The rapid, widespread implementation of artificial intelligence technologies in workplaces has implications for business communication. In this article, the authors describe current capabilities, challenges, and concepts related to the adoption and use of artificial intelligence (AI) technologies in business communication. Understanding the abilities and inabilities of AI technologies is critical to using these technologies ethically. The authors offer a proposed research agenda for researchers in business communication concerning topics of implementation, lexicography and grammar, collaboration, design, trust, bias, managerial concerns, tool assessment, and demographics. The authors conclude with some ideas regarding how to teach about AI in the business communication classroom.
AbbassH. A.(2019).Social integration of artificial intelligence: Functions, automation allocation logic and human-autonomy trust.Cognitive Computation,11(2),159-171.https://doi.org/10.1007/s12559-018-9619-0
2.
AgrawalA.GansJ. S.GoldfarbA.(2017,February7).What to expect from artificial intelligence: To understand how advances in artificial intelligence are likely to change the workplace—and the work of managers—you need to know where AI delivers the most value.MIT Sloan Management Review.https://sloanreview.mit.edu/article/what-to-expect-from-artificial-intelligence/
AndolinaS.OrsoV.SchneiderH.KloucheK.RuotsaloT.GamberiniL.JacucciG.(2018).Investigating proactive search support in conversations. InDIS ‘18: Proceedings of the 2018 Designing Interactive Systems Conference(pp.1295-1307).Association for Computing Machinery.https://doi.org/10.1145/3196709.3196734
5.
BabicD.ChenD.EvgeniouT.FayardA.(2020,July-August).A better way to onboard AI: Use it as a tool to assist rather than replace people.Harvard Business Review.https://hbr.org/2020/07/a-better-way-to-onboard-ai
6.
BaldeggerR.CaonM.SadikuK.(2020).Correlation between entrepreneurship orientation and implementation of AI in human resources management (HRM).Technology Innovation Management Review,10(4),72-79.https://doi.org/10.22215/timreview/1348
7.
BawackR. E.Fosso WambaS.CarilloK. D. A.(2021).A framework for understanding artificial intelligence research: Insights from practice.Journal of Enterprise Information Management,34(2),645-678.https://doi.org/10.1108/jeim-07-2020-0284
8.
BrewerR. N.MorrisM. R.LindleyS. E.(2017).How to remember what to remember: Exploring possibilities for digital reminder systems. InProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies(pp.1-20).Association for Computing Machinery.https://doi.org/10.1145/3130903
CaliskanA.BrysonJ. J.NarayananA.(2017).Semantics derived automatically from language corpora contain human-like biases.Science,356(6334),183-186.https://doi.org/10.1126/science.aal4230
11.
CambreJ.LiuY.TaylorR. E.KulkarniC.(2019).Vitro: Designing a voice assistant for the scientific lab workplace. InDIS ‘19: Proceedings of the 2019 on Designing Interactive Systems Conference(pp.1531-1542).Association for Computing Machinery.https://doi.org/10.1145/3322276.3322298
CardonP.MaH.FleischmannA. C.AritzJ.(2021).Recorded work meetings and algorithmic tools: Anticipated boundary turbulence. InProceedings of the 54th Hawaii International Conference on System Sciences(pp.196-205). ScholarSpace at University of Hawai’i at Manoa.http://hdl.handle.net/10125/70633
CrewsT. B.Stitt-GohdesW. L.(2012).Incorporating Facebook and Twitter in a service-learning project in a business communication course.Business Communication Quarterly,75(1),76-79.https://doi.org/10.1177/1080569911431881
EcheverriaV.Martinez-MaldonadoR.Buckingham ShumS.(2019).Towards collaboration translucence (Paper 39). InCHI ‘19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems(pp.1-16).Association for Computing Machinery.https://doi.org/10.1145/3290605.3300269
FastN. J.SchroederJ.(2020).Power and decision making: New directions for research in the age of artificial intelligence.Current Opinion in Psychology,33(June),172-176.https://doi.org/10.1016/j.copsyc.2019.07.039
23.
FleischmannC.CardonP.AritzJ.(2020).Smart collaboration in global virtual teams: The influence of culture on technology acceptance and communication effectiveness. InProceedings of the 53rd Hawaii International Conference on System Sciences(pp.363-373).ScholarSpace at University of Hawai’i at Manoa.http://hdl.handle.net/10125/63784
24.
FleischmannC.CardonP.AritzJ.(2021).Acceptance of speech-to-text technology: Exploring language proficiency and psychological safety in global virtual teams. InProceedings of the 54th Hawaii International Conference on System Sciences(pp.411-420).ScholarSpace at University of Hawai’i at Manoa.http://hdl.handle.net/10125/70660
HancockJ. T.NaamanM.LevyK.(2020).AI-mediated communication: Definition, research agenda, and ethical considerations.Journal of Computer-Mediated Communication,25(1),89-100.https://doi.org/10.1093/jcmc/zmz022
HoustonA. L.WalshK. R.(1996,January3-6).Using an AI-based tool to categorize digitized textual forms of organizational memory. InProceedings of HICSS-29: 29th Hawaii International Conference on System Sciences.IEEE Xplore.https://doi.org/10.1109/hicss.1996.493171
30.
HuangM.-H.RustR. T.(2021).A strategic framework for artificial intelligence in marketing.Journal of the Academy of Marketing Science,49(1),30-50.https://doi.org/10.1007/s11747-020-00749-9
KocielnikR.AvrahamiD.MarlowJ.LuD.HsiehG.(2018).Designing for workplace reflection: A chat and voice-based conversational agent. InDIS ‘18: Proceedings of the 2018 Designing Interactive Systems Conference(pp.881-894).https://doi.org/10.1145/3196709.3196784
KumarV.RajanB.VenkatesanR.LecinskiJ.(2019).Understanding the role of artificial intelligence in personalized engagement marketing.California Management Review,61(4),135-155.https://doi.org/10.1177/0008125619859317
LeQ. V.(2013).Building high-level features using large scale unsupervised learning. In2013 IEEE International Conference on Acoustics, Speech and Signal Processing(pp.8595-8598).IEEE Xplore.https://doi.org/10.1109/icassp.2013.6639343
40.
LeeY. S.(2020).Instructional innovations with business communication in classrooms: Practice-based presentation topics and online communication tools.Business Communication Research and Practice,3(1),53-59.https://doi.org/10.22682/bcrp.2020.3.1.53
41.
MaL.SunB.(2020).Machine learning and AI in marketing: Connecting computing power to human insights.International Journal of Research in Marketing,37(3),481-504.https://doi.org/10.1016/j.ijresmar.2020.04.005
MarksR.(2021,July8).Jay Richards: Creative freedom, not robots, is the future of work (No. 142) [Audio podcast episode].Mind Matters News.https://mindmatters.ai/podcast/ep142/
McGregorM.TangJ. C.(2017).More to meetings: Challenges in using speech-based technology to support meetings. InCSCW ‘17: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing(pp.2208-2220).Association for Computing Machinery.https://doi.org/10.1145/2998181.2998335
48.
MerriamG.(2021).If A.I. only had a heart: Why artificial intelligence research needs to take emotions more seriously.Journal of Artificial Intelligence and Consciousness,9(1),73-91.https://doi.org/10.1142/s2705078521500120
49.
NaidooJ.DulekR. E.(2022).Artificial intelligence in business communication: A snapshot.International Journal of Business Communication,59(1),126-147.https://doi.org/10.1177/2329488418819139
50.
NematzadehA.BangG.MaZ.LiuS.(2019,August).“Alexa, open analyst assistant”: Evaluating a voice user interface for financial analysis[Conference session].Proceedings of the 5th World Congress on Electrical Engineering and Computer Systems and Science,Lisbon, Portugal.https://doi.org/10.11159/mhci19.101
51.
NiemantsverdrietK.EricksonT.(2017).Recurring meetings: An experiential account of repeating meetings in a large organization. InProceedings of the ACM on Human-Computer Interaction(pp.1-17).Association for Computing Machinery.https://doi.org/10.1145/3134719
52.
O’NeilC.(2016).Weapons of math destruction: How big data increases inequality and threatens democracy.Crown.
53.
OvergoorG.ChicaM.RandW.WeishampelA.(2019).Letting the computers take over: Using AI to solve marketing problems.California Management Review,61(4),156-185.https://doi.org/10.1177/0008125619859318
PorcheronM.FischerJ. E.McGregorM.BrownB.LugerE.CandelloH.O’HaraK.(2017).Talking with conversational agents in collaborative action. InCSCW ‘17 Companion: Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing(pp.431-436).Association for Computing Machinery.https://doi.org/10.1145/3022198.3022666
56.
QiuX.SunT.XuY.ShaoY.DaiN.HuangX.(2020).Pre-trained models for natural language processing: A survey.Science China Technological Sciences,63(10),1872-1897.https://doi.org/10.1007/s11431-020-1647-3
SeeberI.BittnerE.BriggsR. O.de VreedeT.de VreedeG.-J.ElkinsA.MaierR.MerzA. B.Oeste-ReißS.RandrupN.SchwabeG.SöllnerM.(2020).Machines as teammates: A research agenda on AI in team collaboration.Information & Management,57(2),103174.https://doi.org/10.1016/j.im.2019.103174
61.
ShamekhiA.LiaoQ. V.WangD.BellamyR. K. E.EricksonT.(2018).Face value? Exploring the effects of embodiment for a group facilitation agent. InCHI ‘18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems(pp.1-13).Association for Computing Machinery.https://doi.org/10.1145/3173574.3173965
62.
ShaneJ.(2019).You look like a thing and I love you: How artificial intelligence works and why it’s making the world a weirder place.Little, Brown.
63.
ShresthaY. R.KrishnaV.von KroghG.(2021).Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges.Journal of Business Research,123(February),588-603.https://doi.org/10.1016/j.jbusres.2020.09.068
64.
SiddikeM. A. K.SpohrerJ.DemirkanH.KohdaY.(2018).People’s interactions with cognitive assistants for enhanced performances. InProceedings of the 51st Hawaii International Conference on System Sciences(pp.1640-1648).ScholarSpace at University of Hawaii at Manoa.http://hdl.handle.net/10125/50092
StewartA. E. B.VrzakovaH.SunC.YonehiroJ.StoneC. A.DuranN. D.ShuteV.D’MelloS. K.(2019).I say, you say, we say: Using spoken language to model socio-cognitive processes during computer-supported collaborative problem solving. InProceedings of the ACM on Human-Computer Interaction(pp.1-19).Association for Computing Machinery.https://doi.org/10.1145/3359296
69.
TambeP.CappelliP.YakubovichV.(2019).Artificial intelligence in human resources management: Challenges and a path forward.California Management Review,61(4),15-42.https://doi.org/10.1177/0008125619867910
Toledo-RonenO.Bar-HaimR.HalfonA.JochimC.MenczelA.AharonovR.SlonimN.(2018).Learning sentiment composition from sentiment lexicons. InProceedings of the 27th International Conference on Computational Linguistics(pp.2230-2241).Association for Computational Linguistics.https://aclanthology.org/C18-1189/
72.
Toledo-RonenO.OrbachM.BiluY.SpectorA.SlonimN.(2020,October13).Multilingual argument mining: Datasets and analysis(Version 1). ArXiv.Org.https://arxiv.org/abs/2010.06432
73.
van EschP.BlackJ. S.FerolieJ. (2019).Marketing AI recruitment: The next phase in job application and selection.Computers in Human Behavior,90(January),215-222.https://doi.org/10.1016/j.chb.2018.09.009
74.
VealeM.BinnsR.(2017).Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data.Big Data & Society,4(2).https://doi.org/10.1177/2053951717743530
WebberS. S.DetjenJ.MacLeanT. L.ThomasD.(2019).Team challenges: Is artificial intelligence the solution?Business Horizons,62(6),741-750.https://doi.org/10.1016/j.bushor.2019.07.007
ZhangR.McNeeseN. J.FreemanG.MusickG.(2020).“An ideal human”: Expectations of AI teammates in human-AI teaming. InProceedings of the ACM on Human-Computer Interaction(pp.1-25).Association for Computing Machinery.https://doi.org/10.1145/3432945
