Companies' adoption of artificial intelligence (AI) is increasingly becoming an essential element of business success. However, using AI poses new requirements for companies and their employees, including transparency and comprehensibility of AI systems. The field of Explainable AI (XAI) aims to address these issues. Yet, the current research primarily consists of laboratory studies, and there is a need to improve the applicability of the findings to real-world situations. Therefore, this project report paper provides insights into employees' needs and attitudes towards (X)AI. For this, we investigate employees' perspectives on (X)AI. Our findings suggest that AI and XAI are well-known terms perceived as important for employees. This recognition is a critical first step for XAI to potentially drive successful usage of AI by providing comprehensible insights into AI technologies. In a lessons-learned section, we discuss the open questions identified and suggest future research directions to develop human-centered XAI designs for companies. By providing insights into employees' needs and attitudes towards (X)AI, our project report contributes to the development of XAI solutions that meet the requirements of companies and their employees, ultimately driving the successful adoption of AI technologies in the business context.

翻译：企业在采纳人工智能的过程中，其已成为商业成功的关键要素。然而，人工智能的应用给企业及其员工带来了新要求，包括人工智能系统的透明度与可理解性。可解释人工智能领域致力于解决这些问题。然而，当前研究主要停留在实验室阶段，亟需提升研究成果在现实场景中的适用性。为此，本研究报告揭示了员工对（可解释）人工智能的需求与态度。通过调查员工视角，我们发现：人工智能与可解释人工智能是员工普遍认知并视为重要的术语。这种认知是可解释人工智能通过提供对人工智能技术的可理解性洞察、推动人工智能成功应用的关键第一步。在经验教训部分，我们探讨了已识别的开放性问题，并提出未来研究方向——为企业开发以人为本的可解释人工智能设计。通过呈现员工对（可解释）人工智能的需求与态度认知，本研究报告致力于开发满足企业及其员工需求的可解释人工智能解决方案，最终推动人工智能技术在商业场景的成功落地。