Disrupting the Communicator Paradigm: Systematic Mapping of Artificial Intelligence in Contemporary Communication Theory

Authors

  • Vinda Maya Setianingrum

    Communication Department, Universitas Negeri Surabaya, Surabaya 60231, Indonesia

  • Pramana

    Communication Department, Universitas Sebelas Maret, Surakarta 57126, Indonesia

  • Prahastiwi Utari

    Communication Department, Universitas Sebelas Maret, Surakarta 57126, Indonesia

  • Rifqi Abdul Aziz

    Digital Public Relations, Telkom University, Bandung 40257, Indonesia

DOI:

https://doi.org/10.30564/fls.v7i11.11618
Received: 13 August 2025 | Revised: 2 September 2025 | Accepted: 22 September 2025 | Published Online: 27 October 2025

Abstract

This study presents a systematic literature review (SLR) of 132 peer-reviewed articles to examine how artificial intelligence (AI) is reconceptualized as a communicator within contemporary communication theory. Drawing on Robert T.Craig’s (1999) seven communication traditions, the review maps how AI disrupts established models by acting not only as a medium but also as an active participant in meaning-making, emotional simulation, and symbolic interaction. Thematic synthesis reveals five dominant conceptual shifts: from human-centered agency to hybrid systems, from linear transmission models to algorithmic mediation, and from sender–receiver logic to co-constructed symbolic exchanges involving non-human actors. The analysis further identifies tensions across traditions concerning intentionality, empathy, authorship, and communicative ethics, underscoring the uneven uptake of AI across theoretical perspectives. Critical insights emerge regarding the ideological and infrastructural power of AI in shaping discourse, trust, and relational dynamics. In response, the study proposes an operational framework conceptualizing AI as a synthetic communicator encompassing dimensions of agentic presence, symbolic interlocution, affective simulation, and algorithmic mediation. This framework generates testable propositions for future empirical inquiry and bridges the synthesis with language-focused approaches such as pragmatics and discourse analysis. Ultimately, the review contributes a foundational synthesis and a roadmap for advancing communication scholarship in the era of intelligent systems, highlighting both opportunities for theoretical integration and challenges of ethical accountability.

Keywords:

Artificial Intelligence; Communication Theory; Communicator Paradigm; Systematic Literature Review; Craig's Traditions; Human–Machine Interaction

References

[1] Barnlund, D.C., 2008. A transactional model of communication. In: Mortensen, D.C. (ed.). Communication Theory, 2nd ed. Routledge: New York, NY, USA.

[2] Schramm, W., 1954. How communication works. In: Schramm, W. (ed.). The Process and Effects of Mass Communication. University of Illinois Press: Champaign, IL, USA.

[3] Afroogh, S., Akbari, A., Malone, E., et al., 2024. Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications. 11, 1568. DOI: https://doi.org/10.1057/s41599-024-04044-8

[4] Algouzi, S., Alzubi, A.A.F., 2023. The Study of AI-Mediated Communication and Socio-Cultural Language-Related Variables: Gmail Reply Suggestions. Applied Artificial Intelligence, 37(1). DOI: https://doi.org/10.1080/08839514.2023.2175114

[5] Picard, R.W., 2000. Affective computing. MIT Press: Cambridge, MA, USA.

[6] Abed, S.S., Farrokhi, F., 2025. The Role of Artificial intelligence and media communication: A systematic literature review. AI & Technology in Social Science. 12(1), 45–47. DOI: https://doi.org/10.61838/kman.aitech.3.3.3

[7] Bach, T.A., Khan, A., Hallock, H., et al., 2022. A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective. International Journal of Human–Computer Interaction, 40(5), 1251–1266. DOI: https://doi.org/10.1080/10447318.2022.2138826

[8] Daft, R.L., Lengel, R.H., 1984. Information richness: A new approach to managerial behavior and organizational design. Research in Organizational Behavior. 6, 191–233.

[9] Short, J., Williams, E., Christie, B., 1976. The social psychology of telecommunications. John Wiley & Sons: Hoboken, NJ, USA.

[10] Kosela, P.M., 2025. Emergent Communication in Merging Artificial Agent Populations. In: Paszynski, M., Barnard, A.S., Zhang, Y.J. (eds.). Computational Science — ICCS 2025 Workshops. ICCS 2025. Springer: Cham, Switzerland. DOI: https://doi.org/10.1007/978-3-031-97557-8_19

[11] Wu, H., Wang, Y., Chen, Z., Huang, Y., et al., 2024. Research on the uncanny valley effect in artificial intelligence news anchors. Multimedia Tools and Applications. 83, 62581–62606. DOI: https://doi.org/10.1007/s11042-023-18073-z

[12] Lovari, A., De Rosa, F., 2025. Exploring the challenges of generative AI on public sector communication in Europe. Media and Communication. 13, 1–24. DOI: https://doi.org/10.17645/mac.9644

[13] Craig, R.T., 1999. Communication theory as a field. Communication Theory. 9(2), 119–161. DOI: https://doi.org/10.1111/j.1468-2885.1999.tb00355.x

[14] Gong, L., Nass, C., 2007. When a talking-face computer agent is half-human and half-humanoid: Human identity and consistency preference. Human Communication Research. 33(2), 163–193. DOI: https://doi.org/10.1111/j.1468-2958.2007.00295.x

[15] Krämer, N.C., Rosenthal-Von Der Pütten, A.M., Hoffmann, L., 2015. Social effects of virtual and robot companions. In: Sundar, S.S. (ed.). Handbook of Psychology of Communication Technology. pp. 137–159. DOI: https://doi.org/10.1002/9781118426456.ch6

[16] Fitzpatrick, K.K., Darcy, A., Vierhile, M., 2017. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial. JMIR Mental Health. 4(2), 1–11. DOI: https://doi.org/10.2196/mental.7785

[17] Nass, C., Moon, Y., 2000. Machines and mindlessness: Social responses to computers. Journal of Social Issues. 56(1), 81–103. DOI: https://doi.org/10.1111/0022-4537.00153

[18] De Graaf, M.M.A., Ben Allouch, S., 2013. Exploring influencing variables for the acceptance of social robots. Robotics and Autonomous Systems. 61(12), 1476–1486. DOI: https://doi.org/10.1016/j.robot.2013.07.007

[19] Luger, E., Sellen, A., 2016. “Like having a really bad pa”: The gulf between user expectation and experience of conversational agents. Proceedings of the Conference on Human Factors in Computing Systems, 5286–5297. DOI: https://doi.org/10.1145/2858036.2858288

[20] Le Dinh, T., Vu, M.-C., Tran, G.T.C., 2025. Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications. Information, 16(5), 415. DOI: https://doi.org/10.3390/info16050415

[21] Mikalef, P., Krogstie, J., Pappas, I.O., 2020. Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management. 57(2), 103169. DOI: https://doi.org/10.1016/j.im.2019.05.004

[22] Graefe, A., 2016. Guide to Automated Journalism. Tow Center for Digital Journalism: A Tow/Knight Guide: New York , NY, USA. pp. 1–48.

[23] Guzman, A.L., Lewis, S.C., 2020. Artificial intelligence and communication: A Human–Machine Communication research agenda. New Media & Society. 22(1), 70–86. DOI: https://doi.org/10.1177/1461444819858691

[24] Blumer, H., 2023. Symbolic interactionism: Perspective and method. University of California Press: California, CA, USA.

[25] Floridi, L., Sanders, J.W., 2004. On the morality of artificial agents. Minds and Machines. 14(3), 349–379. DOI: https://doi.org/10.1023/B:MIND.0000035461.63578.9d

[26] Gillespie, T., 2014. The relevance of algorithms. In: Gillespie, T., Boczkowski, P.J., Foot, K.A. (eds.). Media Technologies: Essays on Communication, Materiality, and Society. MIT Press: Cambridge, MA, USA. DOI: https://doi.org/10.7551/mitpress/9780262525374.003.0009

[27] Noble, S.U., 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press: New York, NY, USA.

[28] Couldry, N., Mejias, U.A., 2019. Data colonialism: Rethinking big data's relation to the contemporary subject. Television & New Media. 20(4), 336–349. DOI: https://doi.org/10.1177/1527476418796632

[29] Page, M.J., McKenzie, J.E., Bossuyt, P.M., et al., 2021. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 372, n71. DOI: https://doi.org/10.1136/bmj.n71

[30] Moher, D., Liberati, A., Tetzlaff, J., et al., 2009. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine. 6(7), e1000097. DOI: https://doi.org/10.1371/journal.pmed.1000097

[31] Petticrew, M., Roberts, H., 2006. Systematic Reviews in the Social Sciences: A Practical Guide. Blackwell Publishing: Oxford, UK.

[32] Tranfield, D., Denyer, D., Smart, P., 2003. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management. 14(3), 207–222. DOI: https://doi.org/10.1016/j.intman.2013.03.011

[33] Snyder, H., 2019. Literature review as a research methodology: An overview and guidelines. Journal of Business Research. 104, 333–339. DOI: https://doi.org/10.1016/j.jbusres.2019.07.039

[34] Okoli, C., Schabram, K., 2012. A guide to conducting a systematic literature review of information systems research. SSRN Electronic Journal. DOI: https://doi.org/10.2139/ssrn.1954824

[35] Braun, V., Clarke, V., 2006. Using thematic analysis in psychology. Qualitative Research in Psychology. 3(2), 77–101. DOI: https://doi.org/10.1191/1478088706qp063oa

[36] Hannes, K., 2011. Chapter 4: Critical appraisal of qualitative research. In: Noyes, J., Booth, A., Hannes, K. (eds.). Supplementary Guidance for Inclusion of Qualitative Research in Cochrane Systematic Reviews of Interventions, Version 1. Available from: http://cqrmg.cochrane.org/supplemental-handbook-guidance (cited 2 August 2025)

[37] Mays, N., Pope, C., 2000. Qualitative research in health care: Assessing quality in qualitative research. BMJ. 320(7226), 50–52. DOI: https://doi.org/10.1136/bmj.320.7226.50

[38] Holley, R.P., 2008. Applications of social research methods to questions in information and library science (book review). Portal: Libraries and the Academy9(4), 517–518. DOI: http://dx.doi.org/10.1353/pla.0.0081

[39] Di Virgilio, F., Jacobson, K.A., Williams, M., 2021. Geoffrey Burnstock — An accidental pharmacologist. Biochemical Pharmacology. 187, 114300. DOI: https://doi.org/10.1016/j.bcp.2020.114300

[40] Fairclough, N., 2003. Analysing Discourse: Textual Analysis for Social Research. Routledge: London, UK.

[41] Shannon, C.E., 1948. A mathematical theory of communication. Bell System Technical Journal. 27(4), 623–656. DOI: https://doi.org/10.1002/j.1538-7305.1948.tb00917.x

[42] Bickmore, T.W., 2005. Establishing and maintaining long-term human-computer relationships. 12(2), 293–327. DOI: https://psycnet.apa.org/doi/10.1145/1067860.1067867

[43] Edwards, A., 2005. Relational agency: Learning to be a resourceful practitioner. International Journal of Educational Research. 43(3), 168–182. DOI: https://doi.org/10.1016/j.ijer.2006.06.010

[44] Hollan, J., Hutchins, E., Kirsh, D., 2000. Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction. 7(2), 174–196. DOI: https://doi.org/10.1145/353485.353487

[45] Massumi, B., 2002. Parables for the Virtual: Movement, Affect, Sensation. Duke University Press: Durham, NC, USA.

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How to Cite

Setianingrum, V. M., Pramana, Utari, P., & Aziz, R. A. (2025). Disrupting the Communicator Paradigm: Systematic Mapping of Artificial Intelligence in Contemporary Communication Theory. Forum for Linguistic Studies, 7(11), 1225–1241. https://doi.org/10.30564/fls.v7i11.11618

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