As consumers grow increasingly frustrated with garments that fit nowhere near the advertised size, a new wave of artificial‑intelligence (AI) technology promises to tackle the problem at its source – the production line.
BBC Investigation Highlights a Persistent Problem
The BBC’s recent investigation examined how many shoppers abandon purchases or return items because of inconsistent sizing. In women’s wear, return rates linked to poor fit can exceed 30 %, costing retailers billions and contributing to unnecessary waste.
Startup Founder Sees AI as a Fix
Phoebe Gormley, 31, the founder of AI‑driven sizing startup FitLogic, argues that the technology can correct sizing errors before garments ever reach store shelves. “We are not data scientists by training, but we have assembled a team that can translate raw production data into actionable insights,” Gormley told the BBC.
How the Technology Works
FitLogic’s platform ingests three key data streams:
- Return analytics: Detailed information on why customers send items back, including specific fit complaints.
- Fabric behaviour modelling: Simulations that predict how different textiles stretch, shrink, or drape under various conditions.
- Production‑line measurements: Real‑time data from cutting, stitching and finishing stages, captured by sensors and computer‑vision systems.
By correlating these inputs, the AI identifies systematic sizing deviations and recommends adjustments to pattern grading, cutting tolerances, and quality‑control checkpoints.
Potential Industry Impact
Early trials with several European apparel brands have shown promising results. One partner reported a 22 % reduction in size‑related returns within three months of implementing the system, while also shortening the time needed to finalize new size charts.
Beyond cost savings, the technology could help the sector meet sustainability goals. Fewer returns mean less transportation, lower landfill contributions, and a decrease in the need for over‑production to compensate for uncertain demand.
Challenges and Skepticism
Despite the optimism, experts caution that AI is not a silver bullet. “Data quality is paramount,” notes Dr. Elena Martínez, a textile engineering professor at the University of Milan. “If the input from factories is inconsistent, the output will be unreliable.” Moreover, smaller manufacturers may lack the resources to integrate sophisticated sensor networks required for real‑time monitoring.
There is also the question of consumer perception. While AI‑generated size recommendations could improve fit, shoppers may remain wary of algorithms that dictate personal style choices.
Looking Ahead
FitLogic plans to expand its platform to include menswear and plus‑size ranges, sectors where sizing inconsistencies are equally pronounced. The company is also exploring partnerships with major e‑commerce platforms to embed AI‑driven size suggestions directly into online shopping experiences.
If the technology scales successfully, it could mark a turning point for an industry long plagued by the “size‑it‑right” dilemma, delivering a more reliable fit for consumers and a greener, more efficient supply chain for brands.
