive maintenance
• Promising Government Initiatives & Investments in Developing Nations

Market Challenges

• Concerns regarding latency-sensitive applications and limited skilled workforce

Market Segmentation Analysis

• Technology: Rising adoption of robotic process automation to increase productivity across manufacturing sector
• Application: Increasing need for security and process automation in manufacturing sector
• End-User: Growing demand for AI for propelling innovation and efficiency across energy & utility sector

Market Disruption Analysis

• Porter’s Five Forces Analysis
• Value Chain & Critical Path Analysis
• Pricing Analysis
• Technology Analysis
• Patent Analysis
• Trade Analysis
• Regulatory Framework Analysis

FPNV Positioning Matrix

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Artificial Intelligence in Manufacturing Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Artificial Intelligence in Manufacturing Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments

IFS to acquire Falkonry AI

IFS has acquired Falkonry, Inc., an Industrial AI software company specializing in automated, high-speed data analysis for the manufacturing and defense sectors. The integration of Poka's connected worker technology into IFS Cloud positions IFS to establish Smart Factories of the future, enhancing operational efficiency and productivity.

AI-driven biosimilar manufacturing partnership announced

Sandoz International GmbH and Just-Evotec Biologics, Inc. have partnered to develop and manufacture multiple biosimilars utilizing AI technology. This collaboration gave Sandoz access to AI-driven drug development and continuous manufacturing technology, enabling them to expand their biosimilar pipeline to 24 assets. The primary objective of this partnership is to leverage disruptive technology that offers lower operational costs while still delivering high-quality biosimilars at scale.

AI-based startup helping India's manufacturing prowess raises USD 4.2 million

SwitchOn secured funding of USD 4.2 million from a Singapore-based fund and investors such as Axilor Ventures, pi Ventures, and prominent angels. This investment enabled SwitchOn to strengthen its presence in India, expand internationally with large enterprises, recruit key personnel, and invest in research and development. By improving efficiency and quality control in manufacturing processes, SwitchOn made significant contributions to the industry, driving innovation and success for its clients.

Strategy Analysis & Recommendation

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Artificial Intelligence in Manufacturing Market. This critical assessment involves a thorough analysis of the organization’s resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

Key Company Profiles

The report delves into recent significant developments in the Artificial Intelligence in Manufacturing Market, highlighting leading vendors and their innovative profiles. These include Advanced Micro Devices, Inc., AIBrain Inc., Bright Machines, Inc., Cisco Systems, Inc., ForwardX Technology Co., Ltd., General Electric Company, General Vision Inc., Google, LLC by Alphabet Inc., Graphcore Limited, Hewlett Packard Enterprise Company, Intel Corporation, International Business Machines Corporation, Landing AI, Medtronic PLC, Micron Technology Inc., Microsoft Corporation, Mitsubishi Electric Corporation, Novartis International AG, Nvidia Corporation, Oracle Corporation, Path Robotics, Progress Software Corporation, Rethink Robotics GmbH, Rockwell Automation Inc., SAP SE, Siemens AG, SparkCognition, Inc., UBTECH Robotics, Inc., and Uptake Technologies Inc..

Market Segmentation & Coverage

This research report categorizes the Artificial Intelligence in Manufacturing Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Technology
• Deep Learning
• Machine Learning Platforms
• Machine Vision
• Robotic Processes Automation
• Text Analytics & Natural Processing Language
• Application
• Cybersecurity
• Field Services
• Industrial Robots
• Material Movement
• Predictive Maintenance & Machinery Inspection
• Production Planning
• Quality Control
• Reclamation
• End-User
• Automobile
• Energy & Power
• Food & Beverages
• Heavy Metals & Machine Manufacturing
• Pharmaceuticals
• Semiconductor & Electronics
• Region
• Americas
• Argentina
• Brazil
• Canada
• Mexico
• United States
• California
• Florida
• Illinois
• New York
• Ohio
• Pennsylvania
• Texas
• Asia-Pacific
• Australia
• China
• India
• Indonesia
• Japan
• Malaysia
• Philippines
• Singapore
• South Korea
• Taiwan
• Thailand
• Vietnam
• Europe, Middle East & Africa
• Denmark
• Egypt
• Finland
• France
• Germany
• Israel
• Italy
• Netherlands
• Nigeria
• Norway
• Poland
• Qatar
• Russia
• Saudi Arabia
• South Africa
• Spain
• Sweden
• Switzerland
• Turkey
• United Arab Emirates
• United Kingdom

Please Note: PDF & Excel + Online Access - 1 Year