Building Answer Engine Trust : A Perspective on Entrepreneurial Healthcare Marketing in the Generative AI Era
DOI:
https://doi.org/10.17010/amcije/2026/v9i1/176105Keywords:
answer engine trust capability; AI-mediated discovery; digital health; entrepreneurial legitimacy; generative artificial intelligence; patient trust; representation risk.JEL Classification Codes : I11, L26, M31, O33
Abstract
Purpose : Traditional search engine optimization was becoming less effective, as Generative Artificial Intelligence changed patient search behavior and the way information was discovered, thereby challenging conventional approaches to entrepreneurial visibility. This perspective paper examined the impact of AI-driven discovery on digital visibility, patient trust, and business legitimacy and highlighted the capabilities required to navigate emerging risks surrounding content and representation.
Design/Methodology/Approach : This perspective paper introduced answer engine trust capability, a venture-level capability that incorporated evidence and clinical validation, authority and attribution, contextual information structuring, responsible communication, and continuous monitoring and correction.
Findings : Healthcare ventures could not fully control what external answer engines retrieved or synthesized; therefore, increasing the credibility, provenance, and governance of the information released by ventures emerged as an important entrepreneurial requirement.
Practical Implications : Rather than focusing primarily on discoverability and conversion goals, AETC emphasized justified trust, accountable representation, and responsible patient acquisition, and provided an actionable framework for sustaining entrepreneurial growth in health-product markets where representational control had diminished.
Originality/Value : The paper's originality lay in moving the debate from SEO as a visibility tactic to AETC as an entrepreneurial capability.
Downloads
References
1) Banu, S. (2025). An analysis of perception of MSMEs toward adoption of digital practices with special reference to Karnataka. AMC Indian Journal of Entrepreneurship, 8(1), 44–55. https://indianjournalofcapitalmarkets.com/index.php/IJOE/article/view/175191
2) Bedi, S., Liu, Y., Orr-Ewing, L., Dash, D., Koyejo, S., Callahan, A., Fries, J. A., Wornow, M., Swaminathan, A., Soleymani Lehmann, L., Hong, H. J., Kashyap, M., Chaurasia, A. R., Shah, N. R., Singh, K., Tazbaz, T., Milstein, A., Pfeffer, M. A., & Shah, N. H. (2025). Testing and evaluation of health care applications of large language models: A systematic review. JAMA, 333(4), 319–328. https://doi.org/10.1001/jama.2024.21700
3) Chakraborty, D. (2024). Revolutionizing travel: The impact of generative AI on personalization and efficiency in the tourism industry. Indian Journal of Marketing, 54(9), 8–24. https://doi.org/10.17010/ijom/2024/v54/i9/174394
4) Dash, G., Akmal, S., & Chakraborty, D. (2022). A study on adoption of e-health services: Developing an integrated framework in a multinational context. Indian Journal of Marketing, 52(5), 25–40. https://doi.org/10.17010/ijom/2022/v52/i5/169415
5) Giri, A., & Biswas, W. (2025). Prompt-to-purchase: Leveraging generative AI to revolutionize e-tail (electronic–retail) customer engagement. Indian Journal of Marketing, 55(12), 59–70. https://doi.org/10.17010/ijom/2025/v55/i12/175246
6) Goktas, P., & Grzybowski, A. (2025). Shaping the future of healthcare: Ethical clinical challenges and pathways to trustworthy AI. Journal of Clinical Medicine, 14(5), 1605. https://doi.org/10.3390/jcm14051605
7) Gregory, A. (2026). Google AI overviews put people at risk of harm with misleading health advice. The Guardian. https://www.theguardian.com/technology/2026/jan/02/google-ai-overviews-risk-harm-misleading-health-information
8) Guo, S., Song, Y., Chen, G., Han, H., Wu, H., & Ma, J. (2025). Promoting trust and intention to adopt health information generated by ChatGPT among healthcare customers: An empirical study. Digital Health, 11. https://doi.org/10.1177/20552076251374121
9) Kim, J. Y., Hasan, A., Kueper, J., Tang, T., Hayes, C., Fine, B., Balu, S., & Sendak, M. (2025). Establishing organizational AI governance in healthcare: A case study in Canada. npj Digital Medicine, 8, Article no. 522. https://doi.org/10.1038/s41746-025-01909-3
10) Kumar, A., & Banerjee, P. (2025). Leading with intelligence: How AI is reshaping creative innovation in organizations. Prabandhan: Indian Journal of Management, 18(9), 54–62. https://doi.org/10.17010/pijom/2025/v18i9/174843
11) Kumari, A., & Laheri, V. K. (2025). Understanding consumer behavior through AI-powered recommender systems: A systematic review and bibliometric perspective. Indian Journal of Marketing, 55(8), 9–32. https://doi.org/10.17010/ijom/2025/v55/i8/175207
12) Mahajan, S., Gupta, M., & Chauhan, V. (2025). How may “AI” help you? Analyzing the role of AI-backed chatbot interactions in customer services. Indian Journal of Marketing, 55(4), 69–88. https://doi.org/10.17010/ijom/2025/v55/i4/174929
13) Mittal, R., & Saxena, K. (2025). Innovation management in the age of generative AI: Strategic challenges and opportunities for business leaders. Journal of Emerging Technologies and Innovation Management, 1(2), 50–56. https://doi.org/10.64006/jetim/1205
14) Neha, & Khurana, A. (2025). The impact of generative AI on academic performance and social sustainability: A PLS-SEM and fsQCA study. Journal of Emerging Technologies and Innovation Management, 1(2), 13–22. https://doi.org/10.64006/jetim/1202
15) OpenAI. (2026). Introducing ChatGPT Health. https://openai.com/index/introducing-chatgpt-health/
16) Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), Article ID 101885. https://doi.org/10.1016/j.jsis.2024.101885
17) Patel, M., & Imran, M. (2025). AI in the courtrooms: Global expert systems, ethical challenges, and policy implications for regulating the use of AI. Policy, Law, and Governance Insights, 1(2), 1–14. https://doi.org/10.64006/plgi/1201
18) Pichai, S. (2026). I/O 2026: Welcome to the agentic Gemini era. Google India Blog. https://blog.google/intl/en-in/company-news/technology/sundar-pichai-io-2026/
19) Practo. (2025). India's health concerns are shifting: Practo insights reveal 84% YoY growth in lifestyle disease awareness. Practo Insights. https://blog.practo.com/indias-health-concerns-are-shifting-practo-insights-reveal-84-yoy-growth-in-lifestyle-disease-awareness/
20) U.S. Food and Drug Administration. (2026). FDA warns 30 telehealth companies against illegal marketing of compounded GLP-1s. https://www.fda.gov/news-events/press-announcements/fda-warns-30-telehealth-companies-against-illegal-marketing-compounded-glp-1s
21) Wardle, C., Urbani, S., & Wang, E. (2025). Evolving health information–seeking behavior in the context of Google AI Overviews, ChatGPT, and Alexa: Interview study using the think-aloud protocol. Journal of Medical Internet Research, 27, Article ID e79961. https://doi.org/10.2196/79961
22) World Health Organization. (2024). Ethics and governance of artificial intelligence for health: Large multi-modal models. https://www.who.int/publications/b/70584
23) Yun, H. S., & Bickmore, T. (2025). Online health information–seeking in the era of large language models: Cross-sectional web-based survey study. Journal of Medical Internet Research, 27, Article ID e68560. https://doi.org/10.2196/68560