Design for Getting Dressed: AI Briefs for More Inclusive Menswear

A shirt can look excellent in a photograph and still be frustrating to put on. A cuff may be awkward to fasten. A neckline may require a movement the wearer would rather avoid. A beautiful kurta may be comfortable standing but less welcome during a long seated occasion.

These are design questions, not reasons to make assumptions about a person. AI could help a design team organise them—if the process begins with the wearer rather than an imagined “average user”.

Start with lived experience

Microsoft’s inclusive-design principles emphasise recognising exclusion and learning from people’s diverse experiences. They provide a useful process lens, not a garment specification or a claim that one solution suits everyone. See Microsoft Inclusive Design.

For clothing, begin by asking what someone wants to wear, what gets in the way and what they do not want changed. Style preferences belong in that conversation alongside practical needs. Easier use should not automatically mean abandoning the look the wearer enjoys.

Give AI a limited, useful role

Google documents text generation from supplied inputs in its Gemini API guidance. A proposed use is to turn consented, de-identified feedback into a draft set of design questions. That is information organisation, not proof that a model understands a person’s abilities or can validate an adaptive garment.

This article describes a conceptual development approach. It does not claim that TRYBUY.IN offers adaptive clothing or AI-led accessibility assessments.

Describe the task, not an assumed diagnosis

“The wearer finds this cuff difficult to fasten independently” is an actionable observation. A broad label attached to a person is not a complete design brief.

Ask whether the difficulty concerns reaching, grasping, seeing the fastening, understanding its orientation or something else the wearer identifies. Do not let AI select an explanation on their behalf.

Keep private health information out of the brief unless it is genuinely necessary and appropriately handled. For many early design questions, the task and the person’s stated preference are the relevant information.

Build three columns for the design discussion

What the wearer reported

Preserve the original meaning. If someone says a men’s kurta feels awkward to put on over the head, do not summarise that as “dislikes kurtas”. The garment category may be exactly what they want to wear.

Questions to explore

Ask which design features might be investigated and what trade-offs need discussion. A different opening arrangement could change appearance, construction and use. The team should compare options with the wearer rather than letting the model select a universal answer.

Evidence needed from a prototype

Write down what the physical sample must help establish. Can the person use it in the way they prefer? Does it remain comfortable in the situations they named? Is the visual result one they would choose?

A rendering cannot settle those questions. Treat it as a discussion aid, not a demonstration of usability.

A brief worth testing

Try this prompt: “Organise these wearer-approved notes into reported experiences, open design questions and prototype checks. Preserve differences between participants. Do not infer diagnoses, invent preferences or claim a proposed feature is safe or accessible for everyone.”

The designer should review the output with the participant. Invite corrections, including “that is not what I meant”. If two people prefer different approaches, retain that disagreement instead of averaging it into an option neither requested.

Keep boys’ garment development separate from adult menswear. Children’s clothing needs its own appropriately supervised design and safety review; an adult concept should not simply be reduced in size.

Test the routine as well as the finished look

Agree a suitable review process with the people involved. Discuss getting dressed, wearing the garment and taking it off, without demanding uncomfortable demonstrations. Allow participants to stop or decline any part.

Record what worked, what remained difficult and what the wearer wants changed next. Qualified product specialists must assess construction and safety. AI can help maintain the questions across revisions, but the participant’s experience should not be overruled by a favourable summary.

Frequently asked questions

Can AI design accessible clothing by itself?

No. It can assist with a brief, but co-design, specialist judgement and physical validation remain essential.

Does one easier fastening work for everyone?

Do not assume so. Preferences, tasks and garment requirements differ.

Should every participant receive the same solution?

No. Preserve individual needs and feedback rather than forcing agreement for a simpler report.

When browsing TRYBUY.IN, consider how a garment would work in your own routine. Ask about any important detail that the listing does not establish.

Primary sources checked on 24 September 2026.