Where Creative Adaptation Is Heading Next Year

2025 saw clients requiring more assets than ever with many campaigns racking up thousands, all needing to be adapted globally. Presence became one of the defining features of how brands evolved to behave in consumers’ lives, further entrenching an ‘always on’ framework. Creative adaptation had to evolve – fast – to help clients get ahead of these changes and keep their competitive edge.

The transformation is driven by a few factors like gen AI and accelerated production expectations alongside the continued rising demand for personalised, platform-specific storytelling. We will see brands continue to prioritise speed, efficiency, and contextual relevance, but the methods to achieve those objectives will evolve.

Gen AI is already embedded in everyday production workflows and 2026 will see it adopted more widely as brands and marketers look to reap the rewards promised. The tech powers copy and image variations, accelerates versioning, and enhances quality assurance – when paired with human oversight. Human involvement will remain crucial and non-negotiable (for the foreseeable future, at least) as no amount of data can be subbed for a human’s experience and interpretive ability to parse intent, cultural context, and nuance. It’s the difference between creating content that’s relevant to other humans rather than technically ‘correct’.

The ongoing transformation reflects a broader change in client expectations. Marketers who once sought an approach that encompassed simple translation, minimal variants, and cost-efficiency above all else are now demanding rapid turnarounds, scalable personalisation, and performance-linked creative outputs. As the industry moves toward an end-to-end content supply chain, the challenge and opportunity will lie in balancing AI-powered automation with human oversight and creativity. Only when the two work in tandem can they really deliver relevance, quality, and trust at the scale that brands need in 2026 and beyond.

Below, we take a look at where creative adaptation and client expectations are at today, and what the future – accelerated by gen AI – might look like soon.

Current state of creative adaptation

AI is already integrated at multiple points of asset production helping to improve speed and lower costs. Now, clients must balance leveraging efficiencies while creating and maintaining distinctiveness. One of the dangers of too much AI is blandness; that’s why a robust layer of human expertise needs to be present to steer the tech-enabled progress in a direction that’s always relevant to other humans.

A positive we’ve seen companies report is that using gen AI not only speeds asset versioning and design, but also connects more parts of the value chain – like marketing, inventory and operations – by giving visibility and agility across stages. Similarly, with Dynamic Creative Optimisation (DCO) mainstreaming to ease personalising visuals and messages at scale across markets and contexts, investment and usage have accelerated since 2023.

As partnership models evolve, we've seen a continued, steady rise of in-housing. Many brands are building or expanding their own creative adaptation capabilities, often blending internal teams with external expertise. In our own client partnerships, this has taken the form of hybrid models where Locaria helps design, build, and staff in-house studios that remain fully embedded within the client organisation. This approach gives brands greater control and speed, while still benefiting from specialist oversight, scalable resourcing and workflow orchestration across markets.

What did clients want in the past?

We saw clients opt for translation over transcreation with less market variants resulting in ‘one master fits all’ with only language swaps.

Personalised and customised assets were less present with a focus on cost-efficiency, resulting in flattened nuance and subdued relevance.

Media plans were adjusted by asset volume instead of creative master materials options development.

What do clients want now?

Today, clients want faster and cheaper asset production and adaptation whilst maintaining the same high quality: speed-to-market is now a critical KPI, with many global brands expecting turnaround in days, not weeks.

They’re often turning to gen AI for production speed (image/variant generation, alternative copies), with human creative direction and brand control.

Scaled personalisation is an ongoing priority with brands creating variations by audience segment, cultural context, and platforms. Instead of five or ten adaptations, brands now expect hundreds of assets for various markets and audiences from a single campaign master.

Measurability needs to be embedded with clients expecting creative variants to be linked to performance data, not just delivered as ‘finished’ assets.

What do clients hope for in the future?

In the not too distant future, clients will double down on an end-to-end ‘content supply chain’ – assets planned, produced, localised, trafficked, measured to reduce fragmentation.

The scope of personalisation will only increase as brands will want to ensure that the right message is delivered at the right moment to the right audience even more efficiently.

​AI compliance will become a huge topic of conversation covering not only brand guidelines control, but also usage rights management, legal checks and consent tracking with the support of AI.

Processes, tools, and technology transformed

To date, creative adaptation has followed a largely linear production chain starting with master assets and ending in versions adapted for different markets. We now have at our disposal a wide range of recently developed automating tools that can support simple adaptation, faster. Cloud-based systems are being adopted to centralise version control, while performance measurement platforms are gradually helping brands optimise and personalise assets in-flight. Early adopters of AI are testing automated briefs, but day-to-day adaptation is still primarily human-led.

AI: reality vs. hype

There’s a lot of justified hype around AI with many legitimate uses already in deployment. Right now AI is great at providing scale by generating different versions of the master materials that are consistent across all markets.

It can optimise and learn to connect creative variants to outcomes and can help with asset performance measurement.

It also has pretty meticulous attention to detail (if instructed to do so) and can assist with QA and accessibility: detect missing supers/logos/clearspace, generate alt-text/captions, and flag low-contrast or off-palette assets.

Still, there are limits to AI’s capabilities. It cannot create distinctive brand campaigns or emotionally resonant storytelling like a team of creatives can.

Cultural nuance is a struggle for AI since literal translation doesn’t equate to transcreation; human review is required for sensitive markets and regulated categories.

Finally, AI compliance like governance, licensing, and usage rights management remain human responsibilities.

Looking to 2026, we can expect a move towards an integrated content supply chain with even more personalisation and stronger AI compliance frameworks. And while automation and AI are speeding up adaptation and QA, real creativity, cultural nuance and governance will continue to rely on people, making the future a blend of intelligent tools and human expertise.