Post-Public AI: Research in Groups and Teams

Abstract

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.

Keywords

work groups teamwork team group AI

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References

American Psychological Association. (2023). Open science at APA. https://www.apa.org/pubs/journals/resources/open-science

Anthony

Bechky

B. A.

Fayard

A.-L.

(2023). “Collaborating” with AI: Taking a system view to explore the future of work. Organization Science, 34(5), 1672–1694. https://doi.org/10.1287/orsc.2022.1651

Asencio

Mesmer-Magnus

J. R.

DeChurch

L. A.

Contractor

(2024). Boundary transitions in dynamic teamwork. Academy of Management Review, 49(3), 597–617. https://doi.org/10.5465/amr.2019.0471

Bandura

(1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bennett

M. S.

Hedley

Love

Houpt

J. W.

Brown

S. D.

Eidels

(2025). Human performance in competitive and collaborative human–machine teams. Topics in Cognitive Science, 17(2), 324–348. https://doi.org/10.1111/tops.12683

Bezrukova

Griffith

T. L.

Spell

Rice

Yang

H. E.

(2023). Artificial intelligence and groups: Effects of attitudes and discretion on collaboration. Group & Organization Management, 48(2), 629–670. https://doi.org/10.1177/10596011231160574

Brynjolfsson

Rock

Syverson

(2019). Artificial intelligence and the modern productivity paradox. In Agrawal

Gans

Goldfar

(Eds.), The economics of artificial intelligence: An agenda (pp. 23–57). Routledge.

Chelli

Descamps

Lavoué

Trojani

Azar

Deckert

Raynier

J.–L.

Clowez

Boileau

Ruetsch-Chelli

(2024). Hallucination rates and reference accuracy of ChatGPT and Bard for systematic reviews: Comparative analysis. Journal of Medical Internet Research, 26, e53164. https://doi.org/10.2196/53164

Chen

Chan

(2024). Large language model in creative work: The role of collaboration modality and user expertise. Management Science, 70(12), 9101–9117. https://doi.org/10.1287/mnsc.2023.03014

10.

Choudhary

Marchetti

Shrestha

Y. R.

Puranam

(2025). Human-AI ensembles: When can they work? Journal of Management, 51(2), 536–569. https://doi.org/10.1177/01492063231194968

11.

Choudhury

M. D.

Lee

M. K.

Zhu

Shamma

D. A.

(2020). Introduction to this special issue on unifying human computer interaction and artificial intelligence. Human–Computer Interaction, 35(5–6), 355–361. https://doi.org/10.1080/07370024.2020.1744146

12.

Crede

Sotola

L. K.

(2024). All is well that replicates well: The replicability of reported moderation and interaction effects in leading organizational sciences journals. Journal of Applied Psychology, 109(10), 1659–1667. https://doi.org/10.1037/apl0001197

13.

Dell’Acqua

Ayoubi

Lifshitz

Sadun

Mollick

Han

Goldman

Nair

Taub

(2025). The cybernetic teammate: A field experiment on generative AI reshaping teamwork and expertise. Harvard Business School Working Paper (No. 25-043). https://doi.org/10.3386/w33641

14.

Dell’Acqua

McFowland

III Mollick

E. R.

Lifshitz-Assaf

Kellogg

Rajendran

Krayer

Candelon

Lakhani

K. R.

(2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality. Harvard Business School Technology & Operations Management. Unit Working Paper (No. 24-013). https://doi.org/10.2139/ssrn.4573321

15.

DellaVigna

Linos

(2022). RCTs to scale: Comprehensive evidence from two nudge units. Econometrica, 90(1), 81–116. https://doi.org/10.3982/ecta18709

16.

de Melo

Carnevale

Gratch

. (2014). Social categorization and cooperation between humans and computers. Proceedings of the Annual Meeting of the Cognitive Science Society, 36, 2109–2114. https://escholarship.org/uc/item/5k62p6c3

17.

Demir

Canan

Cohen

M. C.

(2023). Modeling team interaction and decision-making in agile human–machine teams: Quantum and dynamical systems perspective. IEEE Transactions on Human-Machine Systems, 53(4), 720–730. https://doi.org/10.1109/thms.2023.3276744

18.

Demir

Cohen

Johnson

C. J.

Chiou

E. K.

Cooke

N. J.

(2023). Exploration of the impact of interpersonal communication and coordination dynamics on team effectiveness in human-machine teams. International Journal of Human–Computer Interaction, 39(9), 1841–1855. https://doi.org/10.1080/10447318.2022.2143004

19.

Demir

McNeese

N. J.

Cooke

N. J.

(2017). Team situation awareness within the context of human-autonomy teaming. Cognitive Systems Research, 46, 3–12. https://doi.org/10.1016/j.cogsys.2016.11.003

20.

Dennis

A. R.

Lakhiwal

Sachdeva

(2023). AI agents as team members: Effects on satisfaction, conflict, trustworthiness, and willingness to work with. Journal of Management Information Systems, 40(2), 307–337. https://doi.org/10.1080/07421222.2023.2196773

21.

Dibble

Gibson

C. B.

(2018). Crossing team boundaries: A theoretical model of team boundary permeability and a discussion of why it matters. Human Relations, 71(7), 925–950. https://doi.org/10.1177/0018726717735372

22.

Douthat

(2025, May 15). An interview with the herald of the apocalypse. New York Times. https://www.nytimes.com/2025/05/15/opinion/artifical-intelligence-2027.html

23.

Engstrom

D. F.

Haim

(2023). Regulating government AI and the challenge of sociotechnical design. Annual Review of Law and Social Science, 19(1), 277–298. https://doi.org/10.1146/annurev-lawsocsci-120522-091626

24.

Erengin

Briker

de Jong

S. B.

(2025). You, me, and the AI: The role of third-party human teammates for trust formation toward AI teammates. Journal of Organizational Behavior. https://doi.org/10.1002/job.2857

25.

Farquhar

Kossen

Kuhn

Gal

(2024). Detecting hallucinations in large language models using semantic entropy. Nature, 630(8017), 625–630. https://doi.org/10.1038/s41586-024-07421-0

26.

Fernandez-Borsot

(2025). Artificial intelligence and the future of otherness: What kind of other can an AI be for a human? AI & Society, 1–15. https://doi.org/10.1007/s00146-025-02281-2

27.

Flathmann

Schelble

B. G.

Rosopa

P. J.

McNeese

N. J.

Mallick

Madathil

K. C.

(2023). Examining the impact of varying levels of AI teammate influence on human-AI teams. International Journal of Human-Computer Studies, 177, 103061. https://doi.org/10.1016/j.ijhcs.2023.103061.

28.

Glikson

Woolley

A. W.

(2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057

29.

Griffith

T. L.

(2012). Technology and teams: The next ten years. In Neale

M. A.

Mannix

E. A.

(Eds.), Looking back, moving forward: A review of group and team-based research (pp. 245–278). Emerald Group Publishing Limited. https://doi.org/10.1108/s1534-0856(2012)0000015013

30.

Grote

Parker

S. K.

Crowston

(2024). Taming artificial intelligence: A theory of control-acountability alignment among AI developers and users. Academy of Management Review. Advance online publication. https://doi.org/10.5465/amr.2023.0117

31.

Guo

(2025, February 6). The Nomi AI chatbot told a user to kill himself. Who is to blame? MIT Technology Review. https://www.technologyreview.com/2025/02/06/1111077/nomi-ai-chatbot-told-user-to-kill-himself/

32.

Harris-Watson

A. M.

Larson

L. E.

Lauharatanahirun

DeChurch

L. A.

Contractor

N. S.

(2023). Social perception in human-AI teams: Warmth and competence predict receptivity to AI teammates. Computers in Human Behavior, 145, 107765. https://doi.org/https://doi.org/10.1016/j.chb.2023.107765

33.

Liu

Zheng

Hewlin

P. F.

Yuan

(2023). Being proactive in the age of AI: Exploring the effectiveness of leaders’ AI symbolization in stimulating employee job crafting. Management Decision, 61(10), 2896–2919. https://doi.org/10.1108/md-10-2022-1390

34.

Heyselaar

(2023). The CASA theory no longer applies to desktop computers. Scientific Reports, 13(1), 19693. https://doi.org/10.1038/s41598-023-46527-9

35.

Hillebrand

Raisch

Schad

(2025). Managing with artificial intelligence: An integrative framework. Academy of Management Annals, 19(1), 343–375. https://doi.org/10.5465/annals.2022.0072

36.

Hoff

K. A.

Bashir

(2015). Trust in automation: Integrating empirical evidence on factors that influence trust. Human Factors, 57(3), 407–434. https://doi.org/10.1177/0018720814547570

37.

Jarrahi

M. H.

Glaser

(2024). Not all AI systems are created equal: A typology of AI systems’ performance and affordance [Conference session]. Proceedings of the 58th Annual Hawaii International Conference on Systems Sciences, Kona, Hawaii (pp. 5449–5458). https://doi.org/10.24251/hicss.2025.655

38.

Jones

(2025). AI hallucinations can’t be stopped—But these techniques can limit their damage. Nature, 637(8047), 778–780. https://doi.org/10.1038/d41586-025-00068-5

39.

Kane

Paletz

Diep

Hajkowski

Porter

(2025). Virtual collaborative analysis: Effects of two AI summarizers. Small Group Research, 56(5), 821–863.

40.

Katzenbach

Smith

(1992). The wisdom of teams: Creating the high-performance organization. Harvard Business Press.

41.

Keyton

Heylen

D. K.

(2017). Pushing interdisciplinary in the study of groups and teams. Small Group Research, 48(5), 621–630. https://doi.org/10.1177/1046496417732528

42.

Kou

C.-Y.

Stewart

(2018). Group accountability: A review and extension of existing research. Small Group Research, 49(1), 34–61. https://doi.org/10.1177/1046496417712438

43.

Larson

DeChurch

L. A.

(2020). Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams. The Leadership Quarterly, 31(1), 101377. https://doi.org/https://doi.org/10.1016/j.leaqua.2019.101377

44.

Levine

J. M.

Moreland

R. L.

(1998). Small groups. In Gilbert

D. T.

Fiske

S. T.

Lindzey

(Eds.), Handbook of social psychology (4th ed., pp. 415–429). McGraw.

45.

A. N.

Sherf

E. N.

Tangirala

(2023). Team adaptation to discontinuous task change: Equity and equality as facilitators of individual and collective task capabilities redevelopment. Organization Science, 34(3), 1287–1314. https://doi.org/10.1287/orsc.2022.1621

46.

van Knippenberg

(2021). The team causes and consequences of team membership change: A temporal perspective. Academy of Management Annals, 15(2), 577–606.

47.

Liew

(2018). The future of radiology augmented with artificial intelligence: A strategy for success. European Journal of Radiology, 102, 152–156. https://doi.org/10.1016/j.ejrad.2018.03.019

48.

Lyons

J. B.

Sycara

Lewis

Capiola

(2021). Human-autonomy teaming: Definitions, debates, and directions. Frontiers in Psychology, 12, 589585. https://doi.org/10.3389/fpsyg.2021.589585

49.

Malhotra

Majchrzak

Lyytinen

(2021). Socio-technical affordances for large-scale collaborations: Introduction to a virtual special issue. Organization Science, 32(5), 1371–1390. https://doi.org/10.1287/orsc.2021.1457

50.

Man Tang

Koopman

McClean

S. T.

Zhang

J. H.

C. H.

De Cremer

C. T. S

. (2022). When conscientious employees meet intelligent machines: An integrative approach inspired by complementarity theory and role theory. Academy of Management Journal, 65(3), 1019–1054. https://doi.org/10.5465/amj.2020.1516

51.

Mathieu

J. E.

Tannenbaum

S. I.

Donsbach

J. S.

Alliger

G. M.

(2014). A review and integration of team composition models: Moving toward a dynamic and temporal framework. Journal of Management, 40(1), 130–160. https://doi.org/10.1177/0149206313503014

52.

Mathieu

J. E.

Wolfson

M. A.

Park

(2018). The evolution of work team research since Hawthorne. American Psychologist, 73(4), 308. https://doi.org/10.1037/amp0000255

53.

Mayer

Yee

Chui

Roberts

(2025). Superagency in the workplace: Empowering people to unlock AI’s full potential at work. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work

54.

McClain

(2024, March 26). Americans’ use of ChatGPT is ticking up, but few trust its election information. Pew Research Center. https://www.pewresearch.org/short-reads/2024/03/26/americans-use-of-chatgpt-is-ticking-up-but-few-trust-its-election-information/

55.

McNeese

N. J.

Flathmann

O’Neill

T. A.

Salas

(2023). Stepping out of the shadow of human-human teaming: Crafting a unique identity for human-autonomy teams. Computers in Human Behavior, 148, 1–8. https://doi.org/10.1016/j.chb.2023.107874

56.

McNeese

N. J.

Schelble

B. G.

Canonico

L. B.

Demir

(2021). Who/what is my teammate? Team composition considerations in human–AI teaming. IEEE Transactions on Human-Machine Systems, 51(4), 288–299. https://doi.org/10.1109/THMS.2021.3086018

57.

Mortensen

Haas

M. R.

(2018). Perspective—Rethinking teams: From bounded membership to dynamic participation. Organization Science, 29(2), 341–355. https://doi.org/10.1287/orsc.2017.1198

58.

Nass

Fogg

B. J.

Moon

(1996). Can computers be teammates? International Journal of Human-Computer Studies, 45(6), 669–678. https://doi.org/10.1006/ijhc.1996.0073

59.

Waltman

(2024). To preprint or not to preprint: A global researcher survey. Journal of the Association for Information Science and Technology, 75(6), 749–766. https://doi.org/10.1002/asi.24880

60.

O’Neill

McNeese

Barron

Schelble

(2022). Human–autonomy teaming: A review and analysis of the empirical literature. Human Factors, 64(5), 904–938. https://doi.org/10.1177/0018720820960865

61.

Pereira

Hadjielias

Christofi

Vrontis

(2023). A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective. Human Resource Management Review, 33(1), 100857. https://doi.org/10.1016/j.hrmr.2021.100857

62.

Perrow

(1983). The organizational context of human factors engineering. Administrative Science Quarterly, 28(4), 521–541. https://doi.org/10.2307/2393007

63.

Pilny

Bonito

Schecter

(2025). Coding small group communication with AI: RNNs and transformers with context. Small Group Research, 56(5), 864–893. https://doi.org/10.1177/10464964251314197

64.

Qin

Zhou

Chen

Zhou

Dong

Cao

J. G.

(2025). AI aversion or appreciation? A capability–personalization framework and a meta-analytic review. Psychological Bulletin, 151(5), 580. https://doi.org/10.1037/bul0000477

65.

Rainie

(2025). Large language model use and impact: A user study report. Imagining the Digital Future Center, Elon University. https://imaginingthedigitalfuture.org/wp-content/uploads/2025/03/ITDF-LLM-User-Report-3-12-25.pdf

66.

Raisch

Fomina

(2025). Combining human and artificial intelligence: Hybrid problem-solving in organizations. Academy of Management Review, 50(2), 441–464. https://doi.org/10.5465/amr.2021.0421

67.

Reeves

Nass

(1996). The media equation: How people treat computers, television, and new media like real people and places (pp. 19–36). Cambridge University Press.

68.

Reich

Teeny

J. D.

(2025). Does artificial intelligence cause artificial confidence? Generative artificial intelligence as an emerging social referent. Journal of Personality and Social Psychology. Advance online publication. https://doi.org/10.1037/pspa0000450

69.

Reis

Kunde

(2024). Influence of believed AI involvement on the perception of digital medical advice. Nature Medicine, 30(11), 3098–3100. https://doi.org/10.1038/s41591-024-03180-7

70.

Rogers

E. M.

(2003). Diffusion of innovations (5th ed.). Free Press.

71.

Sachin

P. K.

Schecter

(2024). Advice utilization incombined human-algorithm decision-making: An analysis of preferences and behaviors. Journal of the Association for Information Systems, 25(6), 1439–1465. https://doi.org/10.17705/1jais.00896

72.

Sarala

R. M.

Post

Doh

Muzio

(2025). Advancing research on the future of work in the age of artificial intelligence (AI). Journal of Management Studies. Advance online publication. https://doi.org/10.1111/joms.13195

73.

Schelble

B. G.

Lopez

Textor

Zhang

McNeese

N. J.

Pak

Freeman

(2024). Towards ethical AI: Empirically investigating dimensions of AI ethics, trust repair, and performance in human-AI teaming. Human Factors, 66(4), 1037–1055. https://doi.org/10.1177/00187208221116952

74.

Schmutz

J. B.

Outland

Kerstan

Georganta

Ulfert

A.-S.

(2024). AI-teaming: Redefining collaboration in the digital era. Current Opinion in Psychology, 58, 101837. https://doi.org/10.1016/j.copsyc.2024.101837

75.

Siegel

Eder

J. S. N.

Wicherts

J. M.

Pietschnig

(2022). Times are changing, bias isn’t: A meta-meta-analysis on publication bias detection practices, prevalence rates, and predictors in industrial/organizational psychology. Journal of Applied Psychology, 107(11), 2013. https://doi.org/10.1037/apl0000991

76.

Siemon

(2022). Elaborating team roles for artificial intelligence-based teammates in human-00AI collaboration. Group Decision and Negotiation, 31(5), 871–912. https://doi.org/10.1007/s10726-022-09792-z

77.

SimanTov-Nachlieli

(2025). More to lose: The adverse effect of high performance ranking on employees’ preimplementation attitudes toward the integration of powerful AI aids. Organization Science, 36(1), 1–20. https://doi.org/10.1287/orsc.2023.17515

78.

Smith

van Wagoner

H. P.

Keplinger

Celebi

(2025). Navigating AI convergence in human–artificial intelligence teams: A signaling theory approach. Journal of Organizational Behavior. Advance online publication. https://doi.org/10.1002/job.2856

79.

Smith

(2023, February 2). ChatGPT is amazing—and scary. Investors should take note. Barron’s. https://www.barrons.com/articles/chatgpt-investors-ai-microsoft-stock-51675284609

80.

Smith

(2021). Clinical AI: Opacity, accountability, responsibility and liability. AI & Society, 36(2), 535–545. https://doi.org/10.1007/s00146-020-01019-6

81.

Stollberger

Anand

Dick

(2025). Capturing a moving target: Developing research on and with AI for human relations. Human Relations, 78(5), 499–516. https://doi.org/10.1177/00187267251332075

82.

Trainer

H. M.

Jones

J. M.

Pendergraft

J. G.

Maupin

C. K.

Carter

D. R.

(2020). Team membership change “events”: A review and reconceptualization. Group & Organization Management, 45(2), 219–251. https://doi.org/10.1177/1059601120910848

83.

Trist

E. L.

Bamforth

K. W.

(1951). Some social and psychological consequences of the longwall method of coal-getting: An examination of the psychological situation and defences of a work group in relation to the social structure and technological content of the work system. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101

84.

Tufekci

(2025, May 17). For one hilarious, terrifying day, Elon Musk’s chatbot lost its mind. The New York Times. https://www.nytimes.com/2025/05/17/opinion/grok-ai-musk-x-south-africa.html

85.

Vaccaro

Almaatouq

Malone

(2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8, 2293–2303. https://doi.org/10.1038/s41562-024-02024-1

86.

Vanneste

B. S.

Puranam

(2024). Artificial intelligence, trust, and perceptions of agency. Academy of Management Review. Advance online publication. https://doi.org/10.5465/amr.2022.0041

87.

von Krogh

Roberson

Gruber

. (2023). Recognizing and utilizing novel research opportunities with artificial intelligence. Academy of Management Journal, 66(2), 367–373. https://doi.org/10.5465/amj.2023.4002

88.

Wageman

Gardner

Mortensen

(2012). The changing ecology of teams: New directions for teams research. Journal of Organizational Behavior, 33(3), 301–315. https://doi.org/10.1002/job.1775

89.

Walliser

J. C.

de Visser

E. J.

Wiese

Shaw

T. H.

(2019). Team structure and team building improve human–machine teaming with autonomous agents. Journal of Cognitive Engineering and Decision Making, 13(4), 258–278. https://doi.org/10.1177/1555343419867563

90.

Wang

Gao

Agarwal

(2024). Friend or foe? Teaming between artificial intelligence and workers with variation in experience. Management Science, 70(9), 5753–5775. https://doi.org/10.1287/mnsc.2021.00588

91.

Westphal

Vössing

Satzger

Yom-Tov

G. B.

Rafaeli

(2023). Decision control and explanations in human-AI collaboration: Improving user perceptions and compliance. Computers in Human Behavior, 144, 107714. https://doi.org/10.1016/j.chb.2023.107714

92.

Wolf

F. D.

Stock-Homburg

R. M.

(2023). How and when can robots be team members? Three decades of research on human–robot teams. Group & Organization Management, 48(6), 1666–1744. https://doi.org/10.1177/10596011221076636

93.

Yam

K. C.

Eng

Gray

(2024). Machine replacement: A mind-role fit perspective. Annual Review of Organizational Psychology and Organizational Behavior, 12, 239–267. https://doi.org/10.1146/annurev-orgpsych-030223-044504

94.

You

Robert

(2023). Trusting and working with robots: A relational demography theory of preference for robotic over human co-workers. MIS Quarterly, 48(4), 1297–1330. https://doi.org/10.25300/misq/2023/17403

95.

Zammuto

R. F.

Griffith

T. L.

Majchrzak

Dougherty

D. J.

Faraj

(2007). Information technology and the changing fabric of organization. Organization Science, 18(5), 749–762. https://doi.org/10.1287/orsc.1070.0307

96.

Zhou

Porat

van Zalk

(2024). Humans mindlessly treat AI virtual agents as social beings, but this tendency diminishes among the young: Evidence from a Cyberball experiment. Human Behavior and Emerging Technologies, 2024(1), 8864909. https://doi.org/10.1155/2024/8864909