Emotions with a product or service strongly influence consumer behaviour. Conventional marketing relied on user-centred designs to achieve loyalty. In the past few decades, firms have deployed AI-enabled technologies to create, communicate and deliver value. Algorithms could initially perform mechanical and thinking-oriented tasks only. However, recent developments have empowered machines with feeling intelligence to understand user emotions. Thus, the current article examines the literature on the emerging scope for feeling AI in marketing. Additionally, this study introduces the ‘Five Wheels of Feeling Marketing’, a conceptual model and a strategic ‘FEELING’ framework, designed to transition traditional businesses into enterprises driven by feeling AI.
AltmanI., & TaylorD. A. (1973). Social penetration: The development of interpersonal relationships. Holt, Rinehart & Winston.
2.
ArnoldM. B. (1950). An excitatory theory of emotion. In ReymertM. L. (Ed.), Feelings and emotions. The mooseheart symposium (pp. 11–33). McGraw-Hill.
3.
BagozziR. P., BradyM. K., & HuangM.-H. (2022). AI service and emotion. Journal of Service Research, 25(4), 499–504.
4.
BelkR. (2022). Artificial emotions and love and sex doll service workers. Journal of Service Research, 25(4), 521–536.
5.
BlakeV. K. (2019). Regulating care robots. Temple Law Review, 92, 551.
6.
BrandtzaegP. B., SkjuveM., & FølstadA. (2022). My AI friend: How users of a social chatbot understand their human–AI friendship. Human Communication Research, 48(3), 404–429.
CaruelleD., ShamsP., GustafssonA., & Lervik-OlsenL. (2022). Affective computing in marketing: Practical implications and research opportunities afforded by emotionally intelligent machines. Marketing Letters, 33(1), 163–169.
9.
ChaturvediR., & VermaS. (2023). Opportunities and challenges of AI-driven customer service. In ShethJ. N., JainV., MogajiE. & AmbikaA. (Eds.), Artificial intelligence in customer service: The next frontier for personalized engagement (pp. 33–71). Palgrave Macmillan.
10.
ChaturvediR., VermaS., AliF., & KumarS. (2023). Reshaping tourist experience with AI-enabled technologies: A comprehensive review and future research agenda. International Journal of Human–Computer Interaction, 40(18), 5517–5533.
11.
ChaturvediR., VermaS., DasR., & DwivediY. K. (2023). Social companionship with artificial intelligence: Recent trends and future avenues. Technological Forecasting and Social Change, 193, 122634.
12.
ChaturvediR., VermaS., & SrivastavaV. (2024). Empowering AI companions for enhanced relationship marketing. California Management Review, 66(2), 65–90.
13.
ChenJ. J., & LinJ. C. (2024). Artificial intelligence as a double-edged sword: Wielding the power principles to maximize its positive effects and minimize its negative effects. Contemporary Issues in Early Childhood, 25(1), 146–153.
14.
ContiM., GathaniJ., & TricomiP. P. (2022). Virtual influencers in online social media. IEEE Communications Magazine, 60(8), 86–91.
15.
DanaherJ. (2019). The philosophical case for robot friendship. Journal of Posthuman Studies, 3(1), 5–24.
16.
DeLalloD., & DialM. (2020). Geeting the feels: Should AI have empathy?McKinsey and Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/getting-the-feels-should-ai-have-empathy#
17.
DepountiI., SaukkoP., & NataleS. (2023). Ideal technologies, ideal women: AI and gender imaginaries in Redditors’ discussions on the Replika bot girlfriend. Media, Culture & Society, 45(4) 720–736.
18.
DickinsonS., & DrinevskayaA. (2023, July17). How the fashion industry propels virtual influencers. Seamm Newsletter. https://www.seamm.io/old-articles/ai-fashion-models-how-the-fashion-industry-propels-virtual-influencers-oldblog#:~:text=For%20example%2C%20Nars%2C%20Prada%2C,the%20South%20East%20Asia%20region
19.
FloridiL., CowlsJ., BeltramettiM., ChatilaR., ChazerandP., DignumV., LuetgeC., MadelinR., PagalloU., RossiF., SchaferB., ValckeP., & VayenaE. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28, 689–707.
20.
FreitasJ. D., UğuralpA. K., & UğuralpZ. (2022). Ethical risks of autonomous products: The case of mental health crises on AI companion applications. (Working Paper No. 23-011), Harvard Business School Marketing Unit.
GahlautD. (2023). Top emotion AI companies to watch out for in 2023. Medium. https://deepanshugahlaut.medium.com/top-emotion-ai-companies-to-watch-out-for-in-2023-db925868fd9f
23.
GoldenbergA., & GrossJ. J. (2020). Digital emotion contagion. Trends in Cognitive Sciences, 24(4), 316–328.
24.
GossettS. (2023). Emotion AI: 3 Experts on the possibilities and risks affective computing knows how you feel. BuiltIn. https://builtin.com/artificial-intelligence/emotion-ai
25.
GremslT., & HödlE. (2022). Emotional AI: Legal and ethical challenges 1. Information Polity, 27(2), 163–174.
26.
HanE., YinD., & ZhangH. (2023). Bots with feelings: Should AI agents express positive emotion in customer service?Information Systems Research, 34(3), 1296–1311.
27.
HenkelA. P., ČaićM., BlaurockM., & OkanM. (2020). Robotic transformative service research: Deploying social robots for consumer well-being during COVID-19 and beyond. Journal of Service Management, 31(6), 1131–1148.
28.
HermannE. (2022). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics, 179(1), 43–61.
29.
HuangM.-H., & RustR. T. (2021a). Engaged to a robot? The role of AI in service. Journal of Service Research, 24(1) 30–41.
30.
HuangM.-H., & RustR. T. (2021b). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30–50.
31.
HuangM-H., & RustR. T.2022, AI as customer. Journal of Service Management, 33(2), 210–220.
32.
HuangM-H., & RustR. T. (2024). The caring machine: Feeling AI for customer care. Journal of Marketing, 88(5), 1–23. https://doi.org/10.1177/00222429231224748
33.
JamesJ., BalamuraliB. T., WatsonC. I., & MacDonaldB. (2021). Empathetic speech synthesis and testing for healthcare robots. International Journal of Social Robotics, 13(8), 2119–2137.
34.
KiC.-W. C., CuevasL. M., ChongS. M., & LimH (2020). Influencer marketing: Social media influencers as human brands attaching to followers and yielding positive marketing results by fulfilling needs. Journal of Retailing and Consumer Services, 55, 102133.
KshetriN., DwivediY. K., DavenportT. H., & PanteliN. (2023). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75. https://doi.org/10.1016/j.ijinfomgt.2023.102716
37.
LarueO., PoirierP., & NkambouR. (2013). The emergence of (artificial) emotions from cognitive and neurological processes. Biologically Inspired Cognitive Architectures, 4, 54–68.
38.
LauY., CheeD. G. H., ChowX. P., WongS. H., ChengL. J., & LauS. T. (2020). Humanoid robot-assisted interventions among children with diabetes: A systematic scoping review. International Journal of Nursing Studies, 111, 103749–103749.
39.
LemonK. N., & VerhoefP. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96.
40.
Leo-LiuJ. (2023). Loving a ‘defiant’ AI companion? The gender performance and ethics of social exchange robots in simulated intimate interactions. Computers in Human Behavior, 141. https://doi.org/10.1016/j.chb.2022.107620
41.
LewisM., & CanameroL. (2016). Hedonic quality or reward? A study of basic pleasure in homeostasis and decision making of a motivated autonomous robot. Adaptive Behavior, 24(5), 267–291.
42.
LimW. M., KumarS., VermaS., & ChaturvediR. (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review. Psychology & Marketing, 39(6) 1129–1155.
43.
Liu-ThompkinsY., OkazakiS., & LiH. (2022). Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience. Journal of the Academy of Marketing Science, 50(6), 1198–1218.
44.
LuS., KimH.-J., ZhouY., XiaoL., & DingM. (2022). Audio and visual analytics in marketing and artificial empathy. Foundations and Trends in Marketing, 16(4), 422–493.
45.
MalerbaD., AppiceA., BuonoP., CastellanoG., CarolisB. D., GemmisM. D., PolignanoM., RossanoV., & RuddL. M. (2019). Advanced programming of intelligent social robots. Journal of e-Learning and Knowledge Society, 15(2), 13–26.
46.
Maroto-GómezM., Alonso-MartínF., MalfazM., Castro-GonzálezA., CastilloJ. C., & SalichsM. Á. (2023). A systematic literature review of decision-making and control systems for autonomous and social robots. International Journal of Social Robotics, 15(5), 745–789.
47.
McStayA. (2020a). Emotional AI, soft biometrics and the surveillance of emotional life: An unusual consensus on privacy. Big Data & Society, 7(1). https://doi.org/10.1177/2053951720904386
48.
McStayA. (2020b). Emotional AI and EdTech: Serving the public good?Learning, Media and Technology, 45(3), 270–283.
49.
MeleC., Russo-SpenaT., TreguaM., & AmitranoC. C. (2021). The millennial customer journey: A phygital mapping of emotional, behavioural, and social experiences. Journal of Consumer Marketing, 38(4), 420–433.
50.
Merrill JrK., KimJ., & CollinsC. (2022). AI companions for lonely individuals and the role of social presence. Communication Research Reports, 39(2), 93–103.
51.
MillsA. J., & JohnJ. (2020). Brand stories: Bringing narrative theory to brand management. Journal of Strategic Marketing, 33(1), 35–53. https://doi.org/10.1080/0965254X.2020.1853201
52.
MoermanC. J., HeideL. V. D., & HeerinkM. (2019). Social robots to support children’s well-being under medical treatment: A systematic state-of-the-art review. Journal of Child Health Care, 23(4), 596–612.
53.
MogajiE., OlaleyeS., & UkpabiD. (2020). Using AI to personalise emotionally appealing advertisement. In RanaN. P., SladeE. L., SahuG. P., KizginH., SinghN., DeyB., GutierrezA., & DwivediY. K. (Eds.), Digital and social media marketing: Emerging applications and theoretical development (pp. 137–150). Springer.
54.
MoriM. (1970). The uncanny valley. Energy, 7(4), 33–35.
55.
MradM., RamadanZ., & NasrL. I. (2022). Computer-generated influencers: The rise of digital personalities. Marketing Intelligence & Planning, 40(5), 589–603.
56.
NassC., & MoonY. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103.
57.
ParkG., ChungJ., & LeeS. (2023). Effect of AI chatbot emotional disclosure on user satisfaction and reuse intention for mental health counseling: A serial mediation model. Current Psychology, 42(32), 28663–28673.
58.
PaulJ., LimW. M., O’CassA., HaoA. W., & BrescianiS. (2021). Scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR). International Journal of Consumer Studies, 45(4), O1–O16.
59.
PaulettoS., BalentineB., PidcockC., JonesK., BottaciL., AretoulakiM., WellsJ., MundyD. P., & BalentineJ. (2013). Exploring expressivity and emotion with artificial voice and speech technologies. Logopedics Phoniatrics Vocology, 38(3), 115–125.
60.
PepitoJ. A., ItoH., BetrianaF., TaniokaT., & LocsinR. C. (2020). Intelligent humanoid robots expressing artificial human-like empathy in nursing situations. Nursing Philosophy, 21(4), e12318.
61.
PicardR. W. (2000). Affective computing. MIT Press.
62.
RocksC., JenkinsS., StudleyM., & McGoranD. (2009). ‘Heart Robot’, a public engagement project. Interaction Studies, 10(3), 427–452.
63.
RosalesJ.-H., RodríguezL.-F., & RamosF. (2019). A general theoretical framework for the design of artificial emotion systems in autonomous agents. Cognitive Systems Research, 58, 324–341.
64.
RossiS., & RuoccoM. (2019). Better alone than in bad company: Effects of incoherent non-verbal emotional cues for a humanoid robot. Interaction Studies, 20(3), 487–508.
65.
RyanR. M., & DeciE. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68.
66.
SandsS., FerraroC., DemsarV., & ChandlerG. (2022). False idols: Unpacking the opportunities and challenges of falsity in the context of virtual influencers. Business Horizons, 65(6), 777–788.
67.
SantoraJ. (2023, July17). Key influencer marketing statistics to drive your strategy in 2023. Influencer Marketing Hub. https://influencermarketinghub.com/influencer-marketing-statistics/
68.
SchepersJ., BelancheD., CasalóL. V., & FlaviánC. (2022). How smart should a service robot be?Journal of Service Research, 25(4), 565–582.
69.
SchererK. R. (1995). Expression of emotion in voice and music. Journal of Voice, 9(3), 235–48.
70.
SchererK. R. (2001). Emotional experience is subject to social and technological change: Extrapolating to the future. Social Science Information, 40(1), 125–151.
71.
SchneiderM. (2018). A cybernetical perspective on emotion-cognition interactions as self-directed adaptation in situated decision-makers. Cognitive Systems Research, 52, 400–428.
72.
SchollB. J., & LeslieA. M. (2001). Minds, modules, and meta-analysis. Child Development, 72(3), 696–701.
73.
ShahD., & MurthiB. P. S. (2021). Marketing in a data-driven digital world: Implications for the role and scope of marketing. Journal of Business Research, 125, 772–779.
74.
ShahD., & ShayE. (2019). How and why artificial intelligence, mixed reality and blockchain technologies will change marketing we know today. In ParvatiyarA., & SisodiaR. (Eds.), Handbook of advances in marketing in an era of disruptions: Essays in honour of Jagdish N. Sheth (pp. 377–390). Sage Publications Pvt Ltd.
75.
Stock-HomburgR. (2022). Survey of emotions in human–robot interactions: Perspectives from robotic psychology on 20 years of research. International Journal of Social Robotics, 14(2), 389–411.
76.
SuJ., & YangW. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100049
77.
SundarS. S., & LeeE.-J. (2022). Rethinking communication in the era of artificial intelligence. Human Communication Research, 48(3), 379–385.
78.
TagB., SarsenbayevaZ., CoxA. L., WadleyG., GoncalvesJ., & KostakosV. (2022a). Emotion trajectories in smartphone use: Towards recognizing emotion regulation in-the-wild. International Journal of Human-Computer Studies, 166. https://doi.org/10.1016/j.ijhcs.2022.102872
79.
TagB., van BerkelN., VargoA. W., SarsenbayevaZ., ColasanteT., WadleyG., WebberS., SmithW., KovalP., HollensteinT., GoncalvesJ., & KostakosV. (2022). Impact of the global pandemic upon young people's use of technology for emotion regulation. Computers in Human Behavior Reports, 6, 100192.
80.
TajfelH., & TurnerJ. C. (1986). The social identity theory of inter group behavior. In WorchelS. & AustinW. G. (Eds.), Psychology of intergroup relations. Nelson.
81.
TamirM., OliverJ. P., SrivastavaS., & GrossJ. J. (2007). Implicit theories of emotion: Affective and social outcomes across a major life transition. Journal of Personality and Social Psychology, 92(4), 731.
82.
TsankovaD. D. (2009). Emotional intervention on an action selection mechanism based on artificial immune networks for navigation of autonomous agents. Adaptive Behavior, 17(2), 135–152.
83.
WadleyG., SmithW., KovalP., & GrossJ. J. (2020). Digital emotion regulation. Current Directions in Psychological Science, 29(4), 412–418.
84.
YangF., & ZhenX. (2014). Research on the agent’s behavior decision-making based on artificial emotion. Journal of Information & Computational Science, 11(8), 2723–2733.
85.
ZakiM., McColl-KennedyR., & NeelyA. (2021). Using AI to track how customers feel—In real time. Harvard Business Review. https://doi.org/10.17863/CAM.70387
