It's mid-July, and the yacht on the Hudson is called Praying for Overtime -- an apt name for the boat hosting the Laws of Motion event, where founder Carly Bigi and her crew's passion for beautiful, perfect-fitting clothing bubbles up alongside the Aperol spritzes at the bar. Bigi herself wears a vibrant pink romper that manages to strike the balance between totally chic and still professional, a throughline for the collection, and the pieces on deck: a rack of white with subtle feathers ringing sleeves and hems. Laws of Motion's styles are modern takes on timeless silhouettes, but that's where any resemblance to other brands begins and ends. That's because Laws of Motion, which counts Rent the Runway co-founder Jenny Fleiss among its investors, relies on data to help customers find the ideal fit and reduce the impact of fast fashion (there's an estimated 92 million tons of textile waste each year, globally). Related: This Fashion Founder's Company Will Take Back Any Piece of Clothing for Any Reason.

The worldwide need for clothing will propel the apparel industry from US$1.5tn in value in 2020 to US$2.25tn by 2025. The growth of the human population and its demand for clothing is a foregone conclusion, but the ability of manufacturers to meet expectations without overextending themselves is not. Like every other industry, apparel and textiles must learn to serve a growing population while remaining aware of the planet's finite resources. Leveraging artificial intelligence (AI) to meet demand without exceeding the available supply is nothing new. How does it apply to apparel manufacturing?

The use of artificial intelligence (AI)-style'sewbots' that can replace human sewers and other robotics look set to transform the apparel supply chain and facilitate reshoring or near-shoring to developed countries currently reliant on lower income outsourcing hubs, maybe thousands of kilometres away from buyers. Online merchants and small new brands owned by millennials are already driving reshoring by claiming it involves a lower environmental footprint through reduced transport and less inventory waste. Palaniswamy'Raj' Rajan, chairman and CEO of Softwear Automation, based in Atlanta, Georgia, US, whose sewbots can manufacture t-shirts in a fully automated process, warned that major and more established brands will remain "laggards not leaders" in technologically-driven reshoring. They will wait for a critical mass to develop reshored production, before taking the plunge and disrupting established supply chain routes to market, he predicted. But, stressed Rajan, the artificial intelligence (AI) technology that can deliver this vision is becoming available for the apparel sector: "Our sewbots take cut fabric pieces as input, then put them through a series of automatic steps, and output a finished t-shirt," he told Just Style. He explained that software automation technology is a combination of "proprietary advanced robotics, computer vision, AI, and IoT [internet of things] technologies" enabling on-demand production at scale.

Apparel companies hit by the coronavirus pandemic have been tapping artificial intelligence technology to boost sagging sales, using it to predict the designs and colors that will come into trend. One provider of such technology is Tokyo-based startup Neural Pocket Inc., which runs a system that automatically collects big data related to clothing on various fashion websites, Instagram and other social networking services to analyze day-to-day changes in trends. The company predicts the next hit products by analyzing data on colors, designs and clothing lengths. Such an approach using AI technology is new in the apparel industry, which generally relies on the experience and instinct of designers to predict trends. But as the coronavirus pandemic takes its toll on retailers, demand is growing to efficiently predict the next hot items in fashion.

Artificial Intelligence and Machine Learning are the two progressive technologies that are being utilized for building advanced solutions. These are the ground-breaking advances that power cutting edge ventures. AI supports the capacity of machines to emulate human-like psychological capacities. Under this technology, machines can perform undertakings that ordinarily require human knowledge. With this, machines can learn, take care of issues, perform keen assignments, and the sky is the limit from there, much the same as people do.

A parade of models struts down the catwalk in garments that take the audience's breath away – a collection that is iterative yet wholly unique. As is customary at the close of the show, the designer appears on the runway as the crowd explodes in adulation. After all, the fashion collection was designed by artificial intelligence. Digital tools are poised to completely make over the apparel industry. AI is serving as a game changer for everything from apparel design to trend spotting.

It would be nearly impossible for one person – or even a dedicated team – to tease out meaningful trends and insights from such an onslaught of visual data. For an AI (properly trained with the right algorithms), it's a piece of cake, according to Kavita Bala, chair of the computer science department at Cornell University. She and her team used artificial intelligence (AI) to create a map of style trends and influencers by analyzing 14.5 million photos of people shared publicly on social media. Bala's StreetStyle project can answer questions like: How many people wear black in Los Angeles today, compared with two years ago? Or, where in the world is the hijab most prevalent?

If there's any doubt as to why "big data" has become as ubiquitous in business as pens, chairs and coffee mugs, look no further than the margins. Since becoming the buzzword of the decade, big data has given countless businesses huge competitive advantages by redefining the quality of the information at their fingertips and the speed at which they can react. So why have apparel brands lagged in doing the same? In many cases, identifying the "next big thing" -- what will sell, and the rate at which it will fly off the shelves -- is still steeped in guesswork and unsupported instinct. For brands, the use case is abundantly clear.