Terri L. Griffith

The 2022 public release of ChatGPT marked a key moment in human interaction with artificial intelligence (AI), driving the widespread adoption of generative AI tools. This special issue examines how AI diffusion demands a reconceptualization of group and team research. We propose a distinction between pre- and post-public AI eras, noting that today’s teams increasingly include members with everyday AI experience. Building on Katzenbach and Smith’s classic definition of teams, we stress the need to integrate human-AI dynamics, which introduce new complexities in team composition, complementary skills, shared purpose, and accountability. We advocate for openness to diverse approaches, greater methodological innovation, and interdisciplinary partnerships to keep pace with AI-driven change. The issue features two contributions: one examining how AI types shape trust and attention, another assessing AI-driven methods for analyzing team communication. We hope this editorial sparks a broader conversation to advance group scholarship in the post-public AI era.

Open organizations are structures in which members of the public engage in work for the organization. Examples include open-source software, Amnesty International, Wikipedia, and Lego communities. Much research focuses on structural design characteristics of open organizations, such as pre-specified task divisions and integration teams. These practices require the organization to a priori structure in response to its mission. Increasingly, however, open organizations like CrowdDoing and Hyperloop Transportation Technologies (HyperloopTT) require public involvement across volatile, uncertain, complex, ambiguous (VUCA) contexts. These open organizations must respond to changing political, competitive, and socio-economic events. Structural clarity is more difficult, and contributors may participate in the creative development of new technologies, new policies, and new sources of funding. Working from practices supporting participant engagement in more stable environments, we qualitatively observe HyperloopTT to understand internal practices for open organizing in more VUCA contexts. We observe four practices allowing for the flexibility, versatility, and accommodations needed for open organizing in such settings. The HyperloopTT practices allow more porosity and self-determination—not simply in how people divide and integrate tasks, but also in the exploration and experimentation of the work itself. More than task workers, we see a new class of open organizing participants: creative work designers.

The crucial contingencies surrounding organization design for innovation are experiencing drastic shifts. First, environmental uncertainty is rising with the increasingly connected nature of innovation. Second, the internet provides an almost costless supply of external knowledge. Current organization design theory does not provide adequate frames for studying organizations attempting to simultaneously leverage shifts of uncertainty and the costless supply of external knowledge. In the process of qualitatively examining one such organization - the crowd-based Hyperloop Transportation Technologies, Inc. (HTT) - we find that HTT's design does not fit existing design schema. We label this new design form a "catalyst" organization, clarifying how HTT's design challenges existing organization design principles while simultaneously showing researchers a way forward to new theorizing. We derive implications for theories of organization design, exploration, and online knowledge-creating communities.

We examined team performance as it was affected by organizationally supported face‐to‐face and technology‐mediated knowledge practices. Guided by an information processing perspective, we demonstrate from a field study of over 250 teams within a global Fortune 100 technology company that team member participation in face‐to‐face and technology‐mediated knowledge practices (e.g., community of practice (CoP) meeting attendance and use of CoP‐related technologies, respectively), and team knowledge sharing practices are positively related to individual team member knowledge. We predicted that absorptive capacity would moderate tacit knowledge relationships with team performance, and that transactive memory would moderate explicit knowledge relationships with team performance. We found that the patterns of relationships differed depending on the measure of team performance. The predictions held for absorptive capacity by tacit knowledge on manager‐assessed performance, and for transactive memory by explicit knowledge on customer satisfaction. Additionally, there was a significant direct effect, with no moderation, of tacit knowledge on customer satisfaction. We highlight multilevel modeling for team research and argue for joint consideration of organizational and technology practices. Copyright © 2009 John Wiley & Sons, Ltd.

We question the popular contention of a ‘one-hour’ rule of venture capital investing using data from two studies. A survey of 20 Silicon Valley (SV) venture capital general partners representing 122 portfolio firms finds 52% of their round one deals are done with exclusively SV firms (firms with no outside locations), 30% are done exclusively outside of the SV, and 18% are headquartered in the SV but also have locations elsewhere. A broader study of 3 826 SV venture capital deals finds 42% of round one deals are done with SV headquartered firms (this includes both exclusively SV deals and deals where only the headquarters is in the SV). There are significant effects for the industry of the portfolio company (high tech firms are more likely to be located in the SV) and the age of the venture capital firm, with younger firms roaming further a field in some cases. We describe ‘return on location’ (ROI) as a crucial component of due diligence, and consider the role that virtual management can play in mitigating distance issues. Six prominent Silicon Valley venture capitalists provide insights on the results.