The Future-Ready Podcast: Industry & Beyond
Aug 5, 2026 · 19 min · 9 segments
Businesses across industries and regions have already invested in how to collect data, some even hired entire teams to make it more readable without a degree in data science. But it is not helpful to…
Rainer BrehmGuest
Conor PeickHost
Nick FinbergHost
As we're thinking about the scaling of industrial AI and SDA as well, in your research, are you seeing this importance of the execution layer? Is that reflected in investment decisions or how companies are setting their priorities?
So prior, companies were investing in analytics tools, individually in data platforms.
They were hiring data scientists to help contextualize this data so that it can be meaningful to people like you and me that don't deal with disparate data every day.
This is moving into investments in execution platforms, so more at the operational level, MES, maintenance management, like I talked about before.
Yes, SDA software-defined virtual controllers are coming, but some are simply upgrading their hardware to more data-friendly processors that do a better job of pre-processing data before they share it with the rest of the system.
And the job of vendors need to be how we safeguard the investment of our customers.
And that was, for example, a very, very conscious decision what we did on, you know, when we brought our virtual PLC.
So basically, it's our core 71500 PLC core, which we virtualized and put it now on an edge computer.
But the asset of, you know, all the libraries, all the programs, the asset of how an operator, as you said, they may be afraid they cannot operate anymore.
They can operate because it feels the same from their perspective, even in the background, it runs on a data center.
So how we make sure that we take our customers at the hand and go step by step in that direction.
But do a step, next step, and the steps need to build on each other to go in the future, I think is very important.
And we see success coming there because they're digestible steps which customers are willing to go.
As we're thinking about the scaling of industrial AI and SDA as well, in your research, are you seeing this importance of the execution layer? Is that reflected in investment decisions or how companies are setting their priorities?
So prior, companies were investing in analytics tools, individually in data platforms.
They were hiring data scientists to help contextualize this data so that it can be meaningful to people like you and me that don't deal with disparate data every day.
This is moving into investments in execution platforms, so more at the operational level, MES, maintenance management, like I talked about before.
Yes, SDA software-defined virtual controllers are coming, but some are simply upgrading their hardware to more data-friendly processors that do a better job of pre-processing data before they share it with the rest of the system.
And the job of vendors need to be how we safeguard the investment of our customers.
And that was, for example, a very, very conscious decision what we did on, you know, when we brought our virtual PLC.
So basically, it's our core 71500 PLC core, which we virtualized and put it now on an edge computer.
But the asset of, you know, all the libraries, all the programs, the asset of how an operator, as you said, they may be afraid they cannot operate anymore.
They can operate because it feels the same from their perspective, even in the background, it runs on a data center.
So how we make sure that we take our customers at the hand and go step by step in that direction.
But do a step, next step, and the steps need to build on each other to go in the future, I think is very important.
And we see success coming there because they're digestible steps which customers are willing to go.
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