EPISODE · Feb 18, 2026 · 38 MIN
Beyond the AI Hype: What Actually Works in Manufacturing - with Nick Leeder
from Trend Detection Podcast · host Siemens.FM team
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.What you will learn in this episode:Why many industrial AI initiatives fail to move beyond pilots, despite heavy investment and executive attention.How AI hype and “fear of missing out” often lead companies to start with the technology rather than the business or process problem.Why process maturity, data relevance, and context are essential prerequisites before applying AI at scale.How to identify repeatable, scalable AI use cases—with predictive maintenance highlighted as a strong example.What to measure to prove success, including operational impact, financial value, and real improvements to frontline workers’ day‑to‑day work.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: www.siemens.com/senseye-predictive-maintenanceConnect with Nick on LinkedIn:https://www.linkedin.com/in/redeel/
What this episode covers
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.What you will learn in this episode:Why many industrial AI initiatives fail to move beyond pilots, despite heavy investment and executive attention.How AI hype and “fear of missing out” often lead companies to start with the technology rather than the business or process problem.Why process maturity, data relevance, and context are essential prerequisites before applying AI at scale.How to identify repeatable, scalable AI use cases—with predictive maintenance highlighted as a strong example.What to measure to prove success, including operational impact, financial value, and real improvements to frontline workers’ day‑to‑day work.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: www.siemens.com/senseye-predictive-maintenanceConnect with Nick on LinkedIn:https://www.linkedin.com/in/redeel/
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Beyond the AI Hype: What Actually Works in Manufacturing - with Nick Leeder
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