Get Started

Industrial AI will transform manufacturing 

Manufacturers are on the cusp of a new industrial AI revolution characterized by rapid automation and digitization of processes

Industrial AI is still in its infancy. According to a 2023 survey report published by the Manufacturing Leadership Council, 57% of manufacturing companies are currently still in the experimental stages of applying AI—and only 29% have implemented formal corporate AI strategies.  

But these formative years are coming to an end. It’s predicted that by 2030 manufacturing operations will be dominated by AI, with 96% of companies planning to increase AI investments before that time (and almost 10% expecting to more than double their investments), according to the council’s report

A surge in AI capabilities is setting the stage for a new industrial revolution, and industrial AI sits at the center of it all.

Industrial AI describes the use of AI technologies and hyperautomation solutions tailored specifically for industrial uses. It harnesses advanced algorithms, machine learning models, computer vision, and robotics to streamline industrial operations. 

These include:

  • Supply chain management

  • Advanced analytics 

  • Automation in manufacturing environments. 

Manufacturers and other industrial organizations that wish to future-proof their business must be prepared for the changes that will accompany the next stage of industry, dubbed Industry 4.0.

The manufacturing sector is periodically rocked by sudden advances in technology. Steam engines, electrical power, mechanized production—each innovation was a revolution, forever changing industrial capabilities. AI and other emergent digital capabilities are now contributing to the next Industrial Revolution.

This shift is marked by the increasing digitization of the manufacturing sector, propelled by transformative technologies like cloud computing, the internet of things (IoT), and digital analytics. But at the heart of Industry 4.0 lies the integration of artificial intelligence into manufacturing processes. AI allows industrial machines to learn, adapt, and make autonomous decisions, setting the stage for significant growth in terms of productivity, efficiency, and capability.

A surge in AI capabilities is setting the stage for a new industrial revolution, and industrial AI sits at the center of it all.

AI promises significant advantages in manufacturing. Among the most noteworthy are opportunities to:

  • Increase efficiency: AI optimizes production processes, minimizing downtime and maximizing throughput. 

  • Enhance quality control: AI-driven systems can automate quality inspection, ensuring adherence to established standards. 

  • Establish vital integrations: AI-powered systems facilitate seamless integration between machines and control systems, creating an interconnected, responsive, and agile manufacturing ecosystem. 

  • Implement predictive maintenance: AI may be used to analyze equipment data to forecast maintenance needs, reducing unplanned downtime. 

  • Optimize worker safety: AI is effective at monitoring production environments, detecting safety hazards, and preventing accidents. 

  • Improve supply chains: AI enhances supply chain visibility, optimizing inventory management and logistics. 

  • Automate risk and compliance: AI, ensuring adherence to regulatory requirements and mitigating operational risks.  

  • Predict demand: AI analyzes market trends to accurately predict demand fluctuations, for data-backed production planning. 

  • Minimize energy wastage: AI can help optimize energy consumption and identify opportunities for energy savings, promoting sustainable manufacturing practices and environmental responsibility.  

  • Reduce expenses: AI-driven insights promote more efficient resource utilization, minimizing waste and giving organizations the insights they need to accomplish while spending less. 

In other words, Industry 4.0 builds upon its predecessors, leveraging connectivity, data, human-machine interaction, and advanced engineering to drive efficiency, accelerate innovation, and ensure agility in manufacturing processes.

Automation and digitization are quickly becoming competitive differentiators in industrial operations. In 2022, McKinsey reported that companies that implement automation solutions generally see 30%–50% less machine downtime, 10%–30% more throughput, 15%–30% better labor productivity, and as much as 85% more accurate forecasting.

This is driven by three key factors:

1. Increasing need for knowledge automation

As older, more experienced workers retire, younger employees are moving to fill those gaps. Unfortunately, most of this up-and-coming workforce may have been taught technologies and concepts that do not match the reality of many organizations’ workflows and systems. This is creating a generational shift in the manufacturing industry, where more and more organizations are turning towards automated knowledge sharing and other AI systems to provide employees with the institutional knowledge they need. 

2. Larger quantities of data to analyze

Where once it may have been difficult to capture enough data to derive actionable insights, today’s manufacturers find themselves facing the opposite problem: Too much data, and too little ability to analyze it effectively. Priorities are shifting, with mass data collection giving way to a more strategic approach to data management. Given the complexity of many of these unstructured data sets, AI technologies are needed to help businesses locate and apply the most valuable information from among the chaff.

By harnessing the power of AI technologies, manufacturers are poised to unlock new frontiers of efficiency, innovation, and competitiveness, propelling themselves into Industry 4.0 and beyond.

3. Increasing digital transformation among competitors

New technologies are creating an innovation arms race, with competitors rushing to gain the advantage over slow adopters. Manufacturers who fail to embrace AI and digital transformation will not be able to maintain a competitive edge. On the other hand, those who move quickly to incorporate these technologies into industrial processes will be in a better position to lead their markets.

Generative AI plays a pivotal role in manufacturing execution systems, facilitating the creation of product blueprints and instructions based on specified criteria. Through generative design algorithms and optimization techniques, manufacturers streamline product development processes, optimize manufacturing workflows, and enhance product quality and performance. Generative AI empowers manufacturers to explore innovative design alternatives, optimize material utilization, and accelerate product development cycles, thereby fostering agility, innovation, and competitiveness in the manufacturing sector.

By harnessing the power of AI technologies, manufacturers are poised to unlock new frontiers of efficiency, innovation, and competitiveness, propelling themselves into Industry 4.0 and beyond. Yet a warning for those lagging and not as quickly embracing these innovations—they may soon find themselves unable to compete in an increasingly automated and digitized industry.

The future-ready manufacturer 

Learn more