Content strategy in the AI landscape
I started my design career largely focused on content and words. As writer and content strategist, I dove into how words and images (and interfaces) were intertwined and connected, not words as an afterthought. Fast forward 20 years, and AI is reshaping product design - both the products we design and how we design them - and one thing is becoming more apparent: content strategy and UX writing aren’t side jobs. They are foundational.
AI products live and die by language. Prompts, responses, onboarding, microcopy, taxonomy - all of these are based in words. If those words are sloppy, biased, or confusing, it doesn’t matter how powerful the underlying model is. Companies who treat content as an afterthought of “polish,” will end up with product failures.
Why content matters now
Context and trust are content problems
Users need to know what to expect from an AI system: what its boundaries are, and what’s at stake if it’s wrong. Content strategy is what shapes that scaffolding: disclaimers, guardrails, confidence levels, “why” explanations. Without thoughtful writing and framing, hallucinations create a breeding ground for confusion and misinformation.
Content shapes the data
Prompts, documentation, and structured content are inputs. The words you use in prompts, feedback loops, and documentation don’t just guide the user; they shape the dataset the AI learns from. Inconsistent or incomplete content outputs inconsistency and lack of clarity. Thoughtful content develops a robust collection of information.
Taxonomy is infrastructure
A well-structured knowledge base, taxonomy, or content model not only helps users find what they need, it also feeds the AI with clean, consistent data. When content is fragmented or mislabeled, the system becomes disjointed and the experience disconnected. When it’s structured and intentional, AI can surface the right answers faster and with more confidence.
Differentiation comes from tone
Lots of companies are using the same foundational models. But just like voice and tone matters in websites and interfaces, the edge will come from how those systems interact: is the response empathetic, authoritative, friendly, clinical? That’s content design at work.
Content isn’t polish
Sadly, many teams still treat content as something you bolt on later in the design process. But in AI products, it’s core to the product. Glossing over a confusing system with a few lines of microcopy doesn’t fix fundamental data problems. It has to built in from the start.
In recent years, I’ve seen companies downsize or eliminate content strategy and writing roles, thinking they could streamline. A quick perusal of LinkedIn finds it littered with impacted writers. While that may have looked efficient on a spreadsheet, in an AI-driven product landscape, it’s a short-sighted move. If anything, those skills are about to become more valuable, not less.
AI won’t make good content strategy optional. It’ll make it a competitive advantage. Companies that recognize this, and bring writers and strategists back into the core of product design, will have an edge in building coherent, consistent products people use and trust.
