{"id":10315,"date":"2023-07-19T10:51:45","date_gmt":"2023-07-19T09:51:45","guid":{"rendered":"https:\/\/fortude1.wpenginepowered.com\/blog\/from-science-fiction-to-business-reality-making-ai-work-for-your-fashion-supplier-to-retail-business\/"},"modified":"2026-05-07T06:00:38","modified_gmt":"2026-05-07T05:00:38","slug":"from-science-fiction-to-business-reality-making-ai-work-for-your-fashion-supplier-to-retail-business","status":"publish","type":"blog","link":"https:\/\/fortude.co\/blog\/from-science-fiction-to-business-reality-making-ai-work-for-your-fashion-supplier-to-retail-business\/","title":{"rendered":"Making AI Work for Fashion Supplier to Retail Business"},"content":{"rendered":"

This time last year, the fashion industry was grappling with a severe supply chain crisis, dealing with deadstock taking up warehouse space, coming to terms with shifting consumer behavior and fluctuating demand. A year later, little has changed. While the fashion industry faces different iterations of the same challenges every year<\/a>, technology is rapidly evolving. The advent of ChatGPT, new breed of how Large Language Models (LLMs), and generative AI technologies have awakened the world to the transformative potential of artificial intelligence. While AI itself is not particularly new, business leaders are starting to recognize the technology\u2019s fashion industry potential.<\/p>\n

The third edition of the Fashion, Technology & Wine event series<\/a> sought to explore exactly how fashion brands can reimagine their value chain with AI and ML technologies. Held last month in New York, the exclusive forum organized by Infor, in collaboration with Fortude, opened up with an engaging session featuring Infor’s Sandeep Anand who called for fashion brands to ‘Think Big, Work Smart’ with AI and ML. Diving deeper into this area of innovation, this blog explores some of the most prominent use cases for AI technologies within the fashion value chain and how business leaders can adopt them and attempt to stay ahead of the competition.<\/p>\n

Artificial Intelligence and Machine Learning: Making sense of it all<\/strong><\/h4>\n

As technologies like ChatGPT take over the news cycle, you see the terms artificial intelligence (AI) and machine learning (ML) thrown around and often used interchangeably. As fashion brands look to tap into the benefits these technologies bring, we must take a step back and deepen our understanding of the distinctive differences between each of these terms. Artificial intelligence (AI)<\/strong> is an umbrella term that refers to the type of technology that mimics human intelligence and human cognitive functions like problem-solving and learning. While early AI tech was rules-based, limited in its scope of capabilities and often relied on significant human input, modern AI learns from historical data to optimize and solve complex tasks that were previously only performed by humans, such as facial and speech recognition, decision making and translation.<\/p>\n

Machine learning (ML)<\/strong>, on the other hand, is a branch of AI that enables your system to optimize itself by tapping into historical and current data (remember what happened yesterday is now part of history) to make more accurate predictions and minimize errors. Business leaders can leverage this in two ways. First, ML will be used to augment analytics, solutions, and draw out connections between data points and detect recurring patterns, anomalies, or cause-effect relations, which is particularly useful in trendspotting and demand forecasting. Second, businesses can leverage the pattern recognition capabilities of ML to replicate humans\u2019 cognitive skills. In practice this could be used to \u201clearn\u201d the linguistic patterns of human communication to understand and mimic them or detect visual patterns and relate them to pre-defined objects.<\/p>\n

The fashion industry\u2019s reliance on cycles and trends makes it the perfect candidate for innovation with AI. The industry’s recurring struggle with unsold inventory can also be addressed by AI\u2014from production to shipping, AI can help fashion leaders optimize every aspect of the product lifecycle. <\/p>\n

New product development with a (smarter) twist <\/strong><\/h4>\n

Trend forecasting is a key part of the product development process. This laborious process often involves scouring through trend reports, market analysis, social media data and consumer sentiments to inform designs for the next season\u2019s collection. Fashion brands can tap into AI to collect and analyze all these data sources to support the product ideation process. AI can work alongside human designers to draw inspiration from past product lines, trending styles and social media sentiments and convert these into new product designs and variations. This data also allows brands to decide how much of each design needs to be produced to keep in line with the predicted demand.<\/p>\n

It doesn\u2019t end there. AI can help combat fashion retail’s infamous returns problem<\/a> by helping brands sell it right the first time. Given that poor fit is the leading cause of returns, AI can be used to customize products for individual consumers at scale and meet their demand for personalization. Fashion businesses can also use AI-powered virtual sizing tools to customize products for individual consumers at scale.<\/p>\n

Redesigning the fashion supply chain with AI and ML<\/strong><\/h4>\n