UNSCRIPTED - EPISODE 382 • DIGITAL TRANSFORMATION
Ali Bigdeli, Professor of Industrial Service Innovation at Aston Business School and Co-Director of the Advanced Services Group, joins Sarah Nicastro to explore how industrial AI is reshaping the conditions for outcome-based services and why now is the moment to act.
For years, the concept of outcome-based services has been genuinely compelling in theory and genuinely difficult in practice. The idea of guaranteeing a result rather than billing time and materials asks a lot of a manufacturer: visibility into how your products actually perform in the customer's environment, the ability to act on that data at scale, and enough trust in the relationship to share the upside and the downside alike. For many organizations, that combination of factors was just out of reach.
What Ali Bigdeli argues, convincingly and from fifteen years of working with manufacturers across healthcare, defense, food and beverage, and beyond, is that the conditions have shifted. The gap between what customers want and what providers can realistically deliver is narrowing. And industrial AI is a big part of why.
What Servitization Actually Means
Terminology is a persistent problem in this space. Ali is direct about it: servitization and outcome-based services are not the same thing, and the conflation causes confusion that slows organizations down.
Servitization, as the Advanced Services Group defines it, is the wider organizational transformation. The journey a manufacturer takes from competing on products alone to competing through services. That journey runs through three levels: base services (providing the product), intermediate services (break-fix and performance advisory), and advanced services, where the focus shifts entirely to the outcome the customer is trying to achieve.
The classic example is Rolls-Royce's "power by the hour" model. The airline doesn't buy an engine; it buys the thrust it needs to move passengers from A to B. That same logic now applies across sectors: lighting as a service, comfort as a service, guaranteed uptime for critical infrastructure.
The distinction matters because it changes what you're measuring, what you're responsible for, and what your relationship with the customer actually looks like.
The Gap Between The Provider and Customer Is Closing
One of the most striking things Ali observed at Field Service Next Europe was how much closer the two sides of this relationship have come. Customer requirements and what providers can actually deliver are closer than they've ever been, and technology is a significant part of that.
For a long time, manufacturers had the ambition but not the visibility. You trusted your product, but you didn't know how it was being used in a customer's operation. Without that visibility, guaranteeing an outcome felt like writing a blank check.
That's changing. Connected assets, real-time data, and the ability to analyze that data at scale are giving providers something they've rarely had: a genuine window into how their product performs in the field. And where that visibility exists, the conversation between provider and customer shifts. It stops feeling like a supplier relationship and starts feeling like a partnership.
Ali frames this as the defining change: "I think we are moving, the mindset is moving from 'we provide you with this asset' into 'we are becoming your partner in delivering what success means for you.'"
What AI Actually Changes
This is where the conversation gets specific. The question Ali asks isn't whether AI can cut costs. It's whether AI can reduce the uncertainty that has historically made outcome-based contracts feel too risky to offer.
The answer, increasingly, is yes. Industrial AI, particularly agentic AI that can process historical data, predict failures, and coordinate responses, gives providers something close to what they need to make a guarantee with real confidence. You can understand how a product is performing in conditions you've never directly observed. You can predict the likelihood of failure before it happens. You can connect that insight to coordinated field service action, so when someone does need to go on site, they know exactly why, they have the right parts, and they're not wasting time.
What that means for outcome-based services specifically is a reduction in the risk calculus that has held organizations back. The hesitation isn't usually about the product. Most manufacturers trust what they build. It's about the unknowns in the customer's environment. AI narrows those unknowns.
None of which means the technology is the whole story. Ali is emphatic about that. "Unless we have the right business models, the right attitude towards change in the organization, the soft aspects, which are more important for me personally as a researcher, it's not going to work." The technology creates the conditions. It doesn't do the transformation on its own.
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