Every year, Kalypso surveys brands and retailers on the state of digital transformation in product creation. Ten years in, the picture is getting clearer and more honest.
The research has evolved considerably since it launched in 2016, when the focus was primarily on the state of technology supporting product development. As DPC emerged as a major topic around 2018, the study followed, tracking how brands were using the tools, what they wanted to achieve, and how close they were to hitting scale. By 2024, the conversation had shifted again: less about what the technology could do, and more about what was stopping brands from getting there.
The 2026 edition moves away from the technology conversation that has dominated previous reports and lands squarely on the harder questions: people, process, and what it actually takes to make change stick.
🎥 Watch the full discussion below, and read on for the full write-up.
1. The industry has tech fatigue and it's largely self-inflicted
Teams are exhausted. Not because transformation is inherently draining, but because too many organisations have been throwing technology at people without first asking what problem they're trying to solve.
Kalypso's framing is simple: define how you want to work, who needs to make which decisions, and what information they need to make them. Only then ask what technology enables that. Doing it in reverse is why adoption stalls and why people feel overwhelmed.
Change that is directly tied to how people do their jobs is meaningful. Change that isn't is just a distraction.
2. Who owns the decision matters as much as what the decision is
One of the more quietly damning observations in Kalypso's research is how often the wrong people are in the room when product decisions get made. They cited a brand where the VP of HR was regularly present in design meetings, not as a bad actor, but as a symptom of governance structures that had never been properly redesigned for the way modern product teams need to work.
The consequence is predictable: too many voices, slower decisions, and a culture where senior leadership second-guessing their teams at the final moment extends timelines and kills momentum.
Kalypso's recommendation is to anchor your operating model around three questions:
- when does this decision need to be made?
- who needs to make it?
- what information do they need to make it well?
With those answered, you can then start to build everything else around them. Trust, it turns out, is an operating model decision as much as it is a cultural one.
3. Change management needs to be measured, not just managed
Traditional change management has focused on communication and adoption — tell people what's changing, train them on the new tools, hit 100% usage. The problem is that 100% adoption doesn't guarantee 100% value delivered.
Kalypso's recommended shift is towards value-led change management: define the specific metrics that represent success before the programme begins, track them throughout, and if they aren't being hit, go back and ask why.
It sounds straightforward. Most organisations aren't doing it.
The result is programmes that look successful on adoption dashboards while quietly failing to deliver the business outcomes that justified them in the first place.
4. DPC is not a technology. It's an approach.
One of the clearest shifts in this year's research is how brands are reframing digital product creation.
DPC used to mean 3D, specifically, digital sampling. And when that narrow definition didn't deliver the expected ROI, it was easy for leadership to pull funding.
What Kalypso is now seeing (and recommending), is a much broader conception: DPC as a digitised way of working across the entire product journey, from AI-assisted concepting and 3D development through to merchandising, sales, and e-commerce.
When DPC touches five different points of value along your operating model, it becomes nearly impossible to justify cutting. When it touches one, it's always vulnerable.
5. Your data is a goldmine you probably can't access
Almost every brand Kalypso spoke to is sitting on years of valuable product, sales, and consumer data. Almost none of them can use it properly.
The reasons are consistent: siloed systems, inconsistent schemas, poor governance, and data that was never kept current. Fixing your data foundations is the single most important thing you can do before investing further in AI or any other decision-support technology.
There is a trust dimension too: if your teams don't believe in the data, they will ignore the AI and go back to gut instinct. As one webinar attendee put it in the chat, 'if teams don't trust their data, they are not going to trust what the AI tells them either'.
Both the data and the culture around it may need fixing at the same time.
6. AI has three speeds, but most brands are only operating at one
Kalypso broke AI into three distinct modes that brands are approaching very differently:
Assistive AI — ChatGPT, Copilot, generative image tools — is where most investment is concentrated and where most current value is being extracted.
Applied AI — predictive systems that monitor data and surface pattern-based insights — is what brands are trying to scale next, and where data readiness becomes the limiting factor.
Agentic AI — systems that can make decisions and act on them autonomously — is where most brands see future potential but are still figuring out how to deploy it responsibly.
The message is not to skip ahead. Get your data right, get assistive AI embedded, then build towards applied. Agentic will follow.
And one important caveat from Kalypso: agentic AI, at least today, is not creative. It can reduce the friction of menial tasks and free people to focus on genuinely value-added work, but it cannot replace the creative human mind.
7. Not every brand needs to be racing and Kalypso's data says so
In a landscape saturated with AI urgency, one of the more useful things Kalypso's research does is give permission to be intentional rather than reactive.
The brands they spoke to ranged from those actively choosing not to adopt AI in their product creation processes — because it doesn't align with their brand identity or the kind of work they value — all the way to those who have built proprietary tools trained on their own data and are moving at full speed.
Both are legitimate positions.
What matters is that the choice is made consciously and in service of a clear strategic vision, not because everyone else seems to be doing it. The brands that struggle most aren't the ones moving slowly. They're the ones moving without knowing why.
8. The product lifecycle doesn't end at the point of sale
The final area Kalypso flagged as a growing focus is the connected loop from product creation all the way through to end of life: returns, repair, resale, and the data that flows back from those moments into future planning.
To repair a product, you need to know how it was made.
To resell it with confidence, you need traceability.
The European Digital Product Passport is accelerating all of this on the regulatory side, but the brands moving fastest are doing it because the commercial logic is compelling.
Make it once, sell it twice.
The brands that have their product data in order now are the ones that will be positioned to build those revenue streams, and to close the loop between what gets made and what actually lasts.
Kalypso's full 2026 Retail Research report is available to download here.
For more information, contact Joshua Young or Alison Coddaire directly via LinkedIn.
