🎧 Listen to the full episode here.
There are obvious reasons to go early. You get the latest technology, you learn how it works before everyone else, and you may benefit from improvements that come with being an early adopter. But you also have to accept the other side of that decision.
The infrastructure may not be as convenient everywhere. The technology may improve significantly after you have bought it and technically, you are making the decision with less information than someone who waits 2-3 years and sees where the market goes.
I like to think of it a bit like buying an electric car. The other day, my family was discussing whether we should buy an electric car, and the conversation quickly turned into a debate. Should we actually buy one now, or would it make more sense to wait? Should we pay for it outright, or use one of the leasing-to-buy programs to lessen upfront risk? And, perhaps most importantly, are we buying a technology that genuinely makes sense for us, or are we paying a premium to be part of something that is still developing?
That tension is at the heart of this episode on the Open Podcast, where Sander Mangel and Katy Wilson discuss the opportunities and risks of adopting emerging technology before it becomes mainstream in your market. The conversation focuses largely on new ecommerce platforms and digital technologies, but the underlying question feels more important in a time when AI is accelerating the pace at which new technology enters the market.
When does adopting early create a genuine advantage, and when are you simply taking on risk before you need to?
Being early means investing before there is a return
As Sander puts it, “I don't think it's as simple as early adoption always is good or wait until things are more stable. I think there's a real balance to be found there.”
That balance is important because there is a tendency to treat adoption itself as a strategic decision. But in reality, the strategic decision is whether this particular technology, at this particular moment, makes sense for your business and your clients.
Sander and Katy discuss the distinction between adopting a technology and actually being capable of delivering it. For an agency, the first step may be relatively straightforward with certification, training, and getting familiar with the product. The real investment starts afterwards.A developer may need to learn how to build on a platform, but that developer is not the only person who needs to understand it. The sales team needs to know what can realistically be sold. Solution architects need to understand what is possible and where the limitations are. Project managers need to know what risks to account for. The agency may need to rethink internal processes and educate clients about a different way of working.
Sander describes certification as “a first step, but probably the easiest step.”
The first real test is what happens when that technology becomes part of a live project. Suddenly, questions that seemed theoretical become very practical. How long does a particular implementation really take? Which parts require custom development? What happens when the documentation does not cover the problem encountered?
This is also where the financial reality of early adoption becomes clearer. Katy makes the point that the first projects should be viewed differently from mature projects: “You have to view those initial projects as their investments. They're not profit centers.”
This means recognizing that the first implementation is doing more than delivering a client outcome. It is building the knowledge, processes, and reusable expertise that should make the next project more efficient.
This is particularly relevant for AI, where the technology itself is changing so quickly. An agency experimenting with a new AI may not see a direct commercial return, but it can start to understand where the technology genuinely adds value, areas that it introduces complexity, and what changes need to happen before it can be used effectively at scale.
What is the risk of adopting emerging tech early?
It is very easy to confuse momentum with strategic fit when it comes to emerging tech. For example, when everyone today is talking about an AI-first approach, the safest feeling can be to adopt it so that you don’t feel left behind. But early adoption only makes sense when there is a reason for being early.
Katy puts it bluntly: “It can't just be a shiny object decision. It has got to be strategic.”
For an agency, that means looking beyond what the technology can do and asking what role it should play in the business. You need to ask questions like what problems it actually solves for clients or if adopting early means giving the team another technology to maintain. Most importantly, can the vendor itself support the investment? Before committing resources, it is worth understanding whether the platform has a real plan for the market. Sander shares how he has seen agencies invest heavily in platforms that later pulled back, leaving them with losses. Early adoption is therefore partly a bet on the technology and partly a bet on the company behind it.
A technology is only as strong as the ecosystem around it
A platform can be technically impressive yet difficult to sell and deliver if the ecosystem around it is not ready. Payments, shipping, tax, ERP integrations, marketing technology, extensions and local partners all have an impact on whether a solution works in the real world. The same principle applies to AI. What matters is not only what the technology can do in isolation, but how well it fits into the systems and processes your clients already depend on.
Katy describes the wider ecosystem as a “massive force multiplier.” A mature ecosystem gives an agency somewhere to turn when it reaches a problem it cannot solve alone. There are other partners, existing integrations, communities, documentation and accumulated knowledge. Without those things, an agency may find itself spending valuable time solving problems that nobody else has encountered yet.
For European businesses, there is an additional layer to this conversation. Katy specifically highlights GDPR, AI regulations, and data sovereignty as part of the assessment agencies should make before committing heavily to a new platform. The more quickly technology evolves, the more important it becomes to understand not just what a tool makes possible, but the conditions under which it can actually be used.
That is why the strongest early adoption decisions tend to look at the whole environment rather than the technology in isolation.
Who should your first customers be when adopting emerging tech?
Another common assumption is that adopting a new platform will immediately generate new business. In reality, emerging platforms entering a new market are often still building their own brand awareness and pipeline, so agencies should not expect certification to suddenly bring leads. Existing client relationships are more likely to be the starting point.
Katy explains that “your first projects on a new platform will almost certainly come from clients who already trust you.”
That trust matters because asking a client to adopt emerging technology is different from recommending a tried and tested solution. You are asking them to accept some uncertainty alongside you.
This means choosing the first client carefully based on who values innovation and who’s willing to become a reference case if the project succeeds. A successful first implementation can then become much more valuable than its initial margin suggests. It gives the agency something tangible to show prospective clients and evidence that the technology works in the market it is trying to serve.
When does early adoption really work best?
On this question, Katy recommends a phased approach that starts with exploration and evaluation, moves into a controlled pilot, then develops the internal practice before scaling.
Sander shares how Open Commerce takes exactly this approach when evaluating a new SaaS offering. The team selected a developer who was comfortable learning new technology and had already rebuilt an earlier shop on the platform while being able to track how long different tasks actually took. They also documented the problems they encountered and began creating the processes they would need for real client delivery.
The real question then is not whether an agency should adopt emerging technology early. It is whether one is prepared to make the investment, accept uncertainty, and do the learning required to turn that early start into a genuine advantage.
Looking for more insights like this? Follow The Open Podcast and stay tuned for more episodes on AI this month.
