By Sarah Nicastro, Founder and Editor in Chief, Future of Field Service

When I first spoke with Dave Mackerness for an episode of the podcast in late 2021, Kaer was well into its journey toward fully transitioning to a CaaS (cooling-as-a-service) company.

Fast forward several years, and Kaer has built upon its initial success. The company has expanded beyond its Singapore base into markets including India, Indonesia and Malaysia. Cooling as a service has moved from something that might have seemed like a bold experiment to an increasingly accepted business model. And technology—particularly AI—is creating entirely new opportunities to improve the performance of the assets Kaer operates.

But when I recently reconnected with Dave for a new episode of UNSCRIPTED, one point stood out to me above all others: The most challenging part of as-a-service isn't necessarily changing what you do, it's changing the relationship around what you do.

Kaer has been in the cooling business for roughly 70 years. Its evolution has been gradual: from distributing equipment and technology, to becoming a turnkey contractor and system integrator, to performance-based contracts, and then to CaaS.

As Dave shares, in many respects, the underlying work hasn't fundamentally changed. Kaer still designs cooling systems. It still procures equipment. It still installs and operates those systems. What changed was who owns the responsibility for the outcome—and therefore who owns the decisions about how that outcome is achieved.

In a traditional model, the customer buys the equipment and tells the provider what needs to be done. In an as-a-service model, Kaer takes responsibility for delivering the outcome. The customer doesn't need to care which chiller is running, how the system is optimized, or exactly how maintenance is scheduled, as long as Kaer delivers the agreed result.

That sounds straightforward, right? Theoretically, yes. In reality, not quite. Because the customer has to give up some control, and giving up control requires trust.

Transforming CX: From the Black Box to the Glass Box

Dave described one of the biggest lessons Kaer learned in a particularly memorable way.

Initially, the company thought about its operation as a black box. We'll take care of everything inside. You just care about the outcome.

But customers weren't necessarily comfortable with that. Imagine you've spent years owning and managing a critical piece of infrastructure. Suddenly, a provider tells you, essentially, “Don't worry about what we're doing. We'll take care of it.”

Even if the business case is compelling, that's a difficult psychological transition.

So Kaer changed its approach. Rather than a black box, it created a glass box.

Customers don't control how Kaer operates the system, but they can see what is happening. Through Kaer's customer experience application, customers can access the data and information that demonstrates performance, including historical temperatures, service records, checklists, and other documentation.

With the glass box, transparency replaces control. The customer doesn't need to dictate how the outcome is achieved. But they receive confidence that it is being achieved.

Organizations exploring servitization should pay close attention to this lesson Kaer learned. When you take responsibility for an outcome, you're not simply taking responsibility for the physical work. You're taking responsibility for creating enough confidence that the customer is comfortable allowing you to take control.

The 80/20 Lesson of Servitization Nobody Tells You

Another important consideration for anyone considering servitization is the reflection Dave shared on how Kaer's understanding of its own business changed as the company matured.

As a traditional contractor, the focus was largely on designing and installing equipment and ensuring it operated. With cooling as a service, Dave says, those technical activities represent only about 20% of the work.

The other 80% is managing the customer relationship: ensuring customers are happy, creating confidence, making the service auditable, and building the experience around the outcome. It's easy to focus solely on the commercial and operational aspects of moving to an outcome-based model, but it’s crucial to understand it’s more than that.

It's a customer experience transformation.

When you're selling equipment, the transaction has a relatively clear endpoint. When you're selling an outcome, the relationship is continuous. The customer needs to understand what they're receiving, trust that you're delivering it and have an easy way to engage with the information that matters to them.

As-a-Service Doesn’t Suit All

Another thing I appreciated about Dave's perspective is what he’s learned about what types of businesses “fit” the as-a-service model. He shares that, earlier on, he was of the mindset that anyone and everyone should consider the journey – but over time, he’s realized there are use cases where it simply doesn’t make sense.  In fact, he developed a framework of thinking about whether a product or industry is actually suited to as-a-service that considers two dimensions: complexity and cost.

If something is cheap and simple, customers may choose as-a-service primarily because it provides a better experience or greater convenience. If something is expensive but relatively simple, the economics and cost of capital become more important.

But when you move into products that are both expensive and highly complex, the opportunity becomes much more compelling (provided the provider has the expertise to operate and optimize them effectively). That's where cooling sits. The equipment itself matters, but so does the complexity of operating it well.

As Dave points out, buying the best equipment and installing it perfectly doesn't necessarily result in the best performance. Poor operation can dramatically increase energy consumption and carbon emissions. The ongoing optimization is where significant value can be created.

And that's a critical consideration for any organization thinking about servitization: Where is the expertise that your customer doesn't have, or doesn't want to develop themselves? That may be the real source of your service value.

AI Amplifies As-a-Service Capabilities, But it Can’t Become Another Black Box

Kaer began its AI journey in 2017, developing an AI platform to optimize cooling systems. The impact of AI in CaaS is that Kaer’s highest-performing system isn’t the newest, but the asset for which it has the most data.

The company's first cooling system installed in 2013 remains its highest-performing system, because it has accumulated the most data and that data allows Kaer's models to continually improve how the system is operated and optimized.

That's a powerful concept for asset-intensive industries: The value of an asset doesn't have to deteriorate simply because the asset ages. If data, intelligence, and optimization capabilities improve over time, the operational performance of that asset can actually become better understood and potentially better managed. AI is part of the mechanism through which an outcome is continuously improved.

While AI presents significant opportunity in as-a-service, it must be leveraged responsibly. Just as customers need transparency to trust an as-a-service provider, employees need transparency to trust AI.

Dave described the challenge of introducing AI into mission-critical cooling infrastructure. An AI system might identify an optimization opportunity, but if engineers don't understand or trust why the system is changing something, they may be reluctant to rely on it.

And unlike a consumer using an AI assistant, a cooling system can't simply produce an occasional bad answer. The consequences are far different.

Kaer addressed this by building a second validation layer around its machine learning. The AI can make recommendations, but those recommendations are checked against the physical realities of the system—thermodynamics, pump curves, fan curves ,and the defined service requirements—before action is taken.

That's a useful model for industrial AI more broadly: Intelligence needs guardrails.

The more mission-critical the environment, the more important it becomes to combine AI's ability to learn with domain expertise, physical constraints, safety mechanisms and transparency. The goal isn't simply to make AI autonomous, it's to make AI trustworthy enough to act.

Servitization Creates a Different Kind of Continuous Improvement

Perhaps the biggest lesson from Kaer's journey is that moving to as-a-service removes your endpoint, which changes the incentive structure around improvement.

If you're selling a piece of equipment, there’s a natural end to the transaction. When you're responsible for the outcome, you have a reason to keep asking:

• Can we deliver this more efficiently?
• Can we make the asset perform better?
• Can we reduce energy consumption?
• Can we improve reliability?
• Can we make the customer experience easier?
• Can we use what we've learned from one asset to improve another?

That creates a powerful feedback loop between operations, data, technology, and customer value. And it's one reason Kaer sees the as-a-service model continuing to expand into other industries. Dave points to the growing adoption of models such as lighting-as-a-service, transport-as-a-service, and data-as-a-service.

The Real Transformation is in the Relationship

Kaer's story is obviously about cooling, but the lessons are much broader. Servitization isn't simply about changing the contract from buying something to subscribing to something.

It requires organizations to reconsider:

• What the customer is actually buying
• Who owns the responsibility for the outcome
• How much control the customer needs—and how much they are willing to give up
• How transparency can replace control
• What capabilities the provider must build to continuously improve
• Where data and AI can create new value
• How customers need to be supported through the behavioral shift
• Whether the economics and complexity of the product actually make servitization a good fit

And perhaps most importantly, it requires a different definition of the customer relationship. When you sell a product, you give the customer ownership. When you sell an outcome, you ask them to give you some of that ownership back.

That's a much bigger shift than changing a pricing model; it is a shift in trust.

Kaer's experience suggests that the companies most likely to succeed will be those that understand this nuance. They won't simply tell customers, “Don't worry—we've got it.”

They'll say: “Let us take responsibility for the outcome. And we'll give you enough visibility, transparency, and confidence to know we're doing it well.”