After closing our doors for the holidays with a rearview on the most popular stories The Interline published in 2025, we kick off the new year with our team’s combined predictions on ten themes that we expect to define the way the fashion and beauty industries steer the development of technology, and vice versa, in 2026.
These themes cover the full spectrum, from creative design and technical development, to essential data-wrangling, strategic sourcing, and the secondary market.
Prediction, of course, is not an exact science. So while each of these themes is based on insider knowledge, expert understanding, and a good degree of confidence, we still intend to revisit them at the end of the year to see where our expectations aligned with reality.
Automation of back-office and administrative work
Aside from AI, which is likely to retain its privileged and protected status for the rest of 2026, every technology initiative needs to eventually deliver a tangible return. And the most visible returns – i.e. those that are measured in consumer or partner-facing applications, or that have direct anchors into strategic business objectives – tend to be the ones that get measured, and that then get used to secure further funding.
Through a combination of human nature and business logic, better topline sales is a more tempting metric to measure than time saved on the route to market. But as every industry professional who’s found themselves part of a technology project team has probably observed, the so-called “soft metrics,” like efficiency, reducing admin overheads, cutting manual data entry, and end user satisfaction, rarely get the same attention – even if those are the variables that ultimately determine the success of technology projects.
Recognition of the importance of these hidden indicators is now overdue, and there’s reason to believe that 2026 will be the year that industry-wide emphasis shifts inwards. While no sane executive sponsor is going to bankroll a project on nebulous “vibes” or woolly promises of productivity, Google-generated estimates still suggest that AI tools applied to routine administrative work can return more than a hundred hours a year per employee, simply by reducing time spent on scheduling, reporting, and data handling.
And while the jury is still out on the reliability of generative AI in enterprise applications, we expect that the speed and ease of data analysis and reporting that AI can offer will have a lot of brands (rightly) asking themselves whether optimising administrative work might not deliver a much bigger return than the industry has wanted to admit.
Integration of AI into core enterprise systems
AI might still be able to avoid some (or a lot) of the ROI analysis that other technology strategies must abide by, but no brand or retailer is a charity – and while generative image models deployed at the start or end of the product funnel are where a lot of the industry’s attention has been focused, we suspect that the real returns could be measured when we see deeper integration of AI into big enterprise systems like PLM.
The Interline has been saying for the last two years that, of all the platforms in the fashion tech estate, the one where all mission-critical product data lives (at least in theory) is the one that would benefit the most from the addition of a “copilot” that was grounded in everything from slot plans to supplier scorecards. Now, there are clear trust, governance, and accuracy standards that need to be met for this vision to be realised, but with so many data-generating systems making up the typical go-to-market journey, 2026 feels like the year where we see meaningful AI additions to those systems that could potentially add significant new utility to them, at a time when their footprint has become static.
Rescoping “digital transformation”
“Digital transformation” is one of those terms that has ended up meaning almost everything and anything, far outlasting its original intent as an exercise with a finite beginning and end. After years of investment, very few companies can claim that their operations and data are neatly connected from one end of the business to the other, and a lot of transformation programmes now stretch across so many phases and timelines that it’s difficult to remember what the original problem was meant to be. In some cases, the earliest processes to be digitised already feel slightly out of date – either because the organisation around them has moved on in ways that weren’t anticipated at the time, or because the state of the art has advanced.
Digital transformation, in other words, has started to feel Sisyphean – like an endless treadmill with no end state.
This year, rather than continuing to aim for full-spectrum, end-to-end reinvention, companies are set to begin breaking programmes down into narrower, more defensible goals, and being clearer about what sits in scope and what does not.
There’s some hard evidence behind this instinct. Research from McKinsey from 2022 suggests that around 70 percent of digital transformation initiatives were failing to meet their stated objectives then, and that even when programmes do succeed, the benefits often prove difficult to scale consistently across the organisation, or to reattach to a common trunk. And the added complexity of the technology ecosystem combined with the spread of AI, is likely to have negatively impacted that share even further.
Against that backdrop, the appeal of smaller, outcome-focused work is easy to understand. The risk of “forever projects” remains, but there is growing recognition that progress may depend less on finishing a messy idea of all-encompassing transformation, and more on keeping technology initiatives grounded in reality.
The content challenge
According to the head of Instagram, the race to produce polished, high-quality visual content at scale is, essentially, over. Thanks to the rollout of generative text, image, and video models, the level of production quality that used to define big brands with big budgets has become the baseline for creators of every stripe.
In that context, the question facing fashion and beauty brands is how to create external-facing communications and lifestyle marketing that still feels authored, intentional, and recognisably human – all without increasing overheads.
That logic helps explain why some of the more effective content campaigns of late has leaned so heavily into visible human process, and into the imperfections that are inherent in not just apparel and textile products, but the processes and people that created them. Hermès’ “Drawn to Craft” campaign last year acts as a great example, emphasising the human touch in a way that could set a template.
Of course, the challenge of then scaling that authenticity upwards and outwards will follow naturally, but in the meantime we expect to see retail and brand companies pursuing not just a different aesthetic, but different tools and pipeline.
Interrogating sustainability strategies
The European Commission’s decision last year to scale back and delay parts of its sustainability reporting and due-diligence framework is a useful illustration of the ongoing uncertainty that clouds sustainability strategies.
Inside organisations, attention appears to be shifting toward more pragmatic questions about where sustainability initiatives still deliver clear value, where they can realistically be scaled, and where they may need to be constrained to remain defensible and realistic without the supporting scaffolding of legislation. Recent industry research clearly shows that sustainability has slipped down the list of priorities for a significant portion of brands, even as many remain behind on their own targets. In the absence of consistent regulation, self-governance remains the default, and rather than keeping the ball in the legislator’s court, 2026 is likely to see if fall back at the feet of individual brands and technology providers, who will collectively need to decide where their values can be mapped to value.
Ownership of the secondary market
For a long time, resale has been something brands have been happy to leave at arm’s length. Third-party platforms have taken on the heavy lifting of building out technology and logistics infrastructure, have invested in campaigns to build the audience, have dealt with the complexity of authentication, and have promoted preloved fashion through their own channels and through lobbying efforts.
By and large, brands have been happy with this arrangement. But that tacit approval could start to unwind this year, when economic conditions drive greater numbers of customers towards second-hand goods, prompting a reminder of just how much of the secondary market journey brands have ceded to the control of external partners.
When a platform like Vinted ends up being the largest retailer in France by volume, it’s a reminder that a meaningful amount of everyday purchasing is now taking place outside brand-owned channels. At a certain scale, resale stops feeling like a side conversation and starts to look like a parallel stream of everyday commerce running alongside the primary market. And fashion in particular, already being squeezed from every other angle, will not be keen to let a potential second business unit fall completely out of its grasp.
Just as brands once went back and forth on how closely they wanted to tie themselves to marketplaces like Amazon versus pulling activity back into self-owned DTC channels, resale is now approaching a tipping point where it’s set to provoke a similar kind of internal debate.
Ongoing tension between de-risking and upstream consolidation
Geopolitical uncertainty, trade disruption, and regional instability are all continuing, in 2026, to reinforce the business case for supply chain diversification, and for reducing reliance on any single location or partner. From that perspective, spreading risk looks increasingly prudent, even necessary, as companies try to protect themselves against shocks that remain difficult to predict and harder to absorb.
At the same time, diversification brings its own set of complications. Shifting production between partners or geographies often means resetting relationships, reworking processes, and giving up some of the efficiencies that come with familiarity, repetition, and scale. When margins are already tight and pricing power is limited, that trade-off becomes harder to brush aside. This is where we’ll likely see renewed interest in more objective, data-backed ways of understanding cost, from labour operations through to process, that can be applied across different contexts with fewer assumptions baked in.
Category blurring, expansion, and platform flexibility
Category expansion continues to look like one of the more workable ways for brands to reach beyond mature markets where growth and margin are becoming harder to find. Fashion’s long-standing interest in beauty has already produced some clear successes, while movement in the other direction, from beauty into apparel, underlines how fluid category boundaries have become.
Alongside those headline moves, we also continue to see a steady stream of smaller expansions taking place across brands of all sizes, often positioned as limited tests rather than major strategic shifts, but driven by the same search for new revenue and relevance.
What tends to get less airtime is how well existing systems cope – or don’t – with that kind of flexibility. Expanding into a new category obviously brings questions around suppliers and partners, but it also has a habit of exposing assumptions buried much deeper in product data and go-to-market platforms about how hierarchies are structured, and what lifecycle stages look like. Some PLM systems, for instance, are well set-up for flexible category and business unit expansion, where others run the risk of saddling growth with a long tail of customisation and accumulated tech debt.
This year we expect to see more interest in composable, modular approaches to core systems as a result, where reuse and adaptability reduce the risk that each new category becomes its own permanent complication rather than a genuine opportunity.
Eroding technology footprints and AI as the “great leveller”
For most of fashion’s technology history, software has been sold and understood in fairly discrete blocks. ERP, PLM, supply chain, warehousing, 3D, and so on have operated as distinct categories, even when vendors bundled products together or up-sold portfolio integration, the underlying mental model stayed largely intact, with systems delineated by function and purchased accordingly. Over time, those boundaries have been tested through what we refer to as footprint expansion, as platforms push into adjacent territory, with mixed results.
What’s starting to unsettle that way of thinking isn’t another round of bundling or a new category label, but the growing sense that AI doesn’t slot neatly into any one box, and that the addition of AI into existing solutions serves to blur the lines to a new extent.
When the same underlying intelligence can operate across multiple parts of the workflow, the distinction between tools starts to matter less than what data they can access and what they’re actually allowed to do with it. And when AI interfaces become the predominant mode of interacting with software, then the ability for platforms to stand out based on their design and usability also disappears.
Where that line of thinking leads, and is still an open question, whether it collapses categories entirely or just makes them less tidy, but we do fully expect to see the lines that have traditionally separated software beginning to break down this year.
Spending on technology to stay in the game
Make no mistake: brands are operating in an environment shaped by genuine existential pressure, and that pressure is not easing as the year gets underway. Against a backdrop of squeezed margins, rising costs, and ongoing uncertainty, technology sits at the centre of an uncomfortable calculation about what can still be afforded, what can no longer be deferred, and what happens if investment slows too far in areas that underpin the rest of the business.
The question, increasingly, is not whether technology will deliver something new, but whether it allows companies to continue doing what they already need to do under less forgiving conditions. Much of the spend discussed across the themes above is defensive rather than expansive, aimed at maintaining operational viability rather than driving visible innovation. In that context, return on investment is, this year, likely to be measured less in growth or differentiation and more in resilience, adaptability, and the ability to remain in the game at all.