AI in Logistics and SCM

The AI in Logistics and Supply Chain Management course focuses on the use of artificial intelligence in SCM and Logistics in an organization.

Under the guidance of an experienced lecturer, participants apply the content mainly using exercises and examples from practice.
Top lecturers with experience and experts in their field.
A high degree of satisfaction of course participants.

The form of course implementation is face-to-face or online (or both forms).
The working methods used in the training programs are chosen in such a way as to ensure interactivity, adaptation of the content to the needs of the participants and a priority focus on the transfer of knowledge into practice .

Objectives

Understand the main uses of AI in logistics and supply chains
Be able to identify, prioritize and quantify AI use-cases, build a data foundation: sources, quality and data management.
Know the integration patterns of AI into existing systems (SAP/Dynamics, WMS, TMS) – batch, event-driven, API/EDI.
Be able to use AI safely and ethically. Use of generative AI.
Be able to process a business case and roadmap for an AI deployment project. Develop an AI deployment project: use-case definition, data, metrics and pilot KPIs.

Content Course

Introduction

What AI means in logistics and SCM today – the difference between automation, machine learning and generative AI.
Value map: where AI brings measurable benefits
Typical pitfalls and how to avoid them
Current trends and opportunities
AI-driven inventory optimization
AI demand prediction.

How to use AI

connecting data, models and workflow.
Heuristics, optimization, ML model.
OTIF, inventory, shipping

Data: Standard metrics in logistics and SCM

Demand prediction: promo calendars, weather, holidays, POS, web signals.
Transportation: historical routes, traffic phenomena, loadings, windows, capacities, violations.
Warehouse: picking times, slotting, equipment utilization

Risks

Risks of bad scope, weak data and “AI theatre”.
Costs of operating models and technological lock-in.
Operational risks
Data quality: completeness, consistency, granularity, latency; DQ
dashboard and SLA.
IT security

AI vs automation in logistics processes

Levels of automation
What is worth automating.
Automation vs. AI in logistics – where is the border and synergies.
Principles of ML functioning
AI boundaries
Examples of use: forecasting, inventory, routing
Flexibility of digital systems: cloud/hybrid

Generative AI in practice

Copilot for the planner
Document automation.
AI agents
Secure deployment of LLM in the enterprise.

Design and implementation of an AI project: developed by participants

Definition of AI use-case
Data collection
Choice of KPIs
Project roadmap
Identification of risks

Trainers

Tomáš Marek

Peter Elbert

Application support - consultations and workshops

For course participants, we offer the possibility of subsequent application support in the form of individual consultation with a lecturer or in the form of workshops directly at the client.

To order or for more information, contact us at fbe@fbe.sk, or at phone number +421 2 544 185 13.

"I find the Digital Transformation in Logistics and Supply Chain Management course extremely useful. I particularly appreciate the lecturer's ability to connect practice with theory. Of the topics covered in the course, the x-matrix, artificial intelligence (AI), machine learning (ML), and parameter setting were of greatest practical importance to me."

Miroslav Jančich

Planning team Lead, AAH PLASTICS Slovakia s. r. o.

"The entire course Digital Transformation in Logistics and Supply Chain Management was interesting and enriched my perspective. I liked the practical part with specific examples from practice. I thank the lecturer for his approach."

Andrea Molnárová

Rail & Barge Capacity Management, SLOVNAFT, a.s.

Find out more

We will provide you with more detailed information about the price, possible dates and training schedule.

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