Generative Artificial Intelligence (GenAI) has gained a position as a strategic ally in sectors that require speed, accuracy and scalability. In this scenario, companies from various sectors can adopt the tool to transform logistics and IT operations by focusing on measurable gains such as reducing costs, increasing productivity and improving performance indicators.
Data from Mordor Intelligence indicates that the global logistics automation market is expected to reach US$120.63 billion in the next five years, driven by the digitalization of the sector.
According to Lineker Oyagwe, project manager at Samsung SDS, the technology arm of the Samsung Group, GenAI is moving from being just a text assistant to taking on the role of co-pilot for business operations.
“The tool is able to raise the level of IT and logistics operations from reactive mode to predictive mode and, gradually, to autonomous mode,” he says. According to the CEO, the use of technology contributes to faster and more decisive decisions, reduces rework, increases overall visibility and frees teams to undertake higher value activities.
Among the solutions developed by Samsung SDS, for example, are practical applications of GenAI that have already been integrated in Brazil and in other countries. In IT, technology is used to automate technical support at initial levels, analyze incidents, document, and create runbooks, which helps developers solve problems safely.
In logistics, Oyagwe explains that using GenAI can produce intelligent summaries of shipment status, explain delays, suggest alternative routes, standardize quotes and deadlines from carriers and even respond to customers based on real data from TMS and WMS systems.
“This vision is being realized on three fronts: accelerating analysis and planning, automating processes and improving the customer experience. In practice, this means applying GenAI to tasks such as demand forecasting, capacity simulation, automated service, data auditing, quoting and scheduling.”
For the manager, technology also contributes by providing contextual and real-time information to customers, which translates into more predictability for the entire chain.
GenAI has also proven effective in critical processes such as traceability and demand planning. In inventory monitoring, for example, AI can correlate variables such as sales, promotions and seasonality to indicate optimal levels by SKU and location, as well as suggest transfers between distribution centers and stores, Oyagwe explains.
“In tracking, technology integrates data from multiple sources to create a single, understandable timeline, detailing events and risks. This allows for proactive actions, such as replanning delivery windows and accurately informing customers. In demand planning, GenAI accelerates the S&OP cycle by explaining variations, testing scenarios, suggesting adjustments, and combining statistical models with contextual knowledge,” he adds.
This movement highlighted by the executive authority reflects a broader trend. A McKinsey survey shows that companies around the world are redesigning workflows and engaging senior leadership in AI governance.
A study conducted by the Enterprise Strategy Group (ESG) with Hitachi Vantara, published on the InforChannel portal, indicates that 44% of organizations have well-defined policies for GenAI, although only 37% consider themselves prepared in terms of infrastructure and data.
Oyagwe highlights that some of Samsung’s global SDS platforms, such as Cello (focused on supply chain) and Britty Automation (focused on automation and conversation), already have GenAI capabilities to understand natural language, generate ideas and execute tasks.
“In regulated environments, the technology works with secure retrieval mechanisms (RAG), audit trails and access controls, while respecting legislation such as the General Data Protection Regulation (LGPD).”
Despite the progress, the Executive notes that GenAI adoption in the logistics sector still faces technical and regulatory challenges. “Among the main hurdles are the need to ensure data quality and management, reduce hallucinations through validations, control costs and response time in variable loads and integrate technology with legacy systems safely. It is also necessary to implement model control mechanisms, rapid releases and fallback policies.”
By 2030, Samsung SDS sees generative AI as the driver of “hyper-soft innovation” in logistics operations and enterprise technology, evolving from conversational co-pilots to AI agents capable of coordinating end-to-end operations with clear security, governance and ROI. The company already takes an integrated approach to AI, which includes infrastructure, consulting, platforms and solutions, with a focus on Britain Copilot, Samsung Cloud Platform and partnerships with cloud ERP service providers.
The company is also investing in capabilities such as multi-language automatic translation, graphics processing unit as a service (GPUaaS) and enterprise security. “We work with clear goals, indicators that are monitored in real time, and seamless integration with existing systems. GenAI is destined to become a ubiquitous co-pilot in IT and logistics, increasing productivity and quality of services provided,” Oyagwe concluded.
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