AI or Artificial intelligence is starting to become the mainstream within the future of business and service and its now starting to become the standard within design.  Fashion and sportswear designers are starting to utilise AI to create ranges, predict trends and create new virtual fitting rooms.

AI has made a notable impact on how fashion is created, marketed, and sold with fashion brands creating new online fashion adverts using this new technology. Recently, a growing number of fashion brands have started to experiment with AI to design sportswear—pushing the boundaries of what technology can do in this creative space.

However, as with any emerging technology, there are huge risks and limitations that come with relying too heavily on AI in sportswear design. While AI can assist with efficiency, pattern recognition, and data-driven decisions, it is far from the perfect solution as its simply scrapping what’s been done before rather than looking at new innovation or creativity.

In this blog, we’ll explore how AI is being used in sportswear design, the potential benefits, and importantly why relying too much on AI might not be a good idea for the future of sportswear innovation.

AI in Fashion and Sportswear Design

Artificial intelligence in fashion is not a new concept. AI has already been integrated into various aspects of fashion design, such as trend forecasting, supply chain optimisation, and personalised shopping experiences. Now, it is beginning to make its mark in the actual creation of garments, including sportswear. AI is being used to analyse large datasets, including consumer preferences, body measurements, and even performance metrics, to create designs that could theoretically be both functional and stylish.

At Blue associates Sportswear, we are starting to receive designs from entrepreneurs that have clearly used AI to create a range of sportswear for their new start-ups. The design render quite often looks amazing as it’s been generated using existing creative designs and merged elements together to generate something that answered the brief of the brand, however there are some major , fundamental flaws with nearly every design we have received to date.

How AI Works in Sportswear Design

AI can be integrated into the design process in multiple ways. Here are some of the most common approaches:

1.Data-Driven Design:

AI can analyse large sets of data, including past consumer behaviour, sales figures, and fashion trends, to predict the kinds of sportswear products that are likely to perform well in the market. This helps designers understand consumer needs, material preferences, and design trends, which can guide the creation of new pieces. We think this is an excellent way to confirm any research a brand may have done and make sure their future collections answer the needs of the consumers and markets.

2.Pattern Recognition and Fabric Simulation:

AI can speed up the process of designing sportswear by recognising patterns from existing designs and generating new iterations based on those patterns. This can help designers create functional and ergonomic designs with minimal human input. Additionally, AI algorithms can simulate how fabrics will behave under various conditions (e.g., stretching, sweating, and temperature changes), helping designers select the best materials for a particular garment.

This aspect has some real flaws and needs to be directed incredibly accurately by the designer to make sure the output from AI is actually realistic for the end user or athlete. Again, trawling the internet and pulling data from key sites to make decisions based on popularity might now address the actual requirements for the athlete. There are also a lot of sportswear brands that promote a technology of fabric based on price or accessibility rather than focus on true performance that screws the output too.

3.Customisation:

AI-powered design tools allow for highly personalised sportswear, based on an individual’s body measurements and performance needs. For example, a runner may want shoes or apparel designed with specific types of cushioning, support, or breathability tailored to their running style, which AI can deliver with impressive precision.

Again, this data will be based on trawling the popular data and configure this data to the end users requirements. It won’t take into account the commercial aspect of manufacturing the end product. Foor instance, the date might be drawn from Nike’s best selling running shoe where Nike produce 100,000 pairs that are sold around the world. If a smaller brand wants to utilise this data to copy the statistics and guarantee a product will work, they need to take into account who will be producing this and will it fit into the manufacturer’s MOQ or skill base?

4.Supply Chain and Production Efficiency:

Beyond design, AI can optimise production processes, from fabric cutting to inventory management. AI-powered systems can predict demand, manage stock levels, and even guide the production process, ensuring faster turnaround times for new collections.

This is a great way to optimise the manufacturing process and reduces waste too. It can make the whole process become more environmentally friendly if the focus is based on reducing waste and looking at the carbon footprint of a product.

5.Sustainability:

AI is also being used as a solution for more sustainable fashion practices. By analysing material waste, carbon emissions, and energy usage, AI can help designers and manufacturers make more eco-friendly decisions. AI can even suggest alternative, sustainable materials for sportswear design that meet the same functional requirements as traditional materials.

AI is also being adopted to calculate the carbon footprint of a product and can look at alternative solutions to reduce the footprint.

The Benefits of Using AI in Sportswear Design

AI offers numerous potential advantages for the sportswear industry:

• Speed and Efficiency: AI can generate designs quickly and efficiently, dramatically reducing the time it takes to bring a product from concept to market. By streamlining tasks like fabric simulations, pattern generation, and production planning, AI can increase the overall efficiency of the design process.

Tools such as Clo3d help create a virtual garment that can be sent directly to factories for them to understand the fit and drape and extract the precise patterns, reducing the need to sample and approve the fit.

• Data-Driven Decision-Making: By analysing vast amounts of data, AI can provide designers with insights that might otherwise be difficult or time-consuming to uncover. These insights can lead to more informed decisions about colour choices, fabric selections, and sizing, ensuring that the final product meets the needs of consumers.

Remember that this data is using existing data and current affairs to predict the future trends. Generally, this will be fairly accurate depending on the data it is using to predict these trends.

• Cost Reduction: AI can help reduce costs by optimising production methods, minimising waste, and improving supply chain efficiency. In a highly competitive market like sportswear, where margins are often tight, this cost efficiency can make a significant difference.

• Personalisation: As mentioned, AI can create hyper-personalised products for consumers, which could revolutionise the sportswear market. Custom-fit clothing and footwear designed specifically for an individual’s body shape or sporting needs could become the new norm. This will be the future of fashion and sportswear and we predict the optimal future would be a 3D printed garment where you design your products online, click buy and minutes later, your house 3D printer, creates your product, reducing waste and carbon footprint as the products is printed in your home.

Why AI in Sportswear Design Might Not Be the Best Idea

Despite the obvious, quick fix benefits, there are compelling reasons why designing sportswear using AI might not be the best long-term strategy for the fashion industry. Here are our key concerns:

1. Human Creativity

One of the most significant drawbacks of using AI in sportswear design is its lack of true creativity. While AI can generate designs based on data, it does so without the human touch that is essential in creative fields.

Sportswear design is a mix of creative style and problem solving. A sportswear designer needs to understand the athletes requirements with regard to comfort, durability, fit, stretch, climate, conditions, required features etc. These are the key principled a designer starts with and solves before the style is addressed.

Sportswear design, particularly in the high-performance sector, requires a deep understanding of both form and function. For example, designing a high-quality, ergonomic pair of running shoes isn’t just about making something that looks good—it’s about knowing how materials interact with the human body, how they impact performance, and how they can withstand physical stress. While AI can help with optimisation, it can’t replace the hands-on experience and human intuition that designers bring to these challenges.

Fashion designers bring something invaluable to the table too. Intuition, creativity, and an understanding of culture, emotions, and aesthetics. AI, on the other hand, works based on algorithms, patterns, and historical data, which means it’s often confined to rehashing existing ideas rather than creating truly innovative designs.

2. Innovation

AI is often praised for its ability to analyse and predict based on data. However, an over-reliance on data can stifle creativity and innovation. AI can only work with existing patterns and trends, meaning it lacks the ability to think outside the box. In the world of sportswear, where trends constantly evolve and consumer needs shift, sticking strictly to data-driven approaches may result in repetitive designs that lack any originality.

If sportswear brands begin to rely too heavily on AI to generate designs based on past sales data or consumer preferences, there’s a risk of creating a uniform, predictable market where innovation takes a back seat.

Can you imagine Nike, Adidas and Under Armour all used AI to create their next running shoe based on identical data based on the market at that particular point. They could easily release an identical shoe with a different logo on the side. All of a sudden, the world becomes bland with brands churning out identical fodder rather than pushing the boundaries of creativity and innovation.

CHT GTP now has a design tool that can create product designs, logos and artwork based on the instruction you input. We used this to create a sports bra design and asked it to use data to create one based on the best selling bras available. The image for this blog is the outcome. It’s an OK design, but it’s nothing new. It doesn’t take into account the required support or offers any innovation in terms of creating a product that improves the existing best product. It also doesn’t explain the fabrics, stretch, restricted stretch or support. It’s purely a sports bra that looks like existing best sellers but emits any engineering to develop a product that will work.

3. Limited Understanding of Emotional and Cultural Context

Designs are not just functional or aesthetically pleasing—they also carry emotional and cultural weight. For example, sportswear often represents more than just a piece of clothing; it embodies an athlete’s identity, ambitions, and values. A brand like Nike, for instance, connects with consumers not just through the quality of its products but through the powerful emotional messaging and culture it has built around its apparel and brand.

Patagonia is probably the best example of this, with their brand heavily routed into protecting the environment while creating credible, outdoor products. The culture and DNA of the brand needs to be understood and built into each product, something AI wouldn’t understand as it wouldn’t be able to extract this DNA and Culture.

AI may be able to optimise for physical comfort, performance, and even style preferences, but it is unlikely to capture the emotional and cultural subtleties that make sportswear truly resonate with a particular audience. A piece of sportswear designed by an AI algorithm may not have the same emotional appeal as one designed by a human designer with a deep understanding of the social and emotional contexts surrounding sports and fitness.

4. Ethical and Sustainability Issues

Although AI has the potential to help create more sustainable sportswear by reducing waste and optimising materials, it could also contribute to ethical dilemmas in other areas. For instance, the reliance on AI-driven design could lead to job displacement within the design and manufacturing community, reducing opportunities for skilled human designers in the industry.

Moreover, AI systems rely on large datasets, which may sometimes include biased or incomplete information. If AI algorithms are trained on datasets that do not reflect the diversity of body types, cultural preferences, or performance needs, they may inadvertently perpetuate stereotypes or fail to meet the needs of underrepresented groups in sportswear design.

Niche markets would start to be ignored and products wand brands would start to become standardised based on the popularity of the data it’s trawling.

5. Quality Control

Sportswear, especially in high-performance categories like running shoes, compression gear, or mountaineering gear needs to meet very specific standards of quality and performance. While AI can help with optimising designs, it is not foolproof. Small errors in the algorithms or overlooked aspects of the design process could lead to products that fail to meet athletes expectations or even cause injury or potentially death.

In industries where precision is key to product performance, human oversight remains essential. Designers can spot potential issues that an AI system may miss, ensuring the final product is both functional and safe to use in extreme conditions.

New technologies that might perform better than existing ones wouldn’t be taken into account by AI as it wouldn’t be aware of these or refuse to take it into account as the data surrounding it might still be limited due to its freshness.

It’s all a balance

AI is undoubtedly transforming many industries, and sportswear design is no exception. From accelerating design processes to helping optimise production, AI offers several potential advantages for the sportswear sector. However, the reliance on AI in the creative aspects of sportswear design raises concerns about the loss of human creativity, innovation, and emotional resonance.

Instead of viewing AI as a replacement for human designers, the ideal approach would be to integrate AI as a powerful tool that complements human creativity. Designers can leverage AI’s data-driven insights and pattern recognition to enhance their work, but the core elements of creativity, culture, and intuition will always need a human touch.

We believe the key to successful sportswear design will be striking the right balance between cutting-edge technology and human expertise. By doing so, the sportswear industry can ensure that it continues to innovate while staying connected to the emotional and functional needs of its customers.

Get in touch if you are interested in creating innovative sportswear utilising our experience within the market since 1997