The implementation of automation solutions in the areas of logistics and supply chain They open up a new map of possibilities for companies since they allow working with large volumes of data, analyzing it in real time and making decisions that benefit the business.
“The application of AI to logistics operations is a trend that should expand the borders of the logistics sector in the coming years,” added Martins.
In this framework, the expert lists four reasons to incorporate connectivity tools based on machine learning in this industry:
1 -High return on investment by reducing mileage, fuel consumption and route time, thus increasing productivity. Thanks to machine learning techniques, more deliveries can be made with fewer vehicles, generating significant savings. These improvements not only affect the operational aspect, but also have an impact on the administrative processes of logistics, including customer service, customer retention, availability and visibility for all departments involved.
2 -High availability combined with security. The Technology as a Service (SaaS) model is a trend increasingly adopted by companies. This approach eliminates the need to acquire, install and maintain software, since only the payment of a monthly fee is required that allows access to various functionalities that are always updated and in compliance with current regulations.
3 -Integration into a single system. Integrating all platforms with a single provider offers several advantages, such as the ability to prioritize tasks based on their importance, including route planning, last mile execution, and delivery confirmation. The route planning tool combines information on customer restrictions, vehicles, service windows and routes, as well as the definition of rest stops and other details to create an optimal route.
4 -Global traffic visibility (both customers and orders). Today’s technology offers real-time visibility of trucks, routes, orders and customers for all functions of each organization. This allows you to compare planned with actual, identify driver locations and evaluate their performance. In addition, analytical tools can be used to generate reports and control panels, facilitating management and adjustments to routes.
A new technology that generates many challenges
Although AI is transforming business in Latin America, challenges to implementation persist. This is reflected in the responses of the companies included in the study “Artificial Intelligence in Latin American companies”, by NTT Data and MIT.
Lack of specialized talent, concerns about costs, resistance to change and cybersecurity are just some of the main challenges that must be taken into account for its adoption, he clarifies.
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Furthermore, a growing concern that has arisen is Ethics related to AI and its adoption, focused on issues of transparency, privacy, security and accountability. A factor that companies have to pay special attention to and that still does not have a clear basis for action.
The strategic adoption of Artificial Intelligence has become an imperative in a world where businesses evolve daily. Know the challenges and opportunities that this technology provides It is key to making more strategic and informed decisionss that drive the success of its adoption and with it, that of the organization.
To draw an x-ray of the maturity of Artificial Intelligence in Latin American companies, 120 surveys of business leaders from Argentina, Brazil, Chile, Colombia, Mexico and Peru.
Of the total participants, 67.5% lead areas related to technology and the implementation of solutions, while 32.5% led business areas.
The sample encompasses different sectors, with a predominance in Technology and Software (26%), followed by Banking and Finance (15%), Energy and Petroleum (9%), Consulting (8%), and the Public and Educational sectors (7 % each).
In addition to this quantitative methodology, a qualitative approach was also followed, which consisted of conducting 10 online interviews with major technological leaders (including CDOs, CIOs, executive managers of information technologies (IT) and directors of business areas, with the objective of validating the findings and hypotheses that emerged from the research.
This dual approach allowed us to obtain a broad perspective of the current situation and future trends in the field of Artificial Intelligence in the region
