Artificial intelligence is changing how creative teams approach fashion design. What once took weeks can now happen in minutes with the right AI tools.

Fashion brands, from independent designers to global labels, are starting to integrate AI into their daily work. 

Whether for design assistance, product development, or predicting fashion trends, these tools help teams move faster and make smarter decisions earlier in the design process.

In this guide, we’ll explore how fashion AI tools reshape workflows and which ones are worth adding to your stack in 2025.

Why AI Is Becoming a Standard in Fashion Workflows

Designing and developing fashion products involves more than creative ideas. It takes time, coordination, and fast decision-making. That’s why AI design tools are becoming valuable. They reduce repetitive steps, improve collaboration, and support better outcomes at every stage of the fashion design process.

Instead of relying on traditional methods like manual sketching, guesswork in color selection, or slow sample reviews, teams now use AI-powered tools to generate concepts, test fit digitally, or suggest data-based materials. These features help remove delays and give designers more room to focus on creative work.

For brands managing growing product lines or shifting toward online shopping experiences, fashion AI creates faster feedback loops. Teams can react quickly to emerging trends, reduce costly mistakes, and move from concept to production without slowing down.

It also opens doors for more experimentation, especially when used with generative AI that supports rapid prototyping and virtual try-on features.

In short, AI in fashion is becoming a standard not because it replaces human creativity, but because it supports it. Reducing friction and helping teams stay aligned brings speed and structure to every part of the process.

9 Fashion AI Tools to Know in 2025

With more fashion teams using AI to speed up their work and reduce manual tasks, choosing the right tools makes a difference. Below is a list of nine fashion AI tools that support different parts of the design and development process:

1. Onbrand AI Design

Onbrand AI Design is a generative design workspace built for fashion teams. It helps users quickly create new styles, iterate on bestsellers, and organize collections using AI-powered tools.

The platform supports fast concept generation from sketches, photos, or text prompts, producing photorealistic visuals tailored to your category.

Teams can make quick design adjustments, test new colorways using official PANTONE and Coloro libraries, and export flats or on-model renders for production or review.

Onbrand also includes tools for building moodboards, grouping styles into visual line plans, and sharing files for real-time collaboration.

Designers use it to reduce manual work, cut down on physical samples, and stay aligned across the entire process. From early concepting to final visuals, it offers speed and flexibility for individuals and teams.

Key Features

• AI design generation – Start from a sketch, text prompt, or image to generate new concepts instantly

• Rapid iteration – Explore colorways, trims, cuts, and variations at lightning speed

• Photorealistic rendering – Convert designs into clean flats or lifelike on-model visuals

• Smart recoloring – Apply official PANTONE® and Coloro® swatches to generated designs

• Line planning & moodboards – Organize ideas, build collections, and present plans visually

• Real-time collaboration – Co-edit designs with your team and keep everything version-controlled

Designers using Onbrand report 10x faster design turnaround, 30-50% fewer physical samples, and 10+ weeks saved per year.

Start your 7-day free trial and save $1,000s on external resources!

2. Khroma

Source: khroma.co

Khroma is an AI-powered color selection tool designed to help users generate personalized color palettes based on their unique preferences. By training the system with favorite colors, designers receive tailored palette suggestions that align with their creative direction.

The tool is especially useful when selecting color combinations for mood boards, branding, or design themes during early concept development.

Khroma also allows users to search by hue, contrast, and other visual characteristics, making finding combinations that work well across different design contexts easier.

It functions entirely in-browser and offers offline access once trained, making it accessible to individual creatives and team workflows.

Key Features

• Custom palette generation – Learns user preferences to suggest color combinations.

• Search by visual criteria – Filter palettes by hue, contrast, brightness, and more

• Side-by-side previews – Compare palettes on different backgrounds or use cases

• Offline usability – Works locally after setup without ongoing internet access.

Downside

Khroma focuses solely on color development, not supporting garment design or broader fashion planning tasks. Teams will still need additional tools for visualizing and applying palettes across actual product concepts.

3. ZMO.ai (Creati)

Source: zmo.ai

ZMO.ai is an AI content creation tool that helps fashion teams generate on-model imagery without scheduling photoshoots.

Users can upload flat product images and apply them to AI image models, producing ready-to-use visuals for e-commerce, lookbooks, or digital campaigns. The platform supports multiple model types, poses, and backgrounds to reflect diverse customer groups and styling preferences.

Designed for marketing and merchandising teams, ZMO.ai reduces dependency on traditional photo shoots and enables faster turnaround for digital visuals.

It’s particularly helpful for brands managing large product catalogs or needing consistent content updates across multiple channels.

Key Features

• On-model image generation – Apply flat images to AI models for realistic previews

• Model diversity options – Choose from a wide range of body types, poses, and aesthetics

• Scene and background control – Adjust environments and visual settings for different campaigns.

• No photoshoot required – Create content without needing new photography

Downside

ZMO.ai works best with clean, well-lit product images and may require post-editing for garments with complex textures or layered details. It focuses on imagery only and doesn’t include product development or design creation tools.

4. Heuritech

Source: heuritech.com

Heuritech is an AI-powered trend forecasting platform that analyzes images and data from social media, e-commerce platforms, and global influencers to identify early signals in style, color, and silhouette trends.

The tool offers insights tailored to product categories and regions, helping fashion teams plan collections with better visibility into market movement.

Primarily used by merchandising and design teams, Heuritech helps reduce overproduction and improve assortment planning.

Using real-time data instead of static forecasts, teams can respond faster to changes in consumer behavior and refine product decisions with more confidence.

Key Features

• AI trend detection – Scans large volumes of social and retail data to identify style shifts

• Visual product tagging – Classifies garments by shape, color, and detailing

• Market segmentation filters – Sort insights by demographic, location, or niche audience

• Forecasting dashboard – Centralized view for design and merchandising strategy

Downside

While Heuritech provides rich trend data, teams may need analytical support to interpret outputs effectively. It’s designed for planning and insight, not for directly generating visuals or design content.

5. The New Black

Source: thenewblack.ai

The New Black is an AI-powered design tool that helps fashion teams generate concept visuals from written prompts.

Users can describe a garment or aesthetic, and the platform returns high-quality fashion images that reflect the input description. It's particularly useful in early-stage ideation, where teams must quickly move from reference to concept.

The platform supports concept generation across design, mood board creation, and client-facing visuals.

It focuses on creative exploration rather than technical accuracy, making it better suited for inspiration and early design discussions than production-level development.

Key Features

• Text-to-image generation – Create fashion visuals from short written descriptions

• Fast concept exploration – Try out multiple styles and ideas in minutes

• Style and mood filters – Adjust outputs to match design direction

• High-resolution image output – Suitable for internal presentations and creative reviews

Downside

The New Black is focused on visual prototyping and doesn’t include tools for spec sheets, fabric simulation, or technical development. Teams using it for early-stage concepts still need other platforms to carry work through production.

6. Botika

Source: botika.io

Botika is an AI-based imagery platform that generates on-model fashion photos using existing product images. Designed for e-commerce and digital marketing teams, it allows brands to create high-quality visuals without organizing traditional photo shoots.

Users can choose from various model types, poses, and backdrops to match campaign needs or target demographics.

The tool supports fast content production for websites, product listings, and social media. By automating model photography, Botika helps reduce cost and turnaround time, especially for teams managing large product catalogs or needing localized visuals across regions.

Key Features

• On-model photo generation – Transform flat product images into styled model photos

• Model diversity options – Choose from different body types, ethnicities, and aesthetics

• Background customization – Tailor settings to match brand or seasonal campaigns

• Batch processing – Create multiple images at once for larger product drops

Downside

Botika is optimized for visual output and does not support design or development workflows. Complex garments or items with layered construction may need extra editing to match styling expectations.

7. Raspberry 

Source: raspberry.ai

Raspberry is a visual design generation platform tailored for fashion creatives. It helps teams quickly create garment concepts using text prompts, sketches, or uploaded references. 

The tool supports flat sketches and photorealistic outputs, making it useful for mood boards, concept testing, and early design development.

Designers can adjust silhouettes, change trims or colors, and explore new design directions in a few clicks. Raspberry’s flexible editing tools allow users to refine generated images without needing to start over, which helps reduce repetitive tasks in the creative process.

Raspberry is best suited for teams focused on rapid visual exploration and early-stage ideation. It complements existing workflows by speeding up experimentation while giving teams more control over design variations.

Key Features

• Prompt-based generation – Create garments from short descriptions, sketches, or templates

• Visual editing tools – Tweak colorways, fabric types, and details without re-generating

• Variation controls – Quickly explore new versions of a concept across trims or cuts

• Photoreal outputs – Export on-model or flat visuals for concept boards or review sessions

Downside

Raspberry focuses on visual generation and early creative work but doesn’t include tools for collection planning or production handoff. Brands may still need other tools to manage assets or prepare deliverables beyond concept development.

8. NewArc

Source: newarc.ai

NewArc is a generative AI platform built for fashion design teams working on visual concepts. It helps users transform sketches, reference images, or text prompts into styled garment visuals that are consistent, high-quality, and aligned with brand direction.

The platform supports quick iteration and visual storytelling through model renders, editable backgrounds, and batch output tools, which are suitable for use in lookbooks, moodboards, and early-stage collection planning.

NewArc is especially helpful for brands that want to communicate design intent clearly across teams or to external partners without spending extra time on manual refinements.

Key Features

• AI-assisted concept generation – Turn sketches, text, or photos into visual fashion concepts

• Style consistency tools – Apply brand-aligned filters and visual cohesion across designs

• Model rendering and backgrounds – Preview garments in styled scenes or on virtual models

• Export-ready visuals – Generate images suitable for presentations or internal reviews

Downside

NewArc focuses on visual exploration and does not include technical development features like spec sheets or garment construction tools. Teams working on final production workflows may need additional platforms for those tasks.

9. Refabric

Source: refabric.com

Refabric is a generative AI platform designed for fashion brands looking to digitize and speed up the creative development process. It allows users to generate fashion visuals from prompts or references and explore collections through flexible, AI-assisted tools.

Designers can build moodboards, test variations, and organize ideas across seasons or categories, without the need for manual rendering. 

The platform focuses on helping teams visualize products earlier, align across departments, and reduce sampling delays.

Refabric is suitable for creative and merchandising teams working on seasonal line development or needing fast visual outputs for planning and collaboration.

Key Features

• AI visual generation – Create fashion designs from short descriptions or references

• Moodboard creation – Organize, edit, and share inspiration across projects

• Variation tools – Quickly explore different silhouettes, colors, and trims

• Collaborative workspace – Share visuals and context across departments or partners

Downside

Refabric supports the concept and planning stages but doesn’t include detailed development tools like fabric simulation or spec templates. Teams progressing to production will still need separate tools for technical execution.

Why Onbrand Is the Most Practical Fashion AI Tool for Design Teams

Unlike many AI tools that focus on a single step in the design process, Onbrand provides a unified space where creative teams can move from concept to visual execution without delays or tool switching.

What makes it practical is how closely it mirrors the way fashion teams actually work. Designers can sketch ideas, explore new styles, and develop looks in a visual-first interface that supports fast feedback and creative exploration.

Merchandisers and developers can join the process early by collaborating in the same space, keeping teams aligned from the start.

Instead of relying on a mix of sketching apps, file-sharing platforms, and visual planning tools, Onbrand brings everything into one environment built for speed and clarity.

The ability to test design directions, preview details, and keep versions organized in real time helps teams avoid slowdowns and rework.

For fast-moving teams that need structure without losing creativity, Onbrand is a practical choice. It supports the full flow of visual thinking and collaboration, while reducing the friction that often comes with traditional tools.

How AI Supports the Fashion Design Process

AI is changing how fashion teams design, plan, and develop products. Instead of replacing creativity, it supports it, making the fashion design process faster, more flexible, and easier to manage across teams.

Here’s how fashion AI tools are helping creative teams work better in 2025:

Design Assistance

AI-powered tools can create AI-generated sketches, colorways, and textures from simple prompts or uploaded references. This speeds up the sketch-to-image process and allows fashion designers to test ideas without slowing down.

Some platforms even build mood boards based on text inputs, which are helpful when teams need a quick starting point. These tools also utilize AI to help designers stay aligned with their creative vision from the earliest stages.

Fabric And Material Suggestions

AI models can recommend materials using details like cost, performance, or sustainability tags. These suggestions help teams make smarter choices early, before samples are made.

Some fashion design tools also simulate how fabrics look and move, giving designers a clear view without needing physical swatches. These advanced capabilities give teams more confidence in material planning and reduce the need for guesswork.

Trend Forecasting

AI fashion design tools can review data from social media platforms, search habits, and online sales to spot emerging trends. This trend analysis helps brands build collections that match people's wants, without relying on outdated reports.

It also supports better decisions in merchandising, planning, and content creation. Access to cutting-edge technologies allows teams to track real-time shifts and shape more innovative designs.

Product Development Automation

Some AI tools help with tasks like building flats, fit notes, or organizing tech pack details. When used with PLMs like Onbrand, they support faster turnaround and fewer back-and-forths between design and production.

Teams can spend less time on manual updates and more time refining their work. These tools help teams scale efficiently while staying focused on quality and customer engagement.

Merchandising And Visual Planning

AI helps brands decide what to release, where, and when, using past results and customer data. Some tools support virtual try-on features or help create digital looks for planning drops or collections.

These features also support digital marketing strategies by giving buyers clearer visuals and reducing guesswork during purchase.

How to Choose the Right Fashion AI Tool

With so many available tools, picking the right one depends on your specific needs, not just the features on a checklist.

Some platforms are built for early concept work, others for planning or marketing. Before signing up, it helps to think about where your team needs the most support.

Focus on the Workflow Gaps

Start by identifying where you or your team spends the most time. If concept creation takes hours, look for tools with AI-generated sketches or fabric simulation. 

If you're building marketing visuals or managing product photos, tools with virtual try-on features or model generation might be a better fit.

Match Features to Team Roles

Designers may need tools for sketching, mood boards, and early style preferences, while merchandising teams benefit more from trend forecasting or digital content tools. 

Choosing based on team function helps avoid overpaying for features you won’t use.

Check Integration and Collaboration Options

If you work with other designers, developers, or external vendors, prioritize tools with real-time co-editing, asset sharing, or PLM integration. 

This helps reduce delays and keeps everyone working from the same file or visual reference.

Keep It Simple for Smaller Teams

For individual designers or small brands, use tools that are easy to set up and use immediately. 

Many platforms now offer intuitive tools with minimal setup and built-in templates so you can move quickly without technical support.

Mistakes to Avoid When Implementing Fashion AI Tools

AI can support creative work meaningfully, but only if applied with the right expectations and setup. Here are a few common missteps to avoid when bringing AI tools into your fashion workflows:

Using Too Many Tools at Once

Trying every new platform is tempting, especially when they promise speed or automation. However, managing multiple systems at the same time can create more confusion, not less. 

Start with one tool that solves a specific issue, get familiar with it, and expand only if it fits your team’s flow.

Expecting One Tool to Do Everything

Most tools are built with a clear focus on either design, planning, or marketing, but not all three. Expecting a single solution to handle the full journey from sketch to shelf often leads to workarounds and wasted time. 

It’s better to choose tools that complement each other and cover different parts of your workflow.

Overlooking Team Workflow Fit

A feature-rich tool isn’t helpful if it doesn’t match how your team works. Look for solutions that support shared editing, allow quick handoffs, or offer integration capabilities with your existing PLM system. 

It won't get adopted if the tool adds more steps instead of removing them.

Ignoring the Learning Curve

Even the most user-friendly tools take time to explore. Teams need space to test new features, adjust routines, and ask questions. 

Rushing implementation often results in missed value or inconsistent use across departments.

Skipping Internal Alignment

When AI tools are brought in without a clear context, teams may resist the change. Make sure everyone understands the purpose and how it fits into their role. 

Even simple communication about what it does and doesn’t do helps build adoption.

Onbrand Is Built for the Way Fashion Teams Work Today!

AI is becoming part of everyday work for fashion teams, but it does not replace your team's creativity. Instead, it supports faster decision-making, reduces repetitive tasks, and helps teams focus more on the work that matters.

From early concept development to visual planning, the right tools offer innovative solutions that bring clarity and structure to fast-paced workflows.

The Onbrand AI Design is built with that goal in mind. It combines practical design features with AI-powered support, giving designers and teams one space to create, organize, and prepare for production.

Whether moving quickly across multiple products or managing everything independently, Onbrand helps keep your process consistent, visual, and easy to manage.

As more teams explore AI in their day-to-day work, the focus should not be on using every tool available. The priority is finding the few that remove friction, support collaboration, and make more room for creative thinking.

Start your 7-day free trial now and start saving 10+ weeks every year!

FAQs About Fashion AI Tools

Is there any AI tool for fashion design?

Yes. Several tools are designed to support the fashion design process using AI. Platforms like Onbrand and other AI fashion design generators help teams design fashion with visual concepts, realistic garment previews, and organized digital assets in one space.

How can AI be used in fashion?

AI is used across the fashion industry to improve design workflows, forecasting, and customer-facing experiences. From virtual fitting rooms and realistic images to supply chain optimization and content creation, AI opens up endless possibilities for brands to reduce manual work and respond faster to market shifts.

How do you use AI to create an outfit?

Designers can use AI algorithms and prompt-based tools to describe a look and receive visual outputs within minutes. These tools support the creative process by turning written concepts into visuals, helping teams test styling options while maintaining their artistic vision and benefiting from advanced design capabilities.

Which fashion brand uses AI?

Many brands now rely on AI for fashion marketing, personalized product recommendations, and digital styling. These tools support customer satisfaction by creating personalized fashion experiences, improving size accuracy, and enhancing virtual try-ons across digital platforms.