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Keys to the future of retail in the face of the technological challenges of AI

Jesús Aneiros, Director of Data Science Operations at Panel Sistemas, collaborates with an article in the July retail special of Capital Magazine.

The retail sector has always been one of those that has led the incorporation of the most innovative technologies in its way of working, although it has never been perceived in this way by consumers. Perhaps because many of the improvements have not become visible when they are implemented from within (Transport logistics, warehouse management,...) or because technological initiatives have faded in view of the consumer himself (An overwhelming start, but inconspicuous maintenance over time).

The retail sector and AI

I think this is the time for the sector to take a leap in quality in this regard, both in terms of visibility and understanding how to maintain that visibility over time and generate a sense of evolution and modernity. Artificial intelligence (Generative AI) is currently imposed as a concept and this circumstance is the perfect excuse for a very innovative sector in the management of its processes for many years to raise the level of its discourse and make visible its investments and its ability to generate value with its use.

The budgetary and investment effort must not be focused only on creation, but also on models that are continually learning and improving

From my point of view, this opportunity has to focus on very specific topics and not on common places, since the latter do not allow differentiating the value of what is built. In this sense, it is detected that there are areas in which the sector can and should evolve; Here are some of them.

First of all, great advances have been made in the field of CUSTOMER EXPERIENCE, although there is a long way to go in this field, especially in the implementation towards the consumer. Augmented reality systems for product understanding and, above all, product recommendation algorithms in the field are far from perfect.

The emergence of Generative AI makes its use necessary and extremely useful in CUSTOMER MANAGEMENT systems. In this sense, it is important to understand that any system that uses the aforementioned Artificial Intelligence tools (GPT Chat,...) must be integrating its results, not using them without filter or control; We understand that this is where the maximum development efforts and enrichment of current systems should be devoted.

Changing the third, but seeking to improve management efficiency, a great opportunity is detected to improve the EMPLOYEE EXPERIENCE. In any process related to Human Resources (Personnel Selection, Talent Management, Reduction of unwanted employee turnover, ...) there are ways to use Artificial Intelligence tools, methodologically establishing an analogy with the methods that seek to improve the customer experience.

After what, let's move on to how.

Once the debate on what is settled, let's take a moment to think about the how, and here it really deserves an important reflection about what is the approach to the implementation of a technological improvement centered on Artificial Intelligence; Normally, the visualization of the effort and, therefore, of the costs attributed to any initiative is focused on the moment of implementation and not on the maintenance and evolution of the technology itself.

Until today, costs were distributed 10 to 1 in favor of implementation as opposed to maintenance, THIS PARADIGM HAS TO CHANGE. The budgetary and investment effort must not focus only on creation, but must also focus on models that are continually learning and, therefore, improving in all aspects over time. This is THE KEY TODAY to guarantee that the visibility of technology is enduring over time.

In short, the challenges of the sector involve focusing the shot, using the best of technology, making the results visible and, finally, striving to maintain that visibility for the consumer and society in general.

You can find the full article at www.capital.es or also in paper format at your kiosk.

Panel Sistemas

Panel Sistemas

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