Design thinking is often described through stages such as empathise, define, ideate, prototype and test, though real projects tend to move backwards, sideways and around again.
For content work, its value lies in replacing assumption with evidence and debate with something people can try. A team can explore several ways to explain a service, put rough versions in front of users and learn before committing to a finished design or a small mountain of copy.
Why it matters for content
Organisations often arrive with a requested output: a new website, campaign, guide or chatbot. Design thinking encourages the team to ask what problem sits underneath the request and whose problem it is. The answer may reveal that people need a clearer process, a timely message or one trustworthy source rather than more content.
Prototyping is especially useful. Content can be tested in sketches, paper journeys, draft messages and simple interactive flows. These need not look finished. Their job is to reveal whether people understand the language, find the right information and know what to do next.
The approach also gives different disciplines a shared way to learn. Researchers bring evidence, content specialists shape meaning, designers explore interactions and subject experts test accuracy. It works best when participants can change the outcome, rather than attending a workshop-shaped interval before the original decision resumes unchanged.
How AI changes the picture
AI can accelerate exploration by generating variations, summarising research and turning rough ideas into prototypes. Teams can test more possibilities and create realistic edge cases earlier. This is useful when speed serves learning rather than merely helping the first idea acquire a glossy surface.
Generative tools can also reproduce assumptions in their prompts and training data. An AI-created persona or journey isn’t user research. It may help a team formulate questions, but it can’t provide evidence about what real people need, experience or understand.
AI products themselves benefit from design thinking because their behaviour is uncertain and shaped by context. Teams need to prototype failed retrieval, unclear requests, correction, escalation and consent alongside the successful cases. Human-centred principles remain essential when an interface can produce something nobody explicitly designed.
Questions people ask
- Must the stages happen in order?
The stages describe ways of working, not a ceremonial sequence. Teams move between understanding, making and testing as they learn.
- Is it the same as user-centred design?
They overlap. Human-centred or user-centred design expresses a commitment to people’s needs, while design thinking describes methods and mindsets for applying that commitment to problems.
- Do content teams need to prototype?
Yes, when structure, language or interaction is uncertain. A rough content prototype often reveals more than discussing an abstract requirement for another hour.
- Can AI replace user research?
No. It can organise evidence or help prepare research, but generated users can’t tell you what actual people do, need or misunderstand.
Learn more
- Design Thinking 101 – Nielsen Norman Group’s six iterative phases, including implementation, rather than a fixed five-step sequence.
- Design thinking and human-centred design – IDEO’s distinction between a people-first orientation and the methods for applying it.
- Principles of human-centred design – Don Norman on keeping people and the wider system in view.