ChatGPT and Beyond: Exploring the Responsible Use of Generative AI in the Workplace

Artificial intelligence (AI)-based systems are increasingly pervading most parts of our everyday life.Whether we are shopping online or looking for information at work, providers nowadays rely on AI-based models and seek to provide us with tailored support or guidance.Recently, a novel class of AI-based systems has gained widespread attention around the world.At the latest when Open AI's ChatGPT reached 100 million users in just over 2 months after launch (by comparison, it took TikTok 9 months, and Instagram 2.5 years to reach this level (Bhaimiya 2023; UBS 2023)), the potential as well as the challenges associated with Generative AI (GenAI) are widely discussed in academia, industry, and the public.When speaking of GenAI, we refer to ''…computational techniques that are capable of generating seemingly new, meaningful content such as text, images or audio from training data'' (Feuerriegel et al. 2024, p. 111).Recent studies show that GenAI has great potential when it comes to increasing the productivity of knowledge workers.For example, an experimental study observed significant effects in terms of time saving as well as quality improvement when ChatGPT was used in the context of mid-level professional writing tasks.The same study also observed that using ChatGPT decreased the inequality between participants, since participants with lower ability profited more, indicating that GenAI systems could also foster equality (Noy and Zhang 2023).Another experimental study focusing on software developers reports comparable findings.With the use of GitHub's Copilot, the average completion time of a standard programming task decreased by more than 50%, with no significant difference in success rate.In this study, less experienced developers, developers with high coding loads, as well as older developers benefited the most from using Copilot (Peng et al. 2023).Consequently, first studies suggest several benefits of leveraging the potential of GenAI in the workplace.At the same time, GenAI also presents several challenges that need to be addressed.A prominent challenge vividly discussed is so-called hallucination, which refers to circumstances in which GenAI systems provide incorrect information, e.g., fabricated references or fabricated