Human Ai Collaboration Emerging Digital Work Configurations And The

Bonisiwe Shabane

-Nov 29, 2025, 9:14 PM

human ai collaboration emerging digital work configurations and the

Digital technologies, in particular artificial intelligence (AI), are reconfiguring how, where, and when work gets done, marking a shift from tools designed to support human tasks to agentic systems that collaborate with and even... AI technologies are evolving to work autonomously or within hybrid collaboration systems of human and digital agents. Research on AI and human-AI collaboration has advanced from studying AI that supports human tasks to AI agents’ ability to make independent management decisions and regulate and manage human work. The future of working with AI is, however, still unknown and emergent, with both utopian and dystopian perspectives shaping our understanding of opportunities and challenges of their adoption and use in organizations, work, and... Prior research has helped make sense of and anticipate important side effects of AI-driven management, new forms of hidden and unrecognized ‘meta-work’ performed by employees, and the ‘ripple effects’ of introducing such technologies to... This includes the reconfiguration of spatial-temporal dimensions and ‘ways of seeing’ in the workplace, tensions between craft and mechanical work, and a wide range of unintended effects in work contexts such as loss of...

New research is needed to develop relevant theories and methods to study human-AI collaboration and how this is reconfiguring work. This special issue invites submissions that critically examine the current and expected future effects of human-AI collaboration and other emerging digital work configurations. It seeks theoretical, empirical, and design-oriented contributions that study the transformative potential of digital-human collaboration, aiming to gather research that fosters ethical solutions and sustainable models for AI- and digitally-driven work, while informing future... It encourages work that inspires innovative strategies and follows good research practice in the use of AI, but is also open to developing prospective scenarios and actively creating preferable futures. Human-AI Collaboration, Emerging Digital Work Configurations and the Changing Nature of Work Alexander Richter, Victoria University of Wellington – New Zealand (corresponding editor, alex.richter@vuw.ac.nz)

João Baptista, Lancaster University – UK & Nova SBE – Portugal Ella Hafermalz, Vrije Universiteit Amsterdam – The Netherlands Mareike Möhlmann, Bentley University – USADaniel Schlagwein, The University of Sydney – Australia (JIT editor) We would like to draw your attention to our new Call for Papers for a Special Issue of Journal of Information Technology (JIT): Human-AI Collaboration, Emerging Digital Work Configurations and the Changing Nature of Work The rapid advancement of AI is transforming work practices, moving beyond automation to collaboration between humans and digital agents.

We invite theoretical, empirical, and design-oriented contributions that explore the interplay between AI and human agency, the emergence of new digital work configurations, and the broader implications for ethics, policy, and management. Please find the full call for papers, including the full editorial board, at https://communities.aisnet.org/sigcnow/jitsioncnow Jacob Taylor, Thomas Kehler, Sandy Pentland, Martin Reeves Part of the book series: Progress in IS ((PROIS)) Solving problems by human-AI configurations will likely become a pervasive practice. Traditional models of delegating tasks between humans and machines must be revisited in light of the differences in the learning of humans versus intelligent machines; performance can no longer be the sole criterion for...

We propose a new human-AI configuration called a reciprocal human-machine learning (RHML) configuration and offer a new procedure for delegating tasks dynamically that begins with determining the desired level of machine autonomy. This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout Ågerfalk PJ, Conboy K, Crowston K, Eriksson Lundström JS, Jarvenpaa S, Ram S, Mikalef P (2022) Artificial intelligence in information systems: state of the art and research roadmap. Commun Assoc Inform Syst 50 In the rapidly evolving landscape of artificial intelligence (AI), organizations are continually seeking strategies to harness its transformative power.

An academic study, “Augmenting the Algorithm: Emerging Human-in-the-Loop Work Configurations,” by Tor Grønsund and Margunn Aanestad, sheds light on this journey by examining the integration of AI within a maritime trading organization. The study reveals that as AI capabilities are adopted, the configurations of human and algorithmic collaboration evolve, leading to significant implications for work and organizational structure. It emphasizes the emergence of a human-in-the-loop pattern, where human roles are not replaced but rather redefined to augment the algorithm’s accuracy and performance. The integration of AI necessitates new roles and a redistribution of expertise. Workers are required to audit the algorithm’s outputs and adapt the data acquisition architecture, ensuring that the AI’s performance aligns with the organization’s needs. The findings underscore the strategic importance of human involvement in AI integration.

This human-in-the-loop configuration is crucial for organizational reflexivity, allowing for the continuous optimization of AI systems to meet changing demands and environments. As we look towards the future, the study provides a framework for understanding the dynamic role of AI in transforming work practices. It highlights the necessity for adaptability and human oversight in ensuring effective AI implementation, which will be pivotal in determining the long-term value of AI tools like ChatGPT in various professional contexts. Work in the future will be a partnership between people, agents, and robots—all powered by artificial intelligence. While much of the current public debate revolves around whether AI will lead to sweeping job losses, our focus is on how it will change the very building blocks of work—the skills that underpin... Our research suggests that although people may be shifted out of some work activities, many of their skills will remain essential.

They will also be central in guiding and collaborating with AI, a change that is already redefining many roles across the economy. In this research, we use “agents” and “robots” as broad, practical terms to describe all machines that can automate nonphysical and physical work, respectively. Many different technologies perform these functions, some based on AI and others not, with the boundaries between them fluid and changing. Using the terms in this expansive way lets us analyze how automation reshapes work overall.1Our analysis considers a broader range of automation technologies than the narrow definition of agents commonly used in the AI... For more on how we define the term, see the Glossary. This report builds on McKinsey’s long-running research on automation and the future of work.

Earlier studies examined individual activities, while this analysis also looks at how AI will transform entire workflows and what this means for skills. New forms of collaboration are emerging, creating skill partnerships between people and AI that raise demand for complementary human capabilities. Although the analysis focuses on the United States, many of the patterns it reveals—and their implications for employers, workers, and leaders—apply broadly to other advanced economies. We find that currently demonstrated technologies could, in theory, automate activities accounting for about 57 percent of US work hours today.2Our analysis focuses exclusively on paid productive hours in the US workforce, encompassing full-time... We assess only the share of time awake that is spent on work-related activities, totaling roughly 45 percent of waking hours. Our analysis excludes time spent on unpaid tasks and leisure, but agents and robots could be used in related activities to support productivity and personal well-being.

This estimate reflects the technical potential for change in what people do, not a forecast of job losses. As these technologies take on more complex sequences of tasks, people will remain vital to make them work effectively and do what machines cannot. Our assessment reflects today’s capabilities, which will continue to evolve, and adoption may take decades.

Human Ai Collaboration Emerging Digital Work Configurations And The

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