Artificial Intelligence (IA) has been a hot topic in recent months, especially following the proliferation of ChatGPT. Fear and uncertainty are words we are beginning to associate with this new world, but experts believe there is yet much to explore. 

In the footwear industry, which potentialities can be explored with the integration of some Artificial Intelligence resources? The APICCAPS Journal spoke with Rui Rebelo, from INESC TEC.

What impact can Artificial Intelligence have on the industry, especially in the footwear industry?
Artificial intelligence has strongly impacted the industry across various sectors in recent years, with a widespread paradigm shift towards greater digitalisation of processes and adoption of emerging technologies. Broadly speaking, this impact has been felt mainly at the decision-making level and in the ability of AI technologies to enable effective support in key decision processes in an automated, autonomous, efficient and reliable way.
In the highly dynamic and uncertain context that characterizes today’s industrial ecosystem, real-time, knowledge-based decision-making is increasingly crucial to ensure long-term sustainable growth.

The footwear sector, in particular, has a set of unique characteristics that make it especially interesting for the successful integration of these systems. It is a sector with a largely globalized and fragmented value chain, which presents very short product life cycles and high variability of demand, resulting not only from seasonality but also from the socio-economic context. All of this, along with the increasingly informed and demanding consumers, add to the growing complexity of the footwear business that conditions the efficient management of processes throughout the value chain.
In this context, the integration of AI techniques in the footwear industry will enable greater operational efficiency, but above all greater flexibility/agility in the response to the market required by this sector.

These techniques will therefore allow several gains, namely: 1) Production efficiency: through task automation, data analysis and planning/scheduling algorithms that will enable production costs to be reduced, resource consumption to be minimised, and production downtime to be reduced; 2) Quality: through the automation of repetitive tasks to avoid mistakes, as well as real-time monitoring of production parameters, identifying problems more quickly, thus allowing an immediate response; 3) Forecasting: through the ability to analyse consumption trends, seasonality, fashion events, etc., based on historical data, the current situation and the entire value chain, allowing companies to create more relevant products for the market and make informed decisions about stock and production levels; 4) Customisation: customisation is increasingly critical in the footwear sector and AI can make a key contribution by analysing consumer preferences and fashion trends, thus facilitating the creation of custom designs and their integration into the production system in a faster and more efficient way.
The overall adoption of these techniques across organizations will also contribute to the emergence of new business models based on the current challenges of sustainability (economic, environmental and social) and resilience. The ability to process and analyse large volumes of data will make it possible to trace processes and products throughout the value chain, enabling the adoption of circularity strategies and others that make it possible to understand and limit the sector's environmental, social and economic impacts.
At last, despite the gains already observed and documented, predicting the real impact of AI adoption in the industry will always be a difficult exercise, insofar as this impact is not only very broad and encompasses multiple characteristics, but is constantly evolving in step with technological advances and growing adoption in the various industrial sectors.

How should companies prepare for this impact?
Typically, the adoption of innovative technologies, in particular digital ones, forces major reconfigurations of many elements of the organization, not only at the production level, but also at the level of processes, strategies and organisational structures. Although AI technologies are at an interesting level of maturity for industrial applications, work on structuring problems, processes, data, etc., as well as digital literacy in companies is needed for successful implementation. Therefore, an effective digital transition and adoption of AI solutions require from companies a clear, planned and integrated digital strategy in the global vision of the organisation, actively involving all key players in the process.

Looking at the footwear industry, the main challenges may lie at the level of the proper balance between the preservation of skills and know-how inherent to a highly traditional sector and the level of automation and AI required in new business models. In this sense, companies should actively work to find the right balance between process, technology, and business strategy, within an integrated systems vision. Only then will companies be more capable to achieve effective gains in competitiveness through AI.