NTT DATA and Hyster-Yale Materials Handling Announce Breakthrough Physical AI Solution in Manufacturing

Key Terms

physical ai technical

Physical AI combines artificial intelligence with physical devices or environments, enabling machines to interact with and adapt to the real world in a human-like way. It matters to investors because it can lead to smarter robots, autonomous vehicles, or advanced sensors that improve efficiency and open new markets, potentially creating significant business opportunities and competitive advantages.

edge ai technical

Edge AI refers to artificial intelligence systems that process data directly on local devices or nearby servers rather than sending information to distant data centers. This allows for faster decision-making and real-time responses, similar to how a home security camera can instantly detect motion without needing to connect to a remote server. For investors, edge AI represents a growing trend toward more efficient, responsive technology that can create new opportunities across various industries.

edge computing technical

Edge computing is a technology that processes data close to where it is generated, such as sensors or devices, rather than sending it all to a distant central location. This allows for faster decision-making and reduces delays, much like having a local office handle urgent matters instead of waiting for instructions from a main headquarters. For investors, it signifies improved efficiency and real-time insights, which can enhance the performance of technology-dependent industries.

operational technology technical

Operational technology is the physical equipment and specialized software that directly control machines, sensors and processes in factories, energy grids, transportation systems and buildings — think of it as a facility’s control panel and nervous system. Investors care because problems, upgrades or cyberattacks in this area can halt production, raise costs, require large capital spending, or trigger safety and regulatory issues that affect revenue and valuation.

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• Physical AI embeds intelligence into quality assurance for critical assembly operations
• When compared to legacy techniques, physical AI cuts deployment timelines from months to weeks
• Co-innovation improves product reliability and maintains quality standards at scale

LONDON--(BUSINESS WIRE)-- NTT DATA, a global leader in AI, digital business and technology services, and Hyster-Yale Materials Handling, Inc. (HYMH), the manufacturer of Hyster® and Yale® lift trucks, today announced a breakthrough application of physical AI that embeds intelligence directly into manufacturing processes. This approach leverages sensor data to enable machines and systems to perceive, understand and act in real time within real-world operations.

Bringing this capability into practice introduces AI-driven quality assurance directly into HYMH’s manufacturing operations. This co-developed approach represents a first-of-its-kind use case of how physical AI can be applied in an industrial assembly environment by embedding intelligence into production workflows, helping to safeguard that products are built to consistently high standards.

NTT DATA designed and developed the solution at HYMH’s manufacturing facility in Berea, KY, integrating vision sensors, edge AI that processes data on-site and advanced analytics into a critical assembly workflow.

Together with partner Archetype AI, NTT DATA, in collaboration with HYMH, adapted a physical AI model that analyzes assembly activity against expected production steps, validating that all parts are installed and that assembly stages are completed, flagging deviations before the product moves to the next stage. By validating quality throughout the assembly process, the solution helps identify and address potential issues before products leave the factory floor.

This initiative demonstrates a step-change in how AI can be applied in manufacturing environments. Combined with edge computing, the solution can run locally so all processing happens on-site, enabling faster rollout and quicker time-to-value. Early results showed that physical AI cuts deployment timelines from months to weeks when compared with legacy techniques, accelerating adoption and iteration across manufacturing operations.

“Our confidence in physical AI continues to grow, and we’re starting to see the countless benefits that AI can bring to our global manufacturing operations,” said Barbara Binda, Director of Global Manufacturing Innovation, Hyster-Yale Materials Handling. “Working with NTT DATA allows us to leverage how physical AI can help our production teams maintain high-quality standards and deliver the most reliable products to our clients.”

"This deployment shows what physical AI looks like in real production environments, not as a concept, but with tangible impact on the factory floor,” said Shahid Ahmed, Global Head of Edge Services, NTT DATA, Inc. "By combining real production data with physical AI models at the edge, we’re helping leading manufacturers like HYMH deliver high-quality products, support frontline workers and apply AI in ways that deliver real-world outcomes.”

As manufacturers accelerate automation, demand is rising for physical AI that can operate safely in complex environments, driving efficiency, quality and resilience. NTT DATA is uniquely positioned to deliver this capability at scale, combining industry expertise with end-to-end services to integrate AI across IT and operational technology environments, enabling intelligent, data-driven operations.

Today’s news builds on a longstanding collaborative relationship between NTT DATA and HYMH. Together, the companies are advancing more adaptive and intelligent manufacturing processes and exploring how physical AI can be scaled to drive repeatable, high-quality production outcomes.

About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. Our consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 70 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D. Visit us at nttdata.com

About Hyster‑Yale Materials Handling

Hyster-Yale Materials Handling, Inc., designs, engineers, manufactures, sells and services a comprehensive line of lift trucks, parts and technology and energy solutions marketed globally primarily under the Hyster^®, Yale^®, Nuvera® and Maximal® brand names. The company’s subsidiary, Bolzoni S.p.A., is a leading worldwide producer of attachments, forks, masts and lift tables marketed under the Bolzoni^®, Auramo^® and Meyer^® brand names.

Hyster-Yale Materials Handling is a wholly owned subsidiary of Hyster-Yale, Inc. (NYSE: HY).

View source version on businesswire.com: https://www.businesswire.com/news/home/20260707774797/en/

Lori Bosio | lori.bosio@nttdata.com

Source: NTT DATA