How we design with AI without losing craft

How we design with AI without losing craft?
We use AI for thinking and writing, and keep people on visual decisions. In our October 2026 survey of 11 Hatypo, Habito designers and developers, 9 use AI daily or nearly daily, 8 deliberately keep visual design AI-free, and 10 spend the time they save on deeper research. None reported lower quality. Seven of 11 have no settled rule for when AI stays off.
This article draws on our internal survey (16 responses, 11 in scope), Doshi and Hauser's 2024 Science Advances study of AI and creative writing, Microsoft Research's 2025 CHI survey of 319 knowledge workers, and Figma's 2025 AI report of 2,500 designers and developers.
I'm Raull Khaq, COO at Hatypo Studio, and Art Director at Habito, our branding studio. I oversee daily operations across our teams and ran the survey behind this article. Hatypo has delivered 250+ projects since 2021, so I see how AI use plays out in real project work.

Key takeaways
- AI helps most with brainstorming and copywriting, 4 of 11 respondents each.
- Output is a draft: reuse without edits averages 3.1 out of 5, and heavy rework averages 4.0.
- 10 of 11 have seen generic or wrong output, and 5 of them see it often.
- Craft means choosing the concept (9 of 11) and reading the client's context (7 of 11) more often than pixel detail (5 of 11).
- 8 of 11 say whether clients should be told about AI depends on the project.

How did we run the survey, and how far can the data go?
We sent a Google Form to the designers and developers at Hatypo and Habito between 9 and 12 October 2026. Of 16 responses, 5 came from project managers and account executives, so we counted the other 11: 6 UI/UX designers, 3 brand designers, 1 motion designer and 1 front end developer.
Eleven people is a small sample, so we report counts and skip percentages. The answers are self-reported, and the survey came from management, which can push answers toward the positive. Read the numbers as what our team says about its own work.
Where do we design with AI, and where do we stop?
Brainstorming, research and copywriting carry most of the AI work. Four respondents named brainstorming as the stage where AI helps most, four named copywriting, and one each named research, wireframing and coding. ChatGPT (10 of 11), Claude (9), Gemini (8) and Figma AI (7) are the tools in use.
Visual design is where respondents most often stop. Eight of 11 said they deliberately avoid AI there, more than any other stage. Illustration and moodboards followed with 3 each.
The open answers repeat the pattern: AI works on questions and words, and people make the visual calls. One designer put it as a rule: anything that needs empathy for the client or user, and all visual exploration, stays human, while AI handles technical tasks.
Figma's 2025 report shows a similar split by role. Of its 2,500 respondents, 59% of developers used AI for core development work such as code generation, against 31% of designers for core design work such as asset generation.


How much time does AI save, and where does the time go?
Five of 11 respondents saved 26 to 50% of their working time, four saved 11 to 25%, and two saved more than 50%. Nobody chose the 1 to 10% bracket. In the same Figma report, 78% of respondents agreed that AI significantly improves the efficiency of their work.
The saved time goes mostly into thinking. Ten of 11 spend it on deeper research, five on more iterations and five on rest. Only one respondent uses it to take on more projects.
On our team, saved hours go mostly into understanding the problem.
How often does AI output survive without edits?
Respondents rated how often they use AI output unchanged at 3.1 out of 5 on average (1 is never, 5 is always). They rated how often they rework it heavily at 4.0. Six of 11 gave rework a 4 or 5, and only 3 gave unchanged use a 4 or 5.
In practice AI gives a first version that a person finishes. Final quality still came out higher for 10 of 11 respondents (8 said slightly higher, 2 said much higher), and the eleventh saw no change.
Why does AI output look generic?
Ten of 11 respondents have met generic, wrong or derivative output, and 5 meet it often. Respondents described layouts that start to look alike across projects, with dashboards and wireframes as examples.
A 2024 experiment in Science Advances found the same pattern in writing. Writers who could pick from five AI-generated ideas wrote stories that evaluators rated 8.1% more novel, yet AI-assisted stories were more similar to each other. That suggests the risk sits at portfolio level: each piece looks fine and the set looks alike.
How do we check AI output before it ships?
Ten of 11 respondents check details by hand, 6 compare the output with references, 2 ask a teammate to review it, and 2 test it with a client or user. Peer review is the thinnest of our checks.
A Microsoft Research survey of 319 knowledge workers found that people who trust the AI more apply less critical thinking, while people confident in their own skill apply more. Three of our respondents tied the moments their craft slipped to deadlines, when there was no time to review everything AI produced.
What do our designers and developers mean by craft?
We asked respondents to pick the parts of design they count as craft. Nine of 11 picked concept selection, 7 picked sensitivity to the client's context, 6 picked design decisions, and 5 picked visual detail at the pixel level. The question asked for up to three picks and several people chose more, so read the counts as relative weight.
In their own definitions, people described craft as a good concept, care for the smallest detail, and empathy for the client or user. Craft sits in judgment more than in manual execution, which fits the finding that 8 of 11 let AI work upstream and keep visual execution in human hands.
Has AI lowered our craft, and has it raised it?
Five of 11 respondents said AI never lowered their craft, six said it did once or twice, and nobody said it did often. The reasons were specific: accepting output under deadline, results that felt unoriginal, and a concept the tool could not draw.
Respondents also described gains. They named more time for research, perspectives they had not considered, and visuals that would be hard to make by hand.
Six of 11 say AI helps them learn design skills faster, four see no difference, and one is unsure. Nobody said it slows learning, though the survey asked people to judge their own learning, which is hard to measure from the inside.
What rules keep craft in place?
Four of 11 have a personal rule about when AI is allowed, three are building one, and four have none. The rules differ: no AI for logo design; empathy and visual exploration stay human; execution and the final decision stay with the designer; and AI is acceptable when deadlines are tight or client needs are unreasonable.
The things nobody hands to AI overlap. Three respondents named decision-making and two named logo design. Others named visual exploration, judging a full design from a brief, and what one developer called the soul of the work.
What working rules does the survey support?
- Use AI upstream and finish by hand. Research, brainstorming and first-draft copy go to AI. A person owns visual execution and the final decision, and 8 of 11 respondents already keep visual design AI-free.
- Plan for rework. Heavy rework averages 4.0 out of 5, so schedule revision time and do not count AI output as done work.
- Keep a minimum check under deadline. Every AI output gets a manual detail check and one comparison with references. Ten of 11 respondents already do the first, and 6 do the second.
- Add a second reviewer on key deliverables. Only 2 of 11 ask a teammate to review AI output, which leaves most checks with the person who made the work.
- Set one default for telling clients. Eight of 11 say disclosure depends on the project, 2 say always and 1 says it is not needed. Without a default, each project gets a different answer.


How can Hatypo help with your product design?
If you want to know where a design studio uses AI on your project and where it does not, we can walk you through our process on a call.
Hatypo has delivered 250+ projects since 2021, and projects start at $3,000, with the price following the scope.
- If you are starting a new product or website, we design it from research through developer-ready files.
- If your current interface underperforms, we review it and propose a redesign scope.
- If your product has outgrown its first version, we rework the key flows and the design system.
Tell us where you are and we will recommend a scope: Book a consultation.


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