How AI is changing trend forecasting

How AI is redefining trend forecasting: From prediction to strategic innovation

By Lizzy Bowring

Trend forecasting is no longer a creative approach to predicting the future; It has become a strategic and formulaic process. Just think of trend forecasting as looking into a crystal ball and consulting a fortune teller to predict what's new, what's next, or even the best-selling colors and materials for the next six months, a year, or up to ten Years. Or based on the current question, “Will bohemian styles dominate next spring?”, it could be a definite “yes.” It's more complex. Predicting fashion trends requires a combination of creative instinct and precise analysis. This intricate practice, essential to future planning in any creative field, has evolved from an exclusive space led by seasoned fashion insiders to a dynamic space driven by digital trendsetters, influencers and fast-moving social media trends being affected.

Trend forecasting combines the analytical with the intuitive, predicting future trends by analyzing behaviors across different industries. It combines rigorous data analysis with creative intuition to anticipate cultural, consumer behavior and technology changes. This blend of “math” and “magic” turns trend forecasting into a precise science that balances creativity with data-driven decision-making.

The true value of incorporating AI into trend forecasting lies in its ability to transform large amounts of information into actionable insights. Since 2021, AI has transformed trend forecasting, allowing brands to quickly differentiate between short-lived fads and lasting trends. AI tools analyze large data sets and provide precise insights that improve decision-making, estimate consumer preferences and predict demand changes in real-time.

Artificial intelligence is a transformative force that is reshaping the future of the design industry. In particular, the trend forecast is being strategically rethought. Despite the power of AI, the irreplaceable human touch remains crucial in trend forecasting. The emotional and aesthetic nature of the fashion industry presents unique challenges that can only be partially addressed through pure data analysis. By integrating AI's data results with deep industry knowledge and creative insights, experts can focus on strategic activities and ensure forecasts are consistent with both current circumstances and future opportunities.

The Impression delves deep into the unique osmosis of AI's advanced capabilities, examining how it will shape the future of trend forecasting and how the workforce is adapting to using this tool.

The benefits of using AI

The true value of incorporating AI into trend forecasting lies in its ability to transform large amounts of information into actionable insights. AI has transformed trend forecasting, allowing brands to quickly differentiate between fleeting fads and lasting trends. Platforms like Livetrend, WGSN, Heuritech and Seymour Powell use AI to analyze large data sets, providing precise insights that improve decision-making.

Key Benefits of AI in Trend Forecasting:

• Fast data analysis: AI tools can scan thousands of runway images in moments and extract key trends in color palettes, fabrics and designs, allowing designers to quickly adapt collections and gain creative time.
• Insights into consumer preferences: By analyzing global data, AI identifies different consumer preferences across demographics, enriching the design process and ensuring collections reflect a comprehensive range of tastes.
• Social media and consumer feedback: AI models analyze millions of images and social media posts every day, helping brands predict which products will resonate with consumers. This real-time insight is critical, as trends can change dramatically from one season to the next.
• Prediction accuracy: AI helps understand trends through clickstream data and track online searches and identify rising trends before they peak. This foresight enables strategic inventory management and reduces textile waste by aligning production with expected demand.

Barbara Maioccho, CEO of Livetrend, emphasizes the transformative role of AI: “AI-powered forecasts predict trends more accurately and help brands find the most relevant trends in the fast-moving digital world.” With a reliability rate of 93%, Livetrend AI delivers highly reliable information, striking the right balance between market trends and consumer appeal.

While AI dramatically improves data processing capabilities, the synergy between AI and human creativity is critical. Human experts interpret the nuanced cultural and emotional factors that AI may miss, ensuring predictions are both data-driven and highly contextual. This combination is critical to developing actionable strategies that resonate with consumers and provide competitive advantage in a rapidly evolving market.

The future of AI in trend forecasting

Looking to the future, the transformative power of AI in trend forecasting is immense. AI tools provide quantitative support to the qualitative insights of expert forecasters, enabling brands to anticipate and respond to consumer desires with unprecedented speed and accuracy. This ensures a competitive advantage in a rapidly evolving market and opens up new avenues for innovation and growth.

A prime example of this transformative force is Heuritech, a pioneer in AI-driven trend forecasting. Founded in 2013 by machine learning experts Tony Pinville and Charles Ollion, Heuritech uses proprietary image recognition technology to analyze around three million fashion images on social media every day. By focusing on elements such as color, texture and silhouette, Heuritech categorizes trends by geography and seasonal popularity, providing brands with detailed insights into new styles. Their approach, which segments the data into “trendy,” “trendy,” and “mainstream” consumer panels, allows brands like Dior, Rabanne, Prada, Louis Vuitton and New Balance to capture early signals of upcoming trends and strategize their collections .

With machine learning, you can predictably know where to put up to 80% of your collection. You're left with 20% of the collection to know what to innovate. There's now a lot more white space for the design team to be more creative.

– Brad Lacey, vice president of design lifestyle footwear

As technology advances, trend analysis methods will evolve, promising even more precise forecasting tools. Future developments could introduce advanced predictive models that incorporate a wider range of variables, from environmental impacts to political changes, providing a more holistic view of the future. When companies understand the scope and potential of trend forecasting, they can strategically position themselves to benefit from upcoming trends and navigate the complexities of the global marketplace.

A recent McKinsey survey found that most fashion executives (73%) view General AI (GenAI) as a key business priority in the coming year. In addition, the McKinsey report “Unlocking the Future of Fashion” predicts that GenAI could increase the apparel, fashion and luxury industries’ operating profits by an estimated $150 billion to $275 billion over the next three to five years.

From a pedagogical perspective, future trend researchers must understand and use AI technologies. AI has become an essential resource for trend forecasters, allowing them to analyze and process large amounts of data from various sources, identifying new patterns and trends more quickly and effectively. Integrating the knowledge and use of AI technologies into educational programs for future trend forecasters is critical to preparing them to successfully address the challenges of the modern world.

As AI tools continue to evolve and become more adept at dealing with complex data sets, the enduring value of human insight ensures that fashion forecasting remains both an art and a science. The creativity and cultural sensitivity of human experts are essential to translating cold, complex data into vibrant, vibrant fashion trends that resonate with consumers' lives and values. By incorporating ethical considerations and adding AI to curricula, the fashion industry can harness the full potential of AI responsibly and innovatively, ensuring that integrating this technology into fashion forecasting leads to positive and inclusive outcomes for all.

The central theses

The role of AI in trend forecasting: AI has become a transformative force in the design industry, especially in trend forecasting. It improves the ability to analyze large amounts of data and provides actionable insights that help distinguish between fleeting fads and lasting trends.

Benefits of AI integration: AI tools like Livetrend, WGSN, Heuritech and Seymour Powell can quickly process large amounts of data, from runway images to social media posts. This helps brands predict consumer preferences, streamline design processes and reduce time to market.

The impact of AI on consumer insights and market adaptation: AI helps understand consumer behavior and preferences by analyzing social media reactions, online reviews, and shopping patterns. These real-time insights enable brands to quickly adapt to changing trends and strategically manage inventory.

Future possibilities: The future of AI in trend forecasting looks promising, with potential advances in predictive models that take into account a broader range of variables. This could lead to more precise and holistic forecasting tools that take into account environmental, economic and political factors.

Pedagogical and ethical considerations: As AI becomes more integrated into trend forecasting, it is critical to consider ethical considerations such as privacy and algorithmic bias. In addition, integrating AI technologies into educational programs will prepare future trend forecasters to use these tools effectively.

Strategic and sustainable fashion: By closely aligning production with forecast demand, AI helps mitigate overproduction, a significant problem in the fashion industry. This not only maximizes business results but also promotes sustainability efforts.