Artificial intelligence (AI) has become part and parcel of scientific knowledge production since the latest iterations of generative AI models (e.g., ChatGPT, DeepSeek, Claude, or Gemini) became widely available. Given AI has rapidly evolved since the initial release of ChatGPT in 2022, researching how AI’s capabilities impact organizations and how researchers make use of AI tools can be likened to a moving target. In this editorial essay, we explore the implications of the introduction of AI in the context of academic research, both as the subject of investigation (i.e., research on AI) and as a research tool to facilitate academic writing, data generation, or the peer review process (i.e., research with AI). Specifically, concerning research on AI, we consider issues around clarity regarding both existing definitions and concepts in the AI literature and how these are influenced by the rapid technological evolution of AI’s capabilities. In regard to research with AI, we reflect on the advantages and disadvantages of the use of AI as a research tool and discuss the Human Relations AI Usage Policy. Overall, our aim is not to be overly prescriptive on how to conduct research on and with AI but to encourage authors to reflect on how to best capture AI as a moving target in the context of their research endeavors.
AczelBBarwichASDiekmanAB, et al. (2025) The present and future of peer review: Ideas, interventions, and evidence. Proceedings of the National Academy of Sciences of the United States of America122(5): e2401232121. DOI: 10.1073/pnas.2401232121.
2.
AguinisHRamaniRAlabduljaderN (2018) What you see is what you get? Enhancing methodological transparency in management research. Academy of Management Annals12(1): 1–28. DOI: 10.5465/annals.2016.0011.
3.
AmabileTM (2020) GUIDEPOST: Creativity, artificial intelligence, and a world of surprises. Academy of Management Discoveries6(3): 351–354.
4.
AstleyWGZammutoRF (1992) Organization science, managers, and language games. Organization Science3(4): 443–460. DOI: 10.1287/orsc.3.4.443.
5.
BankinsSOcampoACMarroneM, et al. (2024) A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior45(2): 159–182. DOI: 10.1002/job.2735.
6.
BechkyBADavisGF (2025) Resisting the algorithmic management of science: Craft and community after generative AI. Administrative Science Quarterly70(1): 1–22. DOI: 10.1177/00018392241304403.
7.
BengioYHintonGYaoA, et al. (2024) Managing extreme AI risks amid rapid progress. Science384(6698): 842–845. DOI: 10.1126/science.adn0117.
8.
BerenteNGuBReckerJ, et al. (2021) Managing artificial intelligence. Management Information Systems Quarterly45(3): 1433–1450. DOI: 10.25300/MISQ/2021/16274.
9.
BudhwarPChowdhurySWoodG, et al. (2023) Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal33(3): 606–659. DOI: 10.1111/1748-8583.12524.
10.
ChanMEArveyRD (2012) Meta-analysis and the development of knowledge. Source: Perspectives on Psychological Science7(1): 79–92.
11.
ChawlaDS (2024) Is ChatGPT corrupting peer review? Telltale words hint at AI use. Nature628(8008): 483–484.
12.
CheccoABraccialeLLoretiP, et al. (2021) AI-assisted peer review. Humanities and Social Sciences Communications8(1): 25. DOI: 10.1057/s41599-020-00703-8.
13.
CornelissenJHöllererMABoxenbaumE, et al. (2024) Large language models and the future of organization theory. Organization Theory5(1): 1–15. DOI: 10.1177/26317877241239056.
14.
CroninMAStoutenJvan KnippenbergD (2021a) The theory crisis in management research: Solving the right problem. Academy of Management Review46(4): 667–683. DOI: 10.5465/amr.2019.0294.
15.
CroninMAStoutenJvan KnippenbergD (2021b) Why theory on “how theory fits together” benefits management scholarship. Academy of Management Review47(2): 333–337. DOI: 10.5465/amr.2021.0517.
DeliosATungRLvan WitteloostuijnA (2024) How to intelligently embrace generative AI: The first guardrails for the use of GenAI in IB research. Journal of International Business Studies. DOI: 10.1057/s41267-024-00736-0.
18.
DergaaIChamariKZmijewskiP, et al. (2023) From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing. Biology of Sport40(2): 615–622. DOI: 10.5114/BIOLSPORT.2023.125623.
19.
DiekmannA (2022) Emergence of and compliance with new social norms: The example of the COVID crisis in Germany. Rationality and Society34(2): 129–154. https://doi.org/10.1177/10434631221092749
20.
DoshiARHauserOP (2024) Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science10(28): 1–9.
21.
DriesNLuyckxJRogiersP (2024) Imagining the (distant) future of work. Academy of Management Discoveries10(3): 319–350. DOI: 10.5465/amd.2022.0130.
22.
DwivediYKKshetriNHughesL, et al. (2023) “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management71(C): 1–63.
23.
EinolaKKhorevaVTienariJ (2024) A colleague named Max: A critical inquiry into affects when an anthropomorphised AI (ro)bot enters the workplace. Human Relations77(11): 1620–1649. DOI: 10.1177/00187267231206328.
24.
EpleyNWaytzACacioppoJT (2007) On seeing human: A three-factor theory of anthropomorphism. Psychological Review114(4): 864–886. DOI: 10.1037/0033-295X.114.4.864.
25.
FanJSunTLiuJ, et al. (2023) How well can an AI chatbot infer personality? Examining psychometric properties of machine-inferred personality scores. Journal of Applied Psychology108(8): 1277–1299. DOI: 10.1037/apl0001082.
26.
FountainTMcCarthyBSalehT (2019) Building the AI-powered organization. Harvard Business Review7: 62–73.
27.
FredbergTSchwarzGM (2024) What AI knows: Shaping work and pushing ideas on changing organizations. The Journal of Applied Behavioral Science 60(4): 581–588. DOI: 10.1177/00218863241285218.
28.
GatrellCMuzioDPostC, et al. (2024) Here, there and everywhere: On the responsible use of artificial intelligence (AI) in management research and the peer-review process. Journal of Management Studies61(3): 739–751. DOI: 10.1111/joms.13045.
29.
GiarmoleoFVFerreroIRocchiM, et al. (2024) What ethics can say on artificial intelligence: Insights from a systematic literature review. Business and Society Review129(2): 258–292. DOI: 10.1111/basr.12336.
30.
GliksonEWoolleyAW (2020) Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals14(2): 627–660. DOI: 10.5465/annals.2018.0057.
31.
GoertzGMahoneyJ (2012) A Tale of Two Cultures: Qualitative and Quantitative Research in the Social Sciences. Princeton, NJ; Princeton University Press.
32.
GolgeciIRitalaPArslanA, et al. (2025) Confronting and alleviating AI resistance in the workplace: An integrative review and a process framework. Human Resource Management Review35(2): 101075. https://doi.org/10.1016/j.hrmr.2024.101075
33.
GonzalezOMacKinnonDPMunizFB (2021) Extrinsic convergent validity evidence to prevent jingle and jangle fallacies. Multivariate Behavioral Research56(1): 3–19. DOI: 10.1080/00273171.2019.1707061.
34.
GraßmannCSchermulyCC (2021) Coaching with artificial intelligence: Concepts and capabilities. Human Resource Development Review20(1): 106–126. DOI: 10.1177/1534484320982891.
35.
GrimesMVon KroghGFeuerriegelS, et al. (2023) From scarcity to abundance: Scholars and scholarship in an age of generative artificial intelligence. Academy of Management Journal66(6): 1617–1624. DOI: 10.5465/amj.2023.4006.
36.
GrossmannIFeinbergMParkerDC, et al. (2023) AI and the transformation of social science research. Science380(6650): 1108–1109. DOI: 10.1126/science.adi1778.
37.
GümüsayAAReineckeJ (2024) Imagining desirable futures: A call for prospective theorizing with speculative rigour. Organization Theory5(1): 1–23. DOI: 10.1177/26317877241235939.
38.
HaidtJ (2024) The Anxious Generation. London: Penguin Books.
39.
HaidtJLukianoffG (2019) The Coddling of the American Mind. London: Penguin Books.
40.
HermannEPuntoniS (2024) Artificial intelligence and consumer behavior: From predictive to generative AI. Journal of Business Research180: 114720. DOI: 10.1016/j.jbusres.2024.114720.
HillebrandLRaischSSchadJ (2025) Managing with artificial intelligence: An integrative framework. Academy of Management Annals19(1): 343–375. DOI: 10.5465/annals.2022.0072.
43.
HuangMHRustRMaksimovicV (2019) The feeling economy: Managing in the next generation of Artificial Intelligence (AI). California Management Review61(4): 43–65. DOI: 10.1177/0008125619863436.
44.
HuismanJSmitsJ (2017) Duration and quality of the peer review process: The author’s perspective. Scientometrics113(1): 633–650. DOI: 10.1007/s11192-017-2310-5.
45.
JagoASRaveendhranRFastN, et al. (2024) Algorithmic management diminishes status: An unintended consequence of using machines to perform social roles. Journal of Experimental Social Psychology110(1): 104553.
46.
JiaNLuoXFangZ, et al. (2024) When and how artificial intelligence augments employee creativity. Academy of Management Journal67(1): 5–32.
KeeganAMeijerinkJ (2025) Algorithmic management in organizations? From edge case to center stage. Annual Review of Organizational Psychology and Organizational Behavior12(1): 395–422. DOI: 10.1146/annurev-orgpsych-110622.
49.
KelleyEL (1927) Interpretation of Educational Measurements. Yonkers-on-Hudson: World Book Co.
50.
KuhnT (1970) The Structure of Scientific Revolutions. Chicago, IL: University of Chicago Press.
51.
KulkarniMMantereSVaaraE, et al. (2024) The future of research in an artificial intelligence-driven world. Journal of Management Inquiry33(3): 207–229. DOI: 10.1177/10564926231219622.
52.
LangerMHunsickerTFeldkampT, et al. (2022) “Look! It’s a computer program! It’s an algorithm! It’s AI!”: Does terminology affect human perceptions and evaluations of algorithmic decision-making systems? In: Conference on human factors in computing systems—Proceedings, 29 April 2022, New Orleans, USA. DOI: 10.1145/3491102.3517527.
53.
LangerMLandersRN (2021) The future of artificial intelligence at work: A review on effects of decision automation and augmentation on workers targeted by algorithms and third-party observers. Computers in Human Behavior123: 106878. DOI: 10.1016/j.chb.2021.106878.
54.
LarsonBZMoserCCazaA, et al. (2024) From the editors: Critical thinking in the age of generative AI. Academy of Management Learning & Education23(3): 373–378. DOI: 10.5465/amle.2024.0338.
55.
LeeBCChungJ (2024) An empirical investigation of the impact of ChatGPT on creativity. Nature Human Behaviour8(10): 1906–1914. DOI: 10.1038/s41562-024-01953-1.
56.
LevyDLSpicerA (2013) Contested imaginaries and the cultural political economy of climate change. Organization20(5): 659–678. DOI: 10.1177/1350508413489816.
57.
LiangWIzzoZZhangY, et al. (2024) Monitoring AI-modified content at scale: A case study on the impact of ChatGPT on AI conference peer reviews. ArXiv. DOI: https://arxiv.org/abs/2403.07183.
58.
LindebaumDFlemingP (2024) ChatGPT undermines human reflexivity, scientific responsibility and responsible management research. British Journal of Management35(2): 566–575. DOI: 10.1111/1467-8551.12781.
59.
LindebaumDMoserCIslamG (2024) Big data, proxies, algorithmic decision-making and the future of management theory. Journal of Management Studies61(6): 2724–2747. DOI: 10.1111/joms.13032.
60.
MackenzieSB (2003) The dangers of poor construct conceptualization. 31(3): 323–326. DOI: 10.1177/0092070303254130.
61.
ManningBSZhuKHortonJJ (2024) Automated social science: Language models as scientist and subjects. ArXiv. DOI: http://arxiv.org/abs/2404.11794.
62.
MarianiMMHashemiNWirtzJ (2023) Artificial Intelligence-empowered conversational agents: A systematic literature review and research agenda. Journal of Business Research161(C): 1–61. DOI: 10.1016/j.jbusres.2023.113838.
63.
MatthewsMJSuRYonishL, et al. (2025) A review of artificial intelligence, algorithms, and robots through the lens of stakeholder theory. Journal of Management. DOI: 10.1177/01492063241311855.
64.
MatzSCTeenyJDVaidSS, et al. (2024) The potential of generative AI for personalized persuasion at scale. Scientific Reports14(1): 4692.
MoserCden HondFLindebaumD (2022) Morality in the age of artificially intelligent algorithms. Academy of Management Learning and Education21(1): 139–155. DOI: 10.5465/amle.2020.0287?journalCode=amle.
OgbonnayaCBrownAD (2023) Editorial: Crafting review and essay articles forHuman Relations. Human Relations76(3): 365–394. DOI: 10.1177/00187267221148440.
69.
ParkerSKGroteG (2020) Automation, algorithms, and beyond: Why work design matters more than ever in a digital world. Applied Psychology71(4): 1171–1204. DOI: 10.1111/apps.12241.
70.
PeelMRodgersLde la Torre ArenasI, et al. (2024) Are the robots finally coming? Advances in physical AI mean machines are learning skills previously thought impossible. Financial Times. Available at: https://ig.ft.com/ai-robots/ (accessed 15 March 2025).
PinskiMBenlianA (2024) AI literacy for users – A comprehensive review and future research directions of learning methods, components, and effects. Computers in Human Behavior: Artificial Humans2(1), 100062. DOI: 10.1016/j.chbah.2024.100062.
73.
PodsakoffPMMacKenzieSBPodsakoffNP (2016) Recommendations for creating better concept definitions in the organizational, behavioral, and social sciences. Organizational Research Methods19(2): 159–203. DOI: 10.1177/1094428115624965.
74.
RaischSKrakowskiS (2021) Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review46(1): 192–210. DOI: 10.5465/amr.2018.0072.
75.
RouseED (2020) Where you end and I begin: Understanding intimate co-creation. Academy of Management Review45(1): 181–204. DOI: 10.5465/amr.2016.0388.
76.
SamoiliSLópez CoboMDelipetrevB, et al. (2021) AI watch, defining Artificial Intelligence 2.0: Towards an operational definition and taxonomy for the AI landscape. Luxembourg: Publications Office of the European Union.
77.
SarkerSSusarlaAGopalR, et al. (2024) Democratizing knowledge creation through Human-AI collaboration in academic peer review. Journal of the Association for Information Systems25(1): 158–171. DOI: 10.17705/1jais.00872.
78.
SarstedtMAdlerSJRauL, et al. (2024) Using large language models to generate silicon samples in consumer and marketing research: Challenges, opportunities, and guidelines. Psychology and Marketing41(6), 1254–1270. DOI: 10.1002/mar.21982.
79.
SaxlerFMDorroughARFroehlichL, et al. (2024) Did descriptive and prescriptive norms about gender equality at home change during the COVID-19 pandemic? A cross-national investigation. Personality and Social Psychology Bulletin. https://doi.org/10.1177/01461672231219719
80.
ShafferJADeGeestDLiA (2016) Tackling the problem of construct proliferation: A guide to assessing the discriminant validity of conceptually related constructs. Organizational Research Methods19(1): 80–110. DOI: 10.1177/1094428115598239.
81.
ShumailovIShumaylovZZhaoY, et al. (2024) AI models collapse when trained on recursively generated data. Nature631(8022): 755–759. DOI: 10.1038/s41586-024-07566-y.
82.
SolingerONHeusinkveldSCornelissenJP (2024) Redefining concepts to build theory: A repertoire for conceptual innovation. Human Resource Management Review34(1): 1–17. DOI: 10.1016/j.hrmr.2023.100988.
83.
SpitaleMAxelssonMGunesH (2023) Robotic mental well-being coaches for the workplace: An in-the-wild study on form. In:ACM/IEEE International Conference on Human-Robot Interaction, 301–310. DOI: 10.1145/3568162.3577003
84.
SuddabyR (2010) Editor’s comments: Construct clarity in theories of management and organization. Academy of Management Review35(3): 346–357. DOI: 10.5465/amr.35.3.zok346.
85.
TerblancheN (2024) Artificial Intelligence (AI) coaching: Redefining people development and organizational performance. The Journal of Applied Behavioral Science60(4): 631–638. DOI: 10.1177/00218863241283919.
86.
TerblancheNMolynJde HaanE, et al. (2022) Comparing artificial intelligence and human coaching goal attainment efficacy. PLoS One17(6): 1–17. DOI: 10.1371/journal.pone.0270255.
87.
TsaiCYMarshallJDChoudhuryA, et al. (2022) Human-robot collaboration: A multilevel and integrated leadership framework. The Leadership Quarterly33(1): 1–18. DOI: 10.1016/j.leaqua.2021.101594.
88.
TullySLongoniCAppelG, et al. (2025) Lower artificial intelligence literacy predicts greater AI receptivity. Journal of Marketing. DOI: 10.1177/00222429251314491.
89.
Van DisEAMBollenJVan RooijR, et al. (2023) ChatGPT: Five priorities for research. Nature614(7947): 224–226.
90.
Van QuaquebekeNGerpottFH (2023) The now, new, and next of digital leadership: How artificial intelligence (AI) will take over and change leadership as we know it. Journal of Leadership and Organizational Studies30(3): 265–275. DOI: 10.1177/15480518231181731.
91.
von KroghG (2018) Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing. Academy of Management Discoveries4(4): 404–409. DOI: 10.5465/amd.2018.0084.
92.
von KroghGRobersonQGruberM (2023) From the editors: Recognizing and utilizing novel research opportunities with artificial intelligence. Academy of Management Journal66(2): 367–373. DOI: 10.5465/amj.2023.4002.
93.
WackerJG (2004) A theory of formal conceptual definitions: Developing theory-building measurement instruments. Journal of Operations Management22(6): 629–650. DOI: 10.1016/j.jom.2004.08.002.
94.
WangPLoignonACShresthaS, et al. (2024) Advancing organizational science through synthetic data: A path to enhanced data sharing and collaboration. Journal of Business and Psychology. DOI: 10.1007/s10869-024-09997-w.
95.
WeberULömkerMMoskaliukJ (2021) The human touch: The impact of anthropomorphism in chatbots on the perceived success of solution focused coaching. Management Revue32(4): 385–407. DOI: 10.5771/0935-9915-2021-4-385.
96.
WeibelASchafheitleSWerffL (2023) Smart tech is all around us – bridging employee vulnerability with organizational active trust-building. Journal of Management Studies. Advance online publication. DOI: 10.1111/joms.12940.
97.
WynnG (2024) Reformative concept analysis for applied psychology qualitative research. Qualitative Research in Psychology21(3): 251–278. DOI: 10.1080/14780887.2024.2346851.
98.
XingXShiFHuangJ, et al. (2025) On the caveats of AI autophagy. Nature Machine Intelligence7(2): 172–180. DOI: 10.1038/s42256-025-00984-1.
99.
YamKCBigmanYETangPM, et al. (2021) Robots at work: People prefer—And forgive—Service robots with perceived feelings. Journal of Applied Psychology106(10): 1557–1572. DOI: 10.1037/apl0000834.
100.
ZhangRWLiangXWuSH (2024) When chatbots fail: Exploring user coping following a chatbots-induced service failure. Information Technology and People37(8): 175–195. DOI: 10.1108/ITP-08-2023-0745.
