1 More Paper.

Abstract As artificial intelligence (AI) transforms a wide range of sectors and drives innovation, it also introduces different types of risks that should be identified, assessed, and mitigated. Various AI governance frameworks have been released recently by governments, organizations, and companies to mitigate risks associated with AI. However, it can…

Abstract Responsible AI (RAI) entails developing, using, and governing AI in a human-centred way to ensure its trustworthiness and alignment with human values. Organizations attempt to enact RAI through guiding principles that aim to minimize threats such as bias and privacy violations and enhance outcomes such as transparency and fairness. In the…

The rapid diffusion of generative artificial intelligence (GenAI) is reshaping organisational systems and digital transformation strategies, yet it remains unclear which organisational conditions are associated with long-term competitive performance in business-to-business (B2B) contexts. This study adopts a systems-informed perspective and examines how…

What is the role of product managers (PMs) in the responsible use of generative AI (genAI) in products and everyday work— and what enables or constrains their ability to take action? Past literature has examined the ways in which organizational policies can become decoupled from practices when incentives for responsible action are misaligned or impeded…

We introduce and study the concept of a “jagged technology frontier” to describe the uneven impact of artificial intelligence (AI) capabilities, where AI assistance improves performance for some tasks but worsens it for others, even within the same knowledge workflow and with a seemingly similar level of difficulty. In collaboration with the global…

Recently, frameworks and guidelines aiming to assist trustworthiness in organizations and assess ethical issues related to the development and use of Artificial Intelligence (AI) have been translated into self-assessment checklists and other instruments. However, such tools can be very time consuming to apply. Aiming to develop a more practical tool, an…

Abstract Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important…

Although organizations increasingly position AI adoption as a path- way to competitiveness and innovation, organizations’ perspectives on productivity and efficiency often clash with workers’ perspec- tives on AI’s economic and social value. Through design workshops with 15 UX designers, we examine how AI adoption unfolds across individual, team, and…

Purpose This research investigates the phenomenon of AI complacency – The employee's tendency to intentionally neglect validating AI-generated output even in the presence of systematic errors. It identifies the lack of monitoring accountability as the underlying driver of this phenomenon, assesses its consequences, and offers strategies for mitigation.…

Context: Generative AI (GenAI) is argued to transform software engineering (SE) in various ways, and GenAI tools show promise for various SE tasks. Software organizations across the globe are currently exploring the use of GenAI for SE. Objective: While numerous studies have recently been published on GenAI, few studies have looked at the adoption of…

We study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey linked to comprehensive register data in Denmark. Surveying 18,000 workers from 11 exposed occupations, we document that ChatGPT is widespread, especially among younger and less-experienced workers. However, substantial inequalities have emerged. Women are 16…