They use it daily but don't trust it: what 100 fashion professionals said about AI
Nine in ten fashion industry professionals use AI every day, yet they do not leave important decisions to it. That is the result of a survey The Interline ran earlier this year of about 100 fashion professionals. 90% of respondents used AI daily at work, about 85% of companies had accelerated adoption over the past 12 months, and about 70% expected AI spending to rise in 2027.
Optimism and anxiety appeared together. Respondents were broadly optimistic about AI, but said there are not yet standards for assessing its value. Some worried that their companies overestimate their AI capabilities, and the survey also showed that companies have not properly connected AI with their existing technology environments. The results come as brands and retailers place large bets on general-purpose frontier models (large AI models used across many fields) and fashion-specific tools.
The host of The Interline podcast describes this gap as the "jagged frontier" of AI performance. AI may excel at generating fashion product images yet be weak at understanding how garments are made and where they are used. Respondents saw AI as most mature in analytical uses such as planning. In other words, areas where it performs well are mixed with areas where it is hard to rely on it.
Source · The Interline, "Is AI Already Good Enough For Fashion?"
Caimera cites a 95% approval rate. Trust comes from accuracy
AI image startup Caimera points to the number 95% as the basis for trust. It is the image approval rate on its platform, according to the company. In one of the 17 executive interviews The Interline published in The AI Report 2026, founders Kirti Poonia and Prateek Gupte explained how they bring generated output up to a level brands can put in front of customers. Poonia says trust comes from building up accuracy.
There are two core tools. Sketch-to-image (a feature that turns design sketches into product images) produces one consistent result instead of laying out many candidates. According to the company, it faithfully reflects prints, structure, and seams, so it can also be used at the point where products are sold to consumers. The bulk catalog image tool applies the same background, model, lighting, and pose to thousands of products in a single batch job.
There are also features aimed at enterprise customers. Caimera says it provides legal protection to enterprise brands, and claims that customers process more than 1,000 styles a month. All of these figures are the company's own statements and should be read as such. What characterizes the interview is that it puts consistency of output and accountability ahead of generation speed.
Source · The Interline, "All About AI: Kirti Poonia & Prateek Gupte of Caimera"
Clothing Color Match. A review step that matches garment color to the original before publishing
RealSnap's Clothing Color Match is a snap tool that corrects only the garment area in a generated result image, using the original garment's color as the reference. When the garment color in a generated cut looks different from the actual product, you can use it to check the color before publishing.
With a result image open, you can go straight into the color correction tool.
The original garment reference is loaded automatically, creating a baseline for matching colors against the clothing area in the current result.
It is one of the free correction tools that only adjusts color without redrawing with AI, and you apply them one at a time.
Try using RealSnap's Clothing Color Match on your next generated cut as a color review step: compare the garment color against the original item, then choose the cut to publish.
