Beyond the Org Chart: AI and the Transformation of Invisible Work

• URL: http://arxiv.org/abs/2605.22707v1
• Date: Thu, 21 May 2026 16:46:44 GMT
• Title: Beyond the Org Chart: AI and the Transformation of Invisible Work
• Abstract summary: We interviewed 24 product-focused individuals at a large technology firm about how AI has impacted their own work, their work within their product team, and their professional interactions.<n>Some of these changes are positive, such as smoother collaboration between peers, but other changes are more nuanced and put the typical career growth opportunities at risk.<n>We propose steps that AI companies can take to make the invisible work more visible.
• Score: 2.442168164204936
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: An increasing number of news and research articles report that AI adoption is allowing professionals to blur and extend the boundaries of their corporate roles. With the goal of understanding how work processes might be changing in an AI-forward company, we interviewed 24 product-focused individuals at a large technology firm about how AI has impacted their own work, their work within their product team, and their professional interactions. Our conversations suggest that AI is not only changing formal role responsibilities and collaborations between those roles, but also changing informal cultural practices like professional mentoring that are key to helping professionals settle in their positions, stay engaged with their work, and grow their careers. Some of these changes are positive, such as smoother collaboration between peers, but other changes are more nuanced and put the typical career growth opportunities, like receiving feedback from professional networks and promoting leadership and mentorship, at risk. We propose steps that AI companies can take to make the invisible work more visible. Additionally, we propose efforts that individuals and leaders can take to support their colleagues through AI transformation while preserving healthy company cultures that support diverse thinking, collaboration, and informal interactions.

Related papers

• When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration [78.16115745870405]
  We aim to characterise the value of artificial intelligence in the workplace.<n>Current studies largely measure this value in terms of the current automation capabilities and public adoption of AI.<n>To account for this, we must expand the scope of our analysis beyond atomised tasks of today.
  arXiv  Detail & Related papers  (2026-09-11T06:29:34Z)
• The SPACE of AI: Real-World Lessons on AI's Impact on Developers [0.807084206814932]
  We study how developers perceive AI's influence across the dimensions of the SPACE framework: Satisfaction, Performance, Activity, Collaboration and Efficiency.<n>We find that AI is broadly adopted and widely seen as enhancing productivity, particularly for routine tasks.<n>Developers report increased efficiency and satisfaction, with less evidence of impact on collaboration.
  arXiv  Detail & Related papers  (2025-07-31T21:45:54Z)
• Operationalizing AI for Good: Spotlight on Deployment and Integration of AI Models in Humanitarian Work [52.96150571365764]
  We share details about the close collaboration with a humanitarian-to-humanitarian (H2H) organization.<n>We discuss how to deploy the AI model in a resource-constrained environment, and how to maintain it for continuous performance updates.
  arXiv  Detail & Related papers  (2025-07-21T17:30:38Z)
• TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks [55.03911355902567]
  We introduce TheAgentCompany, a benchmark for evaluating AI agents that interact with the world in similar ways to those of a digital worker.<n>We find that the most competitive agent can complete 30% of tasks autonomously.<n>This paints a nuanced picture on task automation with simulating LM agents in a setting a real workplace.
  arXiv  Detail & Related papers  (2024-12-18T18:55:40Z)
• "It Might be Technically Impressive, But It's Practically Useless to us": Motivations, Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News Industry [7.568817736131254]
  This study investigates the practices, challenges, and opportunities for internal cross-functional collaboration around AI in news industry.<n>We interviewed 17 journalists, six AI technologists, and three AI workers with cross-functional experience from leading Chinese news organizations.
  arXiv  Detail & Related papers  (2024-09-18T14:12:01Z)
• AI's Social Forcefield: Reshaping Distributed Cognition in Human-AI Teams [6.386909552513031]
  We show that AI actively reshapes the social and cognitive fabric of collaboration.<n>We show that AI participation reorganizes the distributed cognitive architecture of teams.<n>We argue for rethinking AI in teams as a socially influential actor.
  arXiv  Detail & Related papers  (2024-07-03T13:46:00Z)
• The Ethics of Advanced AI Assistants [53.89899371095332]
  This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural language interfaces, whose function is to plan and execute sequences of actions on behalf of a user. We consider the deployment of advanced assistants at a societal scale, focusing on cooperation, equity and access, misinformation, economic impact, the environment and how best to evaluate advanced AI assistants.
  arXiv  Detail & Related papers  (2024-04-24T23:18:46Z)
• Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice [63.20307830884542]
  Next several decades may well be a turning point for humanity, comparable to the industrial revolution. Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts. We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies.
  arXiv  Detail & Related papers  (2024-04-06T22:18:31Z)
• The Road to a Successful HRI: AI, Trust and ethicS-TRAITS [64.77385130665128]
  The aim of this workshop is to foster the exchange of insights on past and ongoing research towards effective and long-lasting collaborations between humans and robots. We particularly focus on AI techniques required to implement autonomous and proactive interactions.
  arXiv  Detail & Related papers  (2022-06-07T11:12:45Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study [11.633108017016985]
  The development of AI applications is a multidisciplinary effort, involving multiple roles collaborating with the AI developers. During these collaborations, there is a knowledge mismatch between AI developers, who are skilled in data science, and external stakeholders who are typically not. This difference leads to communication gaps, and the onus falls on AI developers to explain data science concepts to their collaborators.
  arXiv  Detail & Related papers  (2021-01-13T19:33:34Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.