Artificial intelligence is moving deeper into the fashion industry, and Google is giving designers a new way to experiment with collections before garments and runway sets are physically produced.
Image Courtesy : runway7fashion.com
Ahead of New York Fashion Week's Spring/Summer 2027 season, Google partnered with American designers Jane Wade and Sergio Hudson to develop customized AI-powered tools inside Google Flow, the company's creative studio for generating and editing images and video. The collaboration gave each designer a specialized workflow designed around a different challenge: Wade focused on styling and visualizing complete looks, while Hudson used AI to explore runway staging and production concepts.
The collaboration represents a notable expansion of Google's work with creative professionals. Rather than presenting Flow simply as a general-purpose image and video generation platform, Google worked directly with the designers to create tools tailored to the realities of fashion production.
The project was developed through Google's Envisioning Studio, whose team worked alongside Wade and Hudson to understand how they prepare collections and identify parts of the process where AI visualization could be useful. The resulting tools were designed to help designers see and modify ideas earlier, before committing significant amounts of time, fabric, labor and production resources.
For Jane Wade, the technology focuses primarily on the styling process.
Designing a collection involves considerably more than creating individual garments. Designers and their teams have to determine how pieces work together, what colors and fabrics complement one another, which accessories complete an outfit and how the finished look will appear on a model.
Google created a Flow-based tool that allowed Wade to virtually experiment with those combinations.
Instead of having to physically produce every potential combination before evaluating it, Wade could use AI-generated visualizations to explore different head-to-toe looks. The system could help her experiment with elements such as fabrics, colors, accessories, beauty direction and layered outfits while providing visual references for how the overall styling could come together.
That could be particularly useful during the early stages of a collection, when designers are making dozens or even hundreds of decisions that eventually have to converge into a cohesive runway presentation.
The idea isn't to have AI independently design a fashion collection. Instead, Google's approach puts the technology in the position of a visualization and experimentation tool, allowing the designer to make the creative decisions while using AI to rapidly explore possibilities.
Wade's workflow also included model-card-style visualization, giving her another way to consider how particular combinations might appear when translated from an individual garment into a complete runway look.
Sergio Hudson's use of Flow addressed a different part of the fashion process.
For Hudson, Google developed a tool focused on runway staging. A fashion show requires designers to consider the physical space, lighting, props, model movement and overall presentation, all while working within production constraints.
Rather than waiting until a physical set is constructed, Hudson could use AI visualization to experiment with those elements beforehand.
The tool allowed him to explore concepts involving venue dimensions, lighting, props and model movement while also considering budget limitations. That gives a designer an opportunity to see how different staging ideas could work together before spending money on construction and production.
For fashion designers, that kind of visualization could become increasingly valuable.
Runway shows are highly visual productions, but building physical environments can be expensive and time-consuming. A designer may have an idea for a dramatic backdrop, a particular lighting arrangement or a specific way of moving models through a space, only to discover during production that the idea is impractical or too expensive.
AI visualization can provide an earlier checkpoint.
A designer can test several concepts digitally, identify the ideas worth pursuing and then bring the strongest concepts to a production team for physical execution.
Google's collaboration with Wade and Hudson also demonstrates how its Flow platform has evolved.
Flow was initially introduced as a creative tool for filmmakers, but Google has since expanded it into a broader AI creative studio with image and video generation, editing capabilities, project organization and increasingly customizable workflows. In May, Google announced tools that allow users to create bespoke workflows using natural language, without traditional coding.
That ability to create customized tools is particularly relevant to the fashion collaboration.
Fashion designers don't necessarily need a generic AI application. Their workflows can be highly specialized, with different designers having completely different requirements. A couture designer, a sportswear designer and a runway-production team may all use visual tools in very different ways.
Google's approach effectively allows the technology to be shaped around those individual workflows.
The fashion partnership also builds on Google's broader efforts to establish relationships with American designers.
The Council of Fashion Designers of America and Google launched their second Fashion Fellowship in 2025, providing five American brands with $60,000 grants, mentorship and collaboration with Google's product and innovation teams to support their September 2026 collections. Jane Wade and Sergio Hudson were among the participating designers, alongside Eckhaus Latta, Zankov and Tanner Fletcher.
The fellowship was designed to give designers access to Google's technology and expertise while exploring ways technology could be applied to fashion design.
The Flow collaboration takes that relationship from general technology mentorship into a more hands-on experiment with generative AI.
The timing is also significant because the September 2026 fashion season has placed considerable attention on creativity, experimentation and the changing role of technology in the industry.
New York Fashion Week's Spring/Summer 2027 collections included established fashion houses as well as independent designers, with technology increasingly becoming part of the broader conversation surrounding how collections are conceived, presented and marketed.
Sergio Hudson's own position in the fashion industry makes his involvement particularly notable.
Hudson has built a reputation around polished American sportswear, tailoring and strong silhouettes and has dressed prominent figures including Beyoncé and Michelle Obama. His February 2026 collection marked his tenth year in business and featured tailored suits, dramatic gowns and sculptural silhouettes.
Using AI as part of the preparation for a collection therefore provides an interesting contrast between traditional fashion craftsmanship and emerging digital tools.
The physical garments still have to be designed, constructed, fitted and produced. Models still have to wear the clothing. Stylists, makeup artists, hairstylists, photographers, set designers and production crews remain essential to a runway presentation.
What changes is the amount of experimentation that can happen before those physical stages begin.
That distinction is important because AI-generated fashion imagery has raised questions about whether technology could eventually replace portions of the creative process.
Google's collaboration with Wade and Hudson instead presents a different model: AI as an extension of the designer's existing creative process.
The designer establishes the aesthetic direction. The designer determines which ideas are worth pursuing. The designer evaluates whether an AI-generated concept actually fits the collection.
AI simply makes it possible to visualize and iterate on more possibilities in less time.
There are also practical advantages to being able to identify problems earlier.
If a particular combination of garments does not create the intended balance, a designer can experiment with alternatives digitally. If a runway concept requires an expensive physical structure that does not work within the available budget, the designer can test different staging approaches before production begins.
For independent designers in particular, that could potentially provide a way to explore ambitious concepts without physically building every version.
Hudson's tool specifically incorporated budget parameters into the visualization process, demonstrating how Google's experiment is intended to go beyond generating attractive images. The objective is to connect creative visualization with real production considerations.
That could ultimately be one of the more important directions for AI in fashion.
The technology becomes more useful when it understands the constraints surrounding a creative decision.
Fashion is filled with those constraints. Fabric availability, production costs, manufacturing timelines, model availability, venue dimensions, lighting requirements and shipping schedules can all affect whether an idea becomes a finished product.
AI cannot eliminate those realities, but visualization tools can potentially help designers account for them earlier.
Google's experiment also illustrates the broader movement toward specialized AI tools.
Instead of asking users to adapt their creative processes to generic software, technology companies are increasingly attempting to build AI systems around the specific needs of professional industries.
That approach is already appearing in filmmaking, music, advertising and other creative fields. Google has positioned Flow as a platform that can support different kinds of creative work, while its customizable Tools feature allows users to build specialized workflows using natural-language instructions.
Fashion could become another major testing ground for that concept.
The industry is particularly well suited to visual AI because so much of its creative process depends on imagining something before it physically exists.
A designer can imagine a garment, a complete outfit, a model presentation or an entire runway environment long before the public sees it. Generative AI provides a way to translate some of those ideas into visual references almost immediately.
That doesn't eliminate the need for physical craftsmanship. In many cases, it could make the transition from concept to physical creation more deliberate.
The collaboration between Google, Jane Wade and Sergio Hudson therefore represents something larger than an AI-generated fashion image appearing during New York Fashion Week.
It demonstrates an experiment in changing the workflow itself.
Wade's tool focuses on answering a question fashion designers constantly face: What will this collection look like when all of the individual pieces come together?
Hudson's tool tackles another: What will the show look and feel like once the garments, models, lighting and environment are combined?
Both questions traditionally require a significant amount of physical preparation and imagination.
Google Flow provides another layer between the initial idea and the finished product.
For now, the tools are being presented as beta-style planning and visualization systems rather than replacements for fashion designers or production teams. The physical fitting, construction and creative decision-making processes remain essential.
But the experiment points toward a future in which designers may routinely use AI throughout the earliest stages of collection development.
Instead of creating one concept and gradually refining it, a designer could explore dozens of visual directions, compare different styling combinations and simulate a runway environment before committing to production.
That could make fashion design more iterative, more visual and potentially more efficient.
The bigger question will be how designers choose to use that capability without losing the individual creative identity that makes fashion distinctive.
Google's partnership with Jane Wade and Sergio Hudson suggests that the company sees an opportunity to make AI part of that creative process—not by replacing the person behind the collection, but by giving designers a new digital space in which to experiment.
As AI continues moving from the computer screen into the studios of professional creatives, New York Fashion Week may offer an early glimpse of what the next generation of fashion production could look like: human designers making the creative calls, with AI helping them see possibilities that previously existed only in their imagination.