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The emerging complex human and machine collaborations (Benbya et al., 2020 Rai et al., 2019) move the role and nature of workplace technologies beyond merely having an instrumental and supporting role to humans in organisations (Riemer and Peters, 2020). Academic research is only recently starting to appreciate the deeper effects on organisations associated with these technologies (Riemer et al., 2015 Majchrzak et al., 2016 Spagnoletti et al., 2015 Aral et al., 2013 Hutter et al., 2017 Baptista et al., 2010), and taking the first steps to study the distinct nature of a new generation of workplace technologies based on self-determining platforms with artificial intelligence (AI) that can dynamically anticipate and respond to the needs and intentions of workers (Schuetz and Venkatesh, 2020 Lyytinen et al., 2020). Research in this area has captured the nature and affordances of workplace technologies (Vaast and Kaganer, 2013 Treem and Leonardi, 2012 Leonardi and Vaast, 2016) but most of this research takes an instrumental view of these technologies by linking features of workplace technologies with more immediate behaviours and practices that contribute to performance, connectedness, knowledge sharing and collective action (Rice et al., 2017 Saebø et al., 2020 Majchrzak et al., 2013 Kuegler et al., 2015 Von Krogh, 2012). This provides researchers with a challenge to capture the deep effects of workplace technologies in organisations (Silva and Hirschheim, 2007) and emergent human-technology configurations (Suchman, 2012) so we can understand their strategic significance to organisations, leadership and business (Dery et al., 2017 Heavey et al., Tavakoli et al., 2017). The evolutionary use of workplace technologies in organisations over the last two decades has hybridised their use with human activities in organisations, forming complex (Benbya et al., 2020) and emergent human-in-the-loop (Rai et al., 2019) or meta-human configurations as new forms of socio-technical systems not seen before (Lyytinen et al., 2020). While early research on digital workplace technologies such as email and intranets, captured the immediate and surface-level effects of these technologies Cecez-Kecmanovic et al., 1999 Bansler et al., 2000 Markus, 1994 Lee, 1994 Butler, 2003), what we observe now is the introduction of more advanced workplace technologies in organisations, while older technologies are becoming increasingly embedded in the fabric of organisations.

This need for large-scale experimentation will push many scholars out from their comfort zone, because it calls for the revitalization of action research programs that informed the first wave of socio-technical research at the dawn of automating work systems. Such trials will result in improved understanding of metahuman systems. We conclude by noting that improved understanding of metahuman systems will primarily come from learning-by-doing as information systems scholars try out new forms of hybrid learning in multiple settings to generate novel, generalizable, impactful designs. We show how each function raises new research questions for the field. We identify four organizational level generic functions critical to organize metahuman systems properly: delegating, monitoring, cultivating, and reflecting. We review how these changes influence organization design and goals. Information systems researchers can look beyond the capabilities and constraints of human learning toward hybrid human/machine learning systems that exhibit major differences in scale, scope and speed. They will push information systems research in new directions that may involve a revision of the field’s research goals, methods and theorizing.

Metahuman systems will change many facets of the way we think about organizations and work. Metahuman systems are new, emergent, sociotechnical systems where machines that learn join human learning and create original systemic capabilities.