AI in Logistics: An Expanding Trend That Still Faces Barriers in Latin America

The adoption of artificial intelligence (AI) in the Argentine logistics sector has become one of the main areas of technology investment in recent years. Driven by the growth of e-commerce, the pressure to automate processes, and the need to operate more efficiently, more and more companies are looking to apply AI to reduce operational friction and respond in real time. However, structural obstacles still persist in Latin America: a lack of specialized talent, difficulties organizing internal data, and a shortage of solutions adapted to the local context, especially for small and medium-sized businesses.

AI adoption in logistics shows an expanding trend. According to data gathered by the Argentine Association of Business Logistics (ARLOG), 82% of companies in the industry reported plans to invest in infrastructure, automation, and AI-based technology tools, with a focus on modernizing operations and improving traceability. Of that group, more than half (51%) prioritize specific solutions such as smart warehousing systems, virtual assistants, and automated tracking platforms.

One of the main drivers of this process has been the sustained growth of e-commerce. In the first half of 2024 alone, online sales in Argentina rose 248% year over year, accelerating demand for logistics efficiency in the face of higher delivery volumes, more returns, and customers who expect immediate responses. In this scenario, automation is no longer a differentiator but a condition for competitiveness: those who fail to optimize times and processes are quickly left behind.

However, for many companies, especially SMEs, adopting AI remains a concrete challenge. The IBM Global AI Adoption Index indicates that 32% of organizations in Latin America identify a lack of trained staff as the main obstacle to implementing these technologies. In addition, 43% acknowledge that they don't have internal data structured enough to feed predictive or automated models. On top of that come budget constraints, low interoperability with existing systems, and doubts about return on investment, a particularly sensitive point in volatile economic environments.

In this context, the development of technology tools adapted to Latin American conditions is becoming central: solutions that don't require large development teams or costly infrastructure, that can be configured quickly, work with simple databases, and understand local language in informal or decentralized environments.

An example of this kind of initiative is Laburen.com, an Argentine platform designed specifically to work in emerging markets. Unlike tools that require developers or complex implementations, Laburen can be set up in minutes, learns automatically from documents, spreadsheets, or websites, and is built to interpret both local language and emotions in real conversations. Its virtual assistants can automate tasks such as order management, quotes, or document entry, integrating with existing systems without the need for advanced technical knowledge. In various cases, these solutions have freed up to 70% of the operational time spent on repetitive tasks, allowing teams to focus on higher-value work.

The advance of AI in logistics is no longer a promise: it's a trend that is expanding and taking hold. But its real impact will depend on the ability to turn that technology into accessible, concrete, and scalable tools for companies operating with tight margins, lean structures, and diverse realities. In that direction, platforms designed from and for the Global South can play a decisive role in the mass adoption of artificial intelligence in the region.