McKinsey: 'Generative AI will be a Copernican revolution for fashion'. OK, but what is generative AI?
Disruptive AI technologies are set to play a key role in disrupting many sectors and markets. According to McKinsey, generative AI is going to be the top-performing trend in the fashion industry.
McKinsey claims that generative AI will be a revolutionary technology for fashion, disrupting many different aspects of the industry and representing an opportunity to improve productivity, consumer experience and time to market. Let’s find out about generative AI and its main characteristics.
What is generative AI?
Nowadays, when things revolve around artificial intelligence, very often the conversation leads to the fact that AI tools and applications are capable of creating content on their own, including practical and scientific content, such as coding, but also creative ones concerning arts, literature or music.
Is this science fiction? No, it’s generative AI. To provide a more complete and in-depth definition, generative AI are artificial intelligence systems, algorithms and applications that are able to create texts, pictures and other types of media responding to specific user inputs or requests, for example, prompts submitted via chat.
This undoubtedly represents one of the most interesting and fascinating fields of development concerning artificial intelligence, considering the possibilities of creating brand-new activities, markets and professions by mastering this technology.
How does generative AI work?
Just like other types of artificial intelligence systems that leverage machine learning as a key factor, also generative AI learns how to best operate based on previous data and information gained through experience. But it is not only a matter of storing them: indeed, data and information are categorised, recognised and elaborated in order to generate new creations based on this kind of training.
The type of learning used to generate AI applications is the one called generative adversarial networks (or GANs). It consists of two neural networks working together:
- Generator that creates new data;
- Discriminator that evaluates data.
The combined interconnection of these two creates a process where the generator is able to improve the outputs based on the discriminator’s feedback, until it becomes capable of generating contents which can’t be distinguished from the human-made ones.
Thus, the process that makes generative AI work is based on:
- Forming a database with a neural network consisting of multiple information, files and media, and is the very basis of the whole knowledge stored in the AI system;
- Inputting a prompt including a description, a sample or even a question related to the desired content to be produced;
- Generating content and transforming the AI system into a subject capable of learning best practices and ways to improve its outputs.
A few stats to understand the power of generative AI
Let’s take a look at some data which helps to explain and understand the generative AI phenomenon from a wider point of view. For what concerns the most interesting statistics for future expectations, a study claims that:
- By 2025 10% of all data will be produced and/or contributed by artificial intelligence;
- By 2027 the expected growth rate per year of the generative AI market will be 33%;
- By 2030 the whole generative AI market will be valued at almost $16 trillion and thus the global GDP will increase by +26%.
Generative AI in fashion industry: what’s going to happen?
McKinsey claims that considering the next three to five years, generative AI solutions will lead the fashion industry profits to an average increase of around $200 billion.
This projection underlines the important relevance of the apparel industry and how disruptive technologies can be in this sector. Indeed, the introduction of generative artificial intelligence in fashion businesses could be the ultimate ace up the sleeve to look forward to futuristic models and best practices where technologies will write the history of business and economy, once again.
Let’s see a few ways that generative AI will affect the fashion industry.
Merchandising and product
Generative AI can help fashion what concerns merchandising and products by:
- Converting simple sketches and descriptions into true and complete designs;
- Collecting new creative ideas and suggestions, and providing inspiration;
- Customising products for individual consumers with specific needs or wants.
Generative AI can help fashion reduce the issue of counterfeiting:
- Analysing consumer purchasing behaviour;
- Assist in product authentication processes;
- Monitoring supply chains and distribution for signals of over production and grey market distribution.
Supply chain and logistics
Generative AI can help fashion concerning supply chain and logistics by:
- Supporting negotiations with suppliers;
- Improving automation activity for warehouse operations or inventory management;
- Preparing customised return offers for individual consumers.
Generative AI can help with fashion marketing by:
- Identifying and predicting trends to improve performance;
- Preparing automatic consumer segmentation for specific marketing activities;
- Generating personalised marketing content related to consumers insights;
- Cooperating with AI to support the marketing team in developing new ideas.
Digital commerce and customer experience
Generative AI can help fashion when it comes to digital commerce and customer experience by:
- Generating sales descriptions based on previous successful posts;
- Personalising the online customer journey with specific experiences and offers;
- Providing individual consumers with virtual garments try-on or recommendations;
- Enhance AI assistants, like chatbots, to guarantee basic support to consumers.
Generative AI can help store operations by:
- Optimising store layout planning by AI testing according to several parameters;
- Optimising in-store activities like workloads, staff allocation or even theft detection;
- Supporting tools to better perform and communicate with the workforce.
Organisational support functions
Generative AI can help fashion for what concerns support functions by:
- Coaching and supporting sales associates by providing real-time recommendations, feedback reports and also clients profiles;
- Developing personalised training content for all the workers based on roles, performances and training needs;
- Enabling self-assistance for specific support tasks, concerning for example legal or administrative documents.
These represent the most important points which can make generative AI a precious companion to support businesses, regardless of their sector. When it comes to fashion McKinsey predicts a bright future. We are ready to witness the evolution it will bring to the apparel sector.