Uploaded August 2026 | Updated September 2026, 2 weeks ago
Warehouse automation can increase throughput while quietly creating a new failure point: maintenance that has not kept pace.
When critical assets fail, resilience becomes downtime, lost service and lost revenue.
My guest is Asim Akram, CEO of MultiSensor AI. His work sits at the intersection of asset monitoring, predictive maintenance, AI and high-throughput operations, and this discussion focuses on a problem that is easy to overlook: warehouses, fulfilment centres and logistics operations are becoming more automated, while the maintenance processes protecting conveyors, motors, chillers and electrical systems often remain periodic and manual.
That matters because the operating environment is getting less forgiving. Labour constraints make skilled inspection harder to scale. Throughput expectations keep rising. And increasingly automated facilities depend on a physical layer that cannot simply be assumed to work. Asim also makes the point that warehouse downtime can cost thousands to tens of thousands of dollars per hour, before you add customer loss or reputational damage.
A few things changed my thinking. First, degradation is gradual but failure can happen in one shot — which is exactly why periodic inspection can miss emerging problems. Second, more automation does not remove operational dependency; it can increase it. And third, AI-based detection is only useful if people trust the signal enough to act. That turns predictive maintenance from an engineering issue into a decision-making and business continuity issue.
This is for supply chain, logistics, warehousing, manufacturing, operations and risk leaders responsible for keeping high-throughput systems running.
If you are dealing with this on the ground, I’d like to hear where you see the biggest gap between automation and maintenance.
Podcast website: resilientsupplychainpodcast.com
Subscribe for more conversations on supply chain resilience, operational risk, AI and business continuity.
Follow the podcast wherever you listen.
Timestamps / Chapters:
00:00 Manual Maintenance Trap
00:48 Welcome and Episode Setup
01:43 What MultiSensor AI Does
04:07 Inside the Four Walls Risk
07:14 Automation and Data Center Dependencies
12:07 Why Preventive Maintenance Falls Short
15:25 Setting Thresholds and Early Detection
19:32 Trusting AI and Maintenance as Continuity
25:43 Future Resilience and Wrap Up
Warehouse automation can increase throughput while quietly creating a new failure point: maintenance that has not kept pace.
When critical assets fail, resilience becomes downtime, lost service and lost revenue.
My guest is Asim Akram, CEO of MultiSensor AI. His work sits at the intersection of asset monitoring, predictive maintenance, AI and high-throughput operations, and this discussion focuses on a problem that is easy to overlook: warehouses, fulfilment centres and logistics operations are becoming more automated, while the maintenance processes protecting conveyors, motors, chillers and electrical systems often remain periodic and manual.
That matters because the operating environment is getting less forgiving. Labour constraints make skilled inspection harder to scale. Throughput expectations keep rising. And increasingly automated facilities depend on a physical layer that cannot simply be assumed to work. Asim also makes the point that warehouse downtime can cost thousands to tens of thousands of dollars per hour, before you add customer loss or reputational damage.
A few things changed my thinking. First, degradation is gradual but failure can happen in one shot — which is exactly why periodic inspection can miss emerging problems. Second, more automation does not remove operational dependency; it can increase it. And third, AI-based detection is only useful if people trust the signal enough to act. That turns predictive maintenance from an engineering issue into a decision-making and business continuity issue.
This is for supply chain, logistics, warehousing, manufacturing, operations and risk leaders responsible for keeping high-throughput systems running.
If you are dealing with this on the ground, I’d like to hear where you see the biggest gap between automation and maintenance.
Podcast website: resilientsupplychainpodcast.com
Subscribe for more conversations on supply chain resilience, operational risk, AI and business continuity.
Follow the podcast wherever you listen.
Timestamps / Chapters:
00:00 Manual Maintenance Trap
00:48 Welcome and Episode Setup
01:43 What MultiSensor AI Does
04:07 Inside the Four Walls Risk
07:14 Automation and Data Center Dependencies
12:07 Why Preventive Maintenance Falls Short
15:25 Setting Thresholds and Early Detection
19:32 Trusting AI and Maintenance as Continuity
25:43 Future Resilience and Wrap Up
