Uploaded August 2026 | Updated September 2026, 2 weeks ago
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.
In this episode of the Trend Detection Podcast, we're joined by James Loach, Head of Research for Senseye Predictive Maintenance at Siemens, to explore what industrial AI means in practice and how it is changing the future of maintenance.
James explains how statistical systems, machine learning and generative AI can work together to monitor assets at scale, investigate potential problems and provide more prescriptive guidance to maintenance teams.
He also discusses why machine context, maintenance history and human expertise will become increasingly important as AI models grow more capable.
In this episode, you’ll learn:
•
What industrial AI means beyond the marketing terminology
•
How machine learning and generative AI work together at scale
•
Why context is critical for improving AI-generated insights
•
How agentic AI could support more prescriptive maintenance decisions
•
Why the future of maintenance could become increasingly autonomous
You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: siemens.com/senseye-predictive-maintenance (siemens.com/senseye-predictive-maintenance)
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.
In this episode of the Trend Detection Podcast, we're joined by James Loach, Head of Research for Senseye Predictive Maintenance at Siemens, to explore what industrial AI means in practice and how it is changing the future of maintenance.
James explains how statistical systems, machine learning and generative AI can work together to monitor assets at scale, investigate potential problems and provide more prescriptive guidance to maintenance teams.
He also discusses why machine context, maintenance history and human expertise will become increasingly important as AI models grow more capable.
In this episode, you’ll learn:
•
What industrial AI means beyond the marketing terminology
•
How machine learning and generative AI work together at scale
•
Why context is critical for improving AI-generated insights
•
How agentic AI could support more prescriptive maintenance decisions
•
Why the future of maintenance could become increasingly autonomous
You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: siemens.com/senseye-predictive-maintenance (siemens.com/senseye-predictive-maintenance)
