Agentic AI and the Future of Asset Lifecycle Management w/ Kendra DeKeyrel

The Manufacturing Executive · 19 Aug 2025 · Episode 271

AI in practice: 8 real uses of AI described

What this episode covers

Kendra DeKeyrel, Vice President of Asset Lifecycle Management Products and Engineering at IBM, discusses the evolution of AI in manufacturing, moving from simple visual inspection to autonomous 'agentic' workflows. She highlights practical applications like computer vision for defect detection and AI-optimized field service, citing a case study with Shioda Technology that reduced repair times by 31%. DeKeyrel emphasizes that data quality is the primary barrier to adoption and outlines how chaining AI agents can automate complex maintenance and scheduling tasks.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

ManufacturingIBM computer vision models (via IBM Worker Studio)

AI models trained on a single image of a defect detect anomalies in real-time on the manufacturing line, enabling easy proof-of-concept testing with iPhone cameras.

“But now the AI understands what good looks like by one image, it can detect anything bad with just that one image, and you upload an image, and it understands it. And it's just, it's so easy to use. We've got people putting their iPhone cameras up on the manufacturing line to get started with POCs…”

Kendra DeKeyrel · Hear it at 2:28

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Customer supportIBM Watsonx Code Assistant

IBM product managers and developers use AI to augment their workflow by generating better code and test cases, improving internal development efficiency.

“Even internally, we're using AI a lot internally to help every one of our job functions be better, even on my product managers and my developers are using AI to augment how we're doing market research or competitive research or developing better code or better test cases…”

Kendra DeKeyrel · Hear it at 21:41

Mentioned

Companies
IBM, Boston Dynamics, Shioda Technology, Guerrilla 76
Products
IBM Maximo Application Suite, IBM Worker Studio

Other shows on the same ground, closest first.

  • Manufacturing Happy Hour · 24m

    240: How AI Agents are Revolutionizing Safety and Operations in Manufacturing with Dunchadhn Lyons of Spot AI

    Dunchadhn Lyons, Director of Engineering at Spot AI, explains how the company uses existing IP cameras and AI agents to monitor manufacturing safety and operations in real time. He details a case study where a safety manager reduced incidents by 40% by automating the review of 16,000 hours of footage, allowing her to focus on targeted training. Lyons also describes how these AI teammates preserve tribal knowledge from retiring workers and help clothing manufacturers avoid millions in downtime by detecting operational bottlenecks before they cause full stops.

  • EMS@C-LEVEL · 26m

    Revolutionizing Inspection with AI: Loopr.ai Founder & CEO Priyansha Bagaria on EMS@C-Level

    Priyansha Bagaria, founder and CEO of Loopr.ai, explains how her company uses AI-powered computer vision to automate quality inspection in aerospace, automotive, and general manufacturing. She details the deployment of their software applications, IQ Inspect for defect identification and IQ Verify for assembly verification, which are hardware-agnostic and integrate with existing camera infrastructure. Bagaria highlights key industry pain points, including the high cost of quality, labor shortages, and the loss of institutional knowledge as experienced workers retire, arguing that AI provides the consistency and scalability that human inspection cannot. She also discusses Loopr's strategic partnership with Microsoft and the importance of starting with high-value pilot projects to demonstrate clear ROI before scaling across factory floors.

  • Manufacturing Happy Hour · 36m

    241: How NVIDIA and AI Agents Are Transforming Industrial Automation with Alvin Clark

    Alvin Clark, Senior AI Engineer at NVIDIA, explains how AI agents are transforming industrial automation by moving beyond simple error detection to real-time failure analysis and SOP monitoring. He details the NVIDIA Metropolis platform, which enables developers to build visual AI agents using tools like DeepStream and TensorRT, and highlights use cases from partners like Pegatron, Siemens, and DeepHow. Clark emphasizes that these agents address critical industry headwinds, including labor shortages and the loss of tribal knowledge, by providing multimodal assistance to operators and capturing institutional expertise.

  • EMS@C-LEVEL · 7m

    Electronica 24: Peter Gutschi on How AI is Shaping the Future of Manufacturing

    Peter Gutschi, a consultant supporting companies like ESCATEC and startups, explains how AI is moving beyond hype to drive real efficiency in manufacturing, from shop floor quality management to supply chain planning. He highlights specific technologies such as Luminovo's platform for calculating CO2 footprints and Cybord's component inspection tools, which handle data volumes impossible for humans to manage in real time. Gutschi argues that this enhanced visibility allows EMS providers to accurately commit to delivery dates and prevent the inventory overhangs seen in past crises like the 2000 tech wreck.

  • IoT For All Podcast · 26m

    AI’s Role in the Future of Asset Management and Field Work | IBM's Joe Berti

    Joe Berti, Vice President of AI Applications at IBM, discusses how AI and IoT are transforming asset management and field work in heavy industries. He explains that IBM's Maximo and Tariga platforms integrate IoT data with AI to enable predictive maintenance, allowing technicians to use mobile tools for remote collaboration and part identification. Berti highlights the shift from reactive repairs to predictive analytics using anomaly detection, computer vision, and digital twins, while addressing the skills gap between retiring experts and new workers. He also covers the role of 5G in enabling indoor wireless sensor networks and the importance of ethical AI in worker safety applications.

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by The Manufacturing Executive. The episode itself belongs to its publisher.