Advancement in Productivity and Designing

Generative AI supports retailers in fast-tracking productivity, driving sales, and standing out from the competition. The adoption of AI at the global level is estimated to hike from 40% in 2023 to at least 80% in 2026. In the new future, there will be a huge opportunity for mankind to create an environment where generative AI tools will work with a human team. For instance, in 2022, the American lingerie line Adore Me opted to use the GPT text generator CoWrite to create product descriptions. This act has saved the brand’s content creators 35 hours of work in a month.

In addition to production, retailers have the opportunity to use AI for store design. Alongside its automatic texting and support, AI also provides a vast group of assistance. Applications such as DALL-E, GPT-4, Stable Diffusion, and Midjourney have the tools to redefine a store design by inputting unstructured data (in images, videos, and text) and getting results of 3D designs and in some cases, realistic virtual models. Design companies such as the Lionesque Group and MG2 are working with retailers to create exquisite stores. Moreover, MG2 developed a project using Midjourney that involved visuals, architecture, and merchandising in 8 hours, which would take a week to accomplish in the real world.

This generative AI has also inspired audiences to try it. There is one interesting proposal created by a consumer who used generative AI to see what “Chanel’s utopian house” looks like. Zara, by using AI, has maintained to have 85% more capacity in case of in-season adjustments.

Enhanced Shopping Experience

Using AI text generators such as ChatGPT is not new in the world. According to WGSN, it has been a hot topic since 2016. However, it was the COVID-19 pandemic that made everyone prefer online services as the main source. Around 85% of global customers would like to receive messages rather than getting phone calls or emails. In the coming years, AI chatbots will be reintegrated into the retailers’ new ways to interest customers other than purchases by providing customised content in a shorter span for everyone.

Virtual clienteling has become an important phenomenon in luxury retailing. In April 2023, Ermenegildo Zegna partnered with Microsoft to create an online clienteling experience platform, Zegna X. This latest service is combined with an AI-supported recommendation system that enables customers to receive notifications on recent products and utmost 49 billion potential combinations of outfits through WhatsApp, phone text, or emails. Zegna X has earned around 45% of revenue 75% more than the customers spending in store.

Zalando GmbH announces that it will launch an advanced chatbot using ChatGPT in the spring of 2023. Whereas Kering launched KNXT, an OpenAI’s ChatGPT-powered platform, to let its customers buy products with crypto wallets as a way to bridge Web3 with AI.

Forecasting Commerce

It was anticipated that with generative AI, brands will be able to choose future trendy products before even they knew it. The latest version of GPT-4 can suggest recipes based on simplified pictures of the food. Therefore, the next insight for retailers is to connect the consumers with their likes using promotions, recommendations, and offers.

Walmart enhanced its Text to Shop platform with the assistance of GPT-4, which supports the outlet to widen its digital innovations. At the same time, Expedia added ChatGPT to its application to support customers to plan their vacations. In the fashion industry, Nike has involved GPT-4 to auto-generate customised models for its Nike By You campaign.

Using generative AI will give way to consumers’ priorities and spending on real-time data. This will give more of an accurate right-on-time approach and an optimistic result. It helps the brands to position themselves in expected future trends and the after-effect models.

Levelling-up the Supply Chain

The new developments in generative AI can give various advantages to the already existing smart management systems, warehouse predictions, and reverse logistics. Macro events such as the COVID-19 pandemic and the Russia-Ukraine war have demanded that retailers plan by keeping future risks in mind. The world needs retailers to be extra careful before investing too much in supply chain management.

Generative AI can learn from past data which will lead the AI to proactively guide the team to make the correct decisions under the right circumstances. The Chief Solutions Officer of Kearney, Bharath Thota, stated that generative AI can define the applicable business and risk stats including future trends, competitions, changes in market and supply hurdles and can suggest suitable solutions and ideas. Fast fashion brands such as H&M, Zara, Mango, Old Navy, Topshop, Urban Outfitters, and Uniqlo have begun to use AI for their supply chain management.

Prolonged Inferences

Brands and retailers must keep in mind that before jumping into the largest pool of generative AI, they have to fully understand it and forecast potential problems to be faced. The companies have to know how to combine human intelligence and AI to design customer-focused content.

Governments have also started to enter into this digital world. In March 2023, the Italian government passed a bill on a temporary ban on ChatGPT to investigate privacy policies. The ban was lifted in April. Major business magnates such as Elon Musk, Apple co-founder Steve Wozniak and even AI godfather Geoffrey Hinton have put a 6-month pause on their AI departments until they strengthen their safety protocols.

Generative AI lacks emotions, decision-making skills and cannot exist with humans. Hence, retailers have to lay the AI with human intelligence to create a balanced operational system.

According to Goldman Sachs, around 300 billion jobs have been terminated by implementing generative AI. Retailers have to train their workers to thrive in this situation. PwC has invested $ 1 billion for the next 3 years for its AI project, along with upskilling 65,000 employees.

In 2021, Levi Strauss & Co. launched a boot camp on machine learning. This camp was to train non-technical employees to learn to use machine learning as a part of their design process. Employees who successfully complete the program can design new AI applications that are suitable for their work.

Cover Image: Nike's Impossible Store in White Sands, New Mexico, courtesy Benjamin Benichou LinkedIn Profile.