Despite the recent upsurge in manufacturing AI, organizations have barely scratched the surface of what’s possible. Manufacturers that prepare for the imminent embedded AI transformation will be uniquely placed to realize deep improvements to their productivity and profitability.
You’re probably already using embedded AI. For example, when you’re in a Teams meeting and the kids are having a spirited lightsaber battle behind you, AI-powered backgrounds and noise reduction can edit out their leaps and whooshes in favor of a professional-looking office setting and clean meeting audio.
Soon, employees at all levels will benefit from more effective AI-enabled hardware and software, harnessing new efficiencies in smartphones, laptops, operating systems, robots, wearables, and other tools.
The Current Condition
Over 90% of manufacturing companies have already launched pilot projects in AI, and 66% rely on AI in their day-to-day operations. In fact, for every dollar spent on AI, manufacturers see $3.31 in returns. The benefits extend to all business areas, enhancing inventory management, product development, and a shopping list of other functions. AI helps reduce costs, improve product quality, and shorten lead times.
For example, BMW created an AI-supported digital twin of a key facility, simulating production and improving planning. A plastics manufacturer used AI vision to identify and eliminate defects and waste, optimizing production. Through use cases like this (and hundreds more), AI is expected to contribute over $15 trillion to manufacturing by 2025, with hundreds of companies already reporting a 50% reduction in lead times, plus significant cost reductions and productivity improvements.
The Future Condition
AI-integrated OS platforms and next-gen chipsets from makers like AMD and Qualcomm are setting up to deliver powerful AI toolsets onboard laptops, tablets, and phones—instead of via resource-intensive cloud applications. By bringing sophisticated AI and compute technology to the point of use, front-line workers, engineers, and managers will leverage faster insights and more powerful, efficient devices.
Organizations as a whole will enjoy better bandwidth, lower network traffic, and improved compliance with security and privacy requirements. Ultimately, embedded AI will empower teams to design and build higher quality products, with shorter design lifecycles and production lead times, bringing better products to market, faster and more cost effectively.
Engineers
New embedded AI solutions in GPU-enabled engineering laptops will automate routine CAD tasks, analyze design requirements, suggest improvements, and simulate new products before they’re built. One engineering team used AI-driven edge devices to create a real-time object-tracking application. This (normally) processor-heavy task was rendered energy efficient thanks to an embedded AI chipset.
Operators
The National Association of Manufacturers’ Gardner Carrick says AI helps shop floor employees do their jobs better, provides them with more powerful tools, and ultimately increases the value-add of their jobs. In one example, Siemens implemented an AI system running on Microsoft Azure to project a laser grid that helps employees place fiberglass layers on wind-turbine blades with a minimal degree of error.
Managers
Managers will use embedded AI to drive process improvements across inventory management, hiring, scheduling, and dozens of other job functions. For instance, managers at sprinkler system manufacturer Hunter Industries used point-of-use AI to move training and guidance directly into job tasks, significantly reducing their onboarding time and improving employee performance.
How to Get There
It’s mission critical for today’s manufacturing organizations to invest in next-gen embedded AI devices and platforms. Only through ensuring AI readiness will businesses attract and retain top talent and continue to innovate and drive productivity. Explore Connection’s AI services and digital workspace solutions to start leveraging AI.
Ryan Spurr
Ryan Spurr is the Director of Manufacturing Strategy at Connection with 20+ years of experience in manufacturing, information technology, and portfolio leadership. He leads the Connection Manufacturing Practice, go-to-market strategy, client engagement, and advisory services focusing on operational technology (OT) and information technology that make manufacturers more digitally excellent.
