Despite its significant potential for (partial) automation, Artificial Intelligence (AI) is still rarely used in small and medium-sized enterprises (SMEs) within the metal industry. This is particularly critical given ongoing challenges such as skilled labor shortages and supply chain disruptions. A key barrier to adoption is the perception of AI as a “black box,” where results are neither transparent nor easily validated by users.

The project aims to develop an AI system for support in offer calculations in the metal industry. A central focus of the project is the integration of Explainable AI (XAI) and Human-in-the-Loop (HITL) principles. The AI system is designed to make its predictions transparent and adjustable, enabling users to understand, validate, and influence results. The project specifically explores how explainable AI can support targeted human-AI collaboration.

The project delivers an AI-based assistance system for pricing within quotation processes. It provides evaluation and decision-support functionalities that simplify, accelerate, and improve currently manual tasks performed by roles such as work planners, project managers, and sales staff. Preliminary evaluations reveal that the system reduces the workload associated with offer calculations while providing effective meansfor users to provide their expert knowledge.

The project contributes to increasing the adoption and success of AI in SMEs within the metal industry. Beyond it serves as a blueprint for human–AI collaboration and demonstrates how explainable AI can unlock new data-driven applications across industries. It thus plays a key role in advancing the broader digital transformation of SMEs and promoting sustainable, responsible AI integration.