Journal of Intelligent Marketing Management

Journal of Intelligent Marketing Management

Artificial Intelligence and Chatbot in Marketing: review of applications and risks

Document Type : The scientific research paper

Authors
1 Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran
2 Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran.
Abstract
Marketing is undergoing an unprecedented transformation driven by artificial intelligence (AI). Artificial intelligence is becoming increasingly essential for marketers due to its ability to automate tasks, analyze data more effectively, and create personalized experiences for customers. This leads to benefits such as increased efficiency, creativity, customer loyalty and competitive advantage. Businesses that adopt AI tools will be at the forefront of today's ever-changing world. Artificial intelligence tools, including chatbots, have become a powerful tool in marketing and help businesses in various fields. However, using chatbots in marketing without considering ethical considerations and potential risks is irresponsible. The main purpose of this research is to choose the best chatbot in marketing and to examine the uses, risks and ethical use of the chosen chatbot in marketing.

The current research is applied in terms of purpose and in the category of descriptive-analytical research. The stages of conducting this research include 3 main phases, in the first phase, using library methods, the background of the research was investigated and the indicators of choosing the best chatbot in marketing were extracted, and the hierarchical model of the research was obtained. In the second phase, based on the hierarchical model of the research, a table of paired comparisons was created and provided to the experts in the form of a questionnaire of paired comparisons. Then, to choose the best chatbot in marketing, the hierarchical analysis process method was used. In the third phase, applications, uses and risks of using selected chatbots in marketing were examined.

The findings of the research showed that ChatGPT was selected as the best chatbot in marketing. The risks associated with this chatbot and the challenges of using it in marketing for marketers, consumers and other stakeholders include privacy violations, loss of some jobs, inaccuracy of data and production of incorrect items. is If used responsibly, ChatGPT can have a variety of uses, such as transforming customer service, personalized conversations, collecting leads, and supporting content creation in marketing.
Keywords

Subjects


ترابی، محمدامین و عباسیان، عزت اله و میلانی، سید محمدصادق. (۱۴۰۳). بازاریابی هوشمند با استفاده از چت جی­پی­تی. مدیریت بازاریابی هوشمند، ۵(۱)، ۱-۹.
محمد­شفیعی، مجید و آرمان، عارف. (۱۴۰۲). تعیین عوامل بازاریابی نوآورانه در چارچوب ابعاد مزیت رقابتی با استفاده از فرایند تحلیل شبکه­ای (مطالعه موردی: گروه صنعتی انتخاب)، بیستمین کنفرانس بین­المللی مدیریت، تهران، دانشگاه تهران.
Abdullah, Y. I., Schuman, J. S., Shabsigh, R., Caplan, A., & Al-Aswad, L. A. (2021). Ethics of artificial intelligence in medicine and ophthalmology. The Asia-Pacific Journal of Ophthalmology10(3), 289-298.
Adewumi, T., Liwicki, F., & Liwicki, M. (2022). State-of-the-art in Open-domain Conversational AI: A Survey. Information, 13(6), 298.‏
Agarwal, N. (2022). Artificial Intelligence and Marketing. Int. J. Soc. Sci. Econ. Res7.
Ahmad, S. F., Han, H., Alam, M. M., Rehmat, M., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness and safety in education. Humanities and Social Sciences Communications10(1), 1-14.
Ahn, J., & Oh, A. (2021). Mitigating language-dependent ethnic bias in BERT. arXiv preprint arXiv:2109.05704.
Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y. K., D’Ambra, J., & Shen, K. N. (2021). Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management60, 102387.
Association, A.M. Definition of Marketing. Available online: https://www.ama.org/the-definition-of-marketing-what-ismarketing/ (accessed on 20 February 2023).
Bansal, G., Chamola, V., Hussain, A., Guizani, M., & Niyato, D. (2024). Transforming Conversations with AI—A Comprehensive Study of ChatGPT. Cognitive Computation, 1-24.
Bender EM, Gebru T. (2021). The dangers of stylized language: Emergent biases and sociotechnical remedies. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. ACM, 610–623.
 BHUVANESWARI, L., SUBADRA, S., & SALMA SHAJAHAN, D. C. (2024). The Impact Of Artificial Intelligence (AI) On Digital Marketing. Migration Letters, 21(S6), 1132-1142.‏
Bogina, V., Hartman, A., Kuflik, T., & Shulner-Tal, A. (2021). Educating software and AI stakeholders about algorithmic fairness, accountability, transparency and ethics. International Journal of Artificial Intelligence in Education, 1-26.
Borji, A. (2023). A categorical archive of chatgpt failures. arXiv preprint arXiv:2302.03494.
Bornstein, M.; Stahl, S. ChatGPT vs. Content Marketing, A Free Webinar Brought to You by ON24. Available online: https://contentmarketinginstitute.com/ (accessed on 2 February 2023).
Bowman, E. (2022). A new AI chatbot might do your homework for you. But it's still not an A+ student. NPR.
Brand, J., Israeli, A., & Ngwe, D. (2023). Using gpt for market research. Available at SSRN 4395751.
Brooks, R. A. (2018). Intelligence without reason. In The artificial life route to artificial intelligence (pp. 25-81). Routledge.‏
Butler, T. L. (1981). Can a computer be an author-copyright aspects of artificial intelligence. Comm/Ent LS4, 707.‏
Cao Y, Lin Z, Xu X, Tang Y, Zhang Z, Zhang Y. (2020). Clinic: A secure peer-to-peer healthcare blockchain framework with privacy preservation. IEEE Trans Ind Inf, 16(6):4384–95.
Chakrabortty, R. K., Abdel-Basset, M., & Ali, A. M. (2023). A multi-criteria decision analysis model for selecting an optimum customer service chatbot under uncertainty. Decision Analytics Journal6, 100168.‏
Chowdhury, R. M., & Fernando, M. (2014). The relationships of empathy, moral identity and cynicism with consumers’ ethical beliefs: The mediating role of moral disengagement. Journal of Business Ethics124, 677-694.
Cui, J. (2022). Copyright and AI: Are Extant Laws Adequate?. In International Conference on Big Data, 80-87. Cham: Springer International Publishing.‏
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science48, 24-42.
De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U., & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing51(1), 91-105.
Dignum, V. (2018). Ethics in artificial intelligence: introduction to the special issue. Ethics and Information Technology, 20(1), 1-3.‏
Dziri, N., Milton, S., Yu, M., Zaiane, O., & Reddy, S. (2022). On the origin of hallucinations in conversational models: Is it the datasets or the models?. arXiv preprint arXiv:2204.07931.
Etzioni, A., & Etzioni, O. (2017). Incorporating ethics into artificial intelligence. The Journal of Ethics21, 403-418.
Ferrell, O. C., Hartline, M., & Hochstein, B. W. (2021). Marketing strategy. Cengage Learning.
Firat M. How chat GPT can transform autodidactic experiences and open education. Department of Distance Education: Open Education Faculty, Anadolu Unive; 2023.
Fu, T., Gao, S., Zhao, X., Wen, J. R., & Yan, R. (2022). Learning towards conversational AI: A survey. AI Open, 3, 14-28.‏
Gao, J., Galley, M., & Li, L. (2018, June). Neural approaches to conversational AI. In The 41st international ACM SIGIR conference on research & development in information retrieval (pp. 1371-1374).‏
Gao, L., Zhan, H., & Sheng, V. S. (2023). Mitigate gender bias using negative multi-task learning. Neural Processing Letters55(8), 11131-11146.
Garon, J. M. (2023). The Revolution Will Be Digitized: General AI, Synthetic Media, and the Medium of Disruption. Ohio St. Tech. LJ20, 139.‏
George, A. S., & George, A. H. (2023). A review of ChatGPT AI's impact on several business sectors. Partners Universal International Innovation Journal1(1), 9-23.
Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing: A multidisciplinary perspective. Journal of the Academy of Marketing Science, 48, 1-8.
Hacker, P., Engel, A., & Mauer, M. (2023). Regulating ChatGPT and other large generative AI models. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 1112-1123.
Hermann, E. (2022). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics179(1), 43-61.
Jadeja, M., & Varia, N. (2017). Perspectives for evaluating conversational AI. arXiv preprint arXiv:1709.04734.‏
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business horizons62(1), 15-25.
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences103, 102274.
Kibbey, T. (2019). Transcriptivism: An ethical framework for modern linguistics. Proceedings of the Linguistic Society of America4, 45-1.
Kirov, V., & Malamin, B. (2022). Are translators afraid of artificial intelligence?. Societies12(2), 70.
Krafft, M., Sajtos, L., & Haenlein, M. (2020). Challenges and opportunities for marketing scholars in times of the fourth industrial revolution. Journal of Interactive Marketing51(1), 1-8.
Kulkarni, P., Mahabaleshwarkar, A., Kulkarni, M., Sirsikar, N., & Gadgil, K. (2019, September). Conversational AI: An overview of methodologies, applications & future scope. In 2019 5th International conference on computing, communication, control and automation (ICCUBEA) (pp. 1-7). IEEE.‏
Lee, J. Y. (2023). Can an artificial intelligence chatbot be the author of a scholarly article? J Educ Eval Health Prof 20: 6.‏
Legg, S., & Hutter, M. (2007). A collection of definitions of intelligence. Frontiers in Artificial Intelligence and applications157, 17.
Ma, L., & Sun, B. (2020). Machine learning and AI in marketing–Connecting computing power to human insights. International Journal of Research in Marketing37(3), 481-504.
McCarthy, J. (2007). What is artificial intelligence.‏
Mijwil, M., Aljanabi, M., & Ali, A. H. (2023). Chatgpt: Exploring the role of cybersecurity in the protection of medical information. Mesopotamian journal of cybersecurity2023, 18-21.
Mogaji, E., Soetan, T. O., & Kieu, T. A. (2020). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, j-ausmj, 29, 235–242.
Mohammad Shafiee, M. (2022). Competitive advantage via intellectual capital: a moderated mediation analysis. Journal of Intellectual Capital, 23(5), 957-997.
Mohammad Shafiee, M., & Arman, A. (2024). Determining the factors of innovative marketing within the framework of competitive advantage dimensions using the network analysis process (Case study: Entekhaab Industrial Group). The 20th International Conference on Management. (in Persian)
Mojadeddi, Z. M., & Rosenberg, J. (2023). The impact of AI and ChatGPT on research reporting. The New Zealand Medical Journal (Online)136(1575), 60-64.‏
Moon, J. K., Yoo, S. B., Sohn, H. G., & Cho, Y. S. (2021). Conflicting maps: How legal perspectives could minimize zoning cancellation in Republic of Korea. Land10(3), 256.‏
Muhammad, A. F., Susanto, D., Alimudin, A., Adila, F., Assidiqi, M. H., & Nabhan, S. (2020, September). Developing English conversation chatbot using dialogflow. In 2020 International Electronics Symposium (IES) (pp. 468-475). IEEE.‏
Oberoi, P. (2023). How Artificial Intelligence Is Impacting Marketing?. In Encyclopedia of Data Science and Machine Learning (pp. 606-618). IGI Global.
Oda, B. (2023). No Ghost in the Machine: On Human Creativity and Why AI-Generated Images from Text Prompts Are Not Protected by Copyright. The SciTech Lawyer20(1), 20-28.‏
Paliwal, S., Bharti, V., & Mishra, A. K. (2020). Ai chatbots: Transforming the digital world. Recent trends and advances in artificial intelligence and internet of things, 455-482.‏
Paluch, S., & Wirtz, J. (2020). Artificial intelligence and robots in the service encounter. Journal of service management research, 4, 3–8.
Park, D. M., Jeong, S. S., & Seo, Y. S. (2022). Systematic review on chatbot techniques and applications. Journal of Information Processing Systems, 18(1), 26-47.‏
Pitt, C., Paschen, J., Kietzmann, J., Pitt, L. F., & Pala, E. (2023). Artificial intelligence, marketing, and the history of technology: Kranzberg’s laws as a conceptual lens. Australasian Marketing Journal31(1), 81-89.
Plant, R., Giuffrida, V., & Gkatzia, D. (2022). You Are What You Write: Preserving Privacy in the Era of Large Language Models. arXiv preprint arXiv:2204.09391.
Pulizzi, J. (2021). Content Inc.: Start a Content-First Business, Build a Massive Audience and Become Radically Successful (With Little to No Money). McGraw Hill Professional.‏
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI blog1(8), 9.
Rapp, A., Curti, L., & Boldi, A. (2021). The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human-Computer Studies, 151, 102630.‏
Richardson, C., & Heck, L. (2023). Commonsense reasoning for conversational ai: A survey of the state of the art. arXiv preprint arXiv:2302.07926.‏
Rivas, P., & Zhao, L. (2023). Marketing with chatgpt: Navigating the ethical terrain of gpt-based chatbot technology. AI4(2), 375-384.
Rivas, P., Chelsi, C., Nishit, N., & Ravula, L. (2019). Application-agnostic chatbot deployment considerations: a case study. International Conference on Computational Science and Computational Intelligence (CSCI), 361-365. IEEE.
Rivas, P., Holzmayer, K., Hernandez, C., & Grippaldi, C. (2018). Excitement and concerns about machine learning-based chatbots and talkbots: A survey. IEEE International Symposium on Technology and Society, 156-162. IEEE.
Ruane, E., Birhane, A., & Ventresque, A. (2019). Conversational AI: Social and Ethical Considerations. AICS, 2563, 104-115.‏
Sakirin, T., & Said, R. B. (2023). User preferences for ChatGPT-powered conversational interfaces versus traditional methods. Mesopotamian Journal of Computer Science2023, 24-31.
Sathe, T. S., Sorrentino, T. A., & Lee, H. (2023). GPT-4: A Creative Copilot for Navigating Academic Surgery. Surgical Innovation30(5), 555-556.
Selvaraju, R. R., Lee, S., Shen, Y., Jin, H., Ghosh, S., Heck, L., & Parikh, D. (2019). Taking a hint: Leveraging explanations to make vision and language models more grounded. In Proceedings of the IEEE/CVF international conference on computer vision, 2591-2600.
Shafiee, M. M., & Arman, A. (2024). Identifying and Prioritizing Open Innovation Factors in Gaining a Competitive Advantage in the Home Appliance Industry. Journal of Business Management. 10.22059/JIBM.2024.371228.4741
Shieber, S. M. (Ed.). (2004). The Turing test: verbal behavior as the hallmark of intelligence. Mit Press.‏
Shin, D., Kim, H., Lee, J. H., & Yang, H. (2021). Exploring the use of an artificial intelligence chatbot as second language conversation partners. Korean journal of English language and linguistics, 21, 375-391.‏
Shrivastava, R. (2022). Teachers fear ChatGPT will make cheating even easier than ever. Forbes.‏
Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT–Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700.‏
Stokel-Walker, C. (2023). ChatGPT listed as author on research papers: many scientists disapprove. Nature613(7945), 620-621.‏
Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., & Machtynger, L. (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line33(2), 183-200.
Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. arXiv preprint arXiv:1906.02243.
Sun, G. H., & Hoelscher, S. H. (2023). The ChatGPT storm and what faculty can do. Nurse Educator48(3), 119-124.
Team, O. (2022). ChatGPT: Optimizing language models for dialogue. )2022-09-20)[2023-09-27]. https://openai. com/blog/chatgpt.‏
Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science379(6630), 313-313.
Torabi, M. A., Abbasian, E., & Milani, S. M. S. (2024). Smart marketing using Chat-GPT. Journal of Intelligent Marketing Management, 5(1), 1-9. (in Persian)
Venema, L., Jerde, T., Huth, J., Pieropan, M., & Matusevych, Y. (2023). The AI Writing on the Wall. Nat. Mach. Intell5(1).‏
Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights1(1), 100002.
Vlačić, B., Corbo, L., e Silva, S. C., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research128, 187-203.
Wang X, Gao Y, Xie J, Chen H, Deng L. (2020). Turing natural language generation: A scalable pretrained Chinese text-to-text generation model, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2651–61.
Wilson, C., & Van Der Velden, M. (2022). Sustainable AI: An integrated model to guide public sector decision-making. Technology in Society, 68, 101926.‏
Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration43(9), 818-829.
Yara, O., Brazheyev, A., Golovko, L., & Bashkatova, V. (2021). Legal regulation of the use of artificial intelligence: Problems and development prospects. European Journal of Sustainable Development10(1), 281-281.
Yigitcanlar, T. (2021). Greening the artificial intelligence for a sustainable planet: An editorial commentary. Sustainability, 13(24), 13508.‏
Yuan, S., Zhao, H., Zhao, S., Leng, J., Liang, Y., Wang, X., ... & Tang, J. (2022). A roadmap for big model. arXiv preprint arXiv:2203.14101.
Zaman, K. (2022). Transformation of marketing decisions through artificial intelligence and digital marketing. Journal of Marketing Strategies4(2), 353-364.
Zielinski, C., Winker, M., Aggarwal, R., Ferris, L., Heinemann, M., Lapeña, J. F., & Citrome, L. (2023). Chatbots, ChatGPT, and Scholarly Manuscripts-WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications. Afro-Egyptian Journal of Infectious and Endemic Diseases13(1), 75-79.

  • Receive Date 17 June 2024
  • Revise Date 01 July 2024
  • Accept Date 11 July 2024