Brand Voice & Scaling Content: Jacquard’s 2026 Marketing Predictions

We’ve seen a seismic shift in the adoption of AI this year. And what was supposed to solve marketing’s content problem has instead created two new ones. Here at Jacquard, we see the balancing act of these two problems as the fundamental challenge marketing teams have to grapple with in 2026. 

85% of brands now use ChatGPT for production marketing content. It would make sense to think that this might have made marketing easier. But instead we’re seeing brands converge – globally – on a singular voice. It’s one that we can all recognise at this point: a familiar AI-inflected cadence that sounds the same no matter where you see it. Meaningful differentiation is harder than ever. But this doesn’t mean that brands need to turn away from AI: in fact, brands should lean in, utilising the strengths of these powerful tools – the hyper-personalisation they afford, the sheer scale of content they can produce – to ensure that their brand voice stands out from the crowd. 

This will be the first problem marketers have to reckon with in 2026. How to ensure your brand voice stands out, and actually says something meaningful. When ChatGPT handles the copy for everyone, we see the same basic competency embraced on all sides. When a multinational conglomerate and a local startup sound identical because they’re both clicking “generate” on the same prompts, something fundamental breaks down in brand communication.

It’s not that AI is bad at copywriting. It’s about a more fundamental challenge: when everyone uses the same tool, differentiation evaporates. A distinct brand voice, built for performance, once a nice-to-have, is now essential competitive infrastructure. We’ve seen firsthand at Jacquard how the brands that will win in 2026 are those that have moved beyond prompt engineering and built systematic approaches to maintaining linguistic identity at scale and optimising it for engagement and conversion. 

Consumers are already wise to generic AI writing – Google searches of the ‘em-dash’ often used by ChatGPT increased by 400% in 2025 – They are increasingly gravitating towards brands that make the effort to sound genuinely different. The human touch can’t be overstated. Nuances in language hold more weight than ever, and the AI chatter is getting ever louder. Standing out requires more than just better prompts, it requires real depth and understanding. Solving this challenge demands sophisticated infrastructure. At Jacquard, we’ve built tools trained on billions of data points and a decade of language expertise to do exactly that.

Our second prediction is that 2026 will see content creation become the new bottleneck for marketers. We’ve all but solved the data problem – but that’s only left us with a content problem. 

A decade ago, the challenge was collecting, analysing, and activating customer data. Today, with sophisticated tools like AI Decisioning readily available, that’s no longer the primary constraint for most brands. But as audience segmentation and decisioning becomes more sophisticated – and we see increasingly complex groupings based on behaviour, location, language, channel, purchase history and lifecycle stage – content demands multiply exponentially.

Consider the mathematics: if you’re segmenting your audience into hundreds of micro-segments, each requiring personalised messaging across email, push, SMS, and in-app channels, you’re looking at thousands of content variants. This is not a task human copywriters can scale to meet, no matter how talented or numerous. Ask any over-worked copywriting department, and they’ll tell you these numbers mean their task just isn’t feasible. 

The temptation is to throw ChatGPT at the problem. But this creates the very issue outlined above: you solve the volume problem whilst creating a differentiation problem. You end up with content that sounds exactly like your competitors, it doesn’t perform, and you still face the manual effort of distributing that content across channels.

So marketers are looking at managing a difficult balancing act – the content supply chain. Teams are required to create enough (meaningfully) personalised content for all their segments, across all relevant channels, while maintaining a distinctive brand voice. 

This is the bottleneck that most marketing teams haven’t yet acknowledged, let alone solved. Data and tools are abundant. Genuinely on-brand, performant, personalised content at scale remains scarce.

This is where Jacquard’s approach differs from generic AI tools. Our platform learns and replicates a brand’s unique linguistic patterns, allowing marketing teams to generate thousands of personalised message variants that maintain brand consistency whilst driving measurable performance improvements using proprietary performance modelling. We’ve seen brands using this approach achieve click-through rate improvements of up to 89% and conversion rate increases of 30% and more, all whilst producing content at a scale that would be impossible through manual processes. The technology addresses both challenges: maintaining differentiation through brand-specific language models, and solving the content bottleneck through automated, multi-channel distribution.

Our two 2026 predictions – ensuring a distinct brand voice optimised for performance, and handling the content bottleneck – are really two sides of the same coin. As more brands recognise that generic AI tools create sameness rather than differentiation, and as content demands continue to multiply with sophisticated, necessary AI strategies, 2026 will be the year that separates the organisations with proper content infrastructure from those still relying on prompt engineering and manual distribution.

To thrive, marketers will need to move away from focusing solely on prompt engineering and decisioning. They’ll have to find ways to solve the fundamental challenge of maintaining linguistic identity whilst meeting the content demands of modern, hyper-segmented, hyper-personalised marketing.

The question of whether or not to use AI is a thing of the past – the numbers show this starkly. Instead, the question for marketers is now how to use the power and scale AI offers to ensure that their brand voice – that they’ve worked so hard to cultivate and build – doesn’t fade into the cliché-ridden static.