AI Adoption in Product Innovation: How Artificial Intelligence Helps Create More Relevant Products?
DOI:
https://doi.org/10.61100/tacit.v3i1.255Keywords:
Artificial Intelligence, Product Innovation, Data Analysis, Personalization, Operational EfficiencyAbstract
The adoption of artificial intelligence (AI) in product innovation has become a key factor in creating products that are more relevant to customer needs. AI enables companies to analyze market trends, optimize product design, and personalize offerings based on consumer preferences. This study is a literature review employing a qualitative approach and descriptive analysis, utilizing data from Google Scholar and credible websites from 2018 to 2025. From an initial 30 articles, a rigorous selection process reduced the sample to 18 primary sources for this research. The findings indicate that AI has had a significant impact across various industries, such as automotive, healthcare, retail, and food, by enhancing innovation efficiency and aligning products more precisely with customer needs. However, AI adoption in product innovation also faces challenges, including data quality, algorithmic bias, and difficulties in integrating technology at the organizational level. The implications of this research highlight the importance of optimizing AI strategies in product development, improving human resource competencies, and establishing regulations that support ethical and sustainable AI implementation. Therefore, companies need to develop more adaptive strategies for integrating AI to create more competitive product innovations that align with market dynamics.
References
Aggarwal, M., & Madhukar, M. (2017). IBM’s Watson Analytics for Health Care. In Cloud Computing Systems and Applications in Healthcare (pp. 117–134). ResearchGate. https://doi.org/10.4018/978-1-5225-1002-4.ch007
Ali, M., Khan, T. I., Khattak, M. N., & Şener, İ. (2024). Synergizing AI and business: Maximizing innovation, creativity, decision precision, and operational efficiency in high-tech enterprises. Journal of Open Innova-tion: Technology, Market, and Complexity, 10(3), 100352. https://doi.org/10.1016/j.joitmc.2024.100352
Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, 103745. https://doi.org/10.1016/j.jfineco.2023.103745
Bilal, M., Zhang, Y., Cai, S., Akram, U., & Halibas, A. (2024). Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment. Journal of Retailing and Consumer Services, 77, 103674. https://doi.org/10.1016/j.jretconser.2023.103674
Climent, R. C., Haftor, D. M., & Staniewski, M. W. (2024). AI-enabled business models for competitive ad-vantage. Journal of Innovation & Knowledge, 9(3), 100532. https://doi.org/10.1016/j.jik.2024.100532
Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems re-search: A systematic literature review and research agenda. International Journal of Information Manage-ment, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383
Ferrara, E. (2023). Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitiga-tion Strategies. Sci, 6(1), 3. https://doi.org/10.3390/sci6010003
GhorbanTanhaei, H., Boozary, P., Sheykhan, S., Rabiee, M., Rahmani, F., & Hosseini, I. (2024). Predictive ana-lytics in customer behavior: Anticipating trends and preferences. Results in Control and Optimization, 17, 100462. https://doi.org/10.1016/j.rico.2024.100462
Haefner, N., Parida, V., Gassmann, O., & Wincent, J. (2023). Implementing and scaling artificial intelligence: A review, framework, and research agenda. Technological Forecasting and Social Change, 197, 122878. https://doi.org/10.1016/j.techfore.2023.122878
Handoyo, S., Suharman, H., Ghani, E. K., & Soedarsono, S. (2023). A business strategy, operational efficiency, ownership structure, and manufacturing performance: The moderating role of market uncertainty and competition intensity and its implication on open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100039. https://doi.org/10.1016/j.joitmc.2023.100039
Hariguna, T., & Ruangkanjanases, A. (2024). Assessing the impact of artificial intelligence on customer per-formance: a quantitative study using partial least squares methodology. Data Science and Management, 7(3), 155–163. https://doi.org/10.1016/j.dsm.2024.01.001
Kuncoro, W., & Suriani, W. O. (2018). Achieving sustainable competitive advantage through product innova-tion and market driving. Asia Pacific Management Review, 23(3), 186–192. https://doi.org/10.1016/j.apmrv.2017.07.006
London L. (2020). NotCo: Creating Plant-Based Food Alternatives with AI. D3.Harvard.Edu.
Mathews, A. (2024). How Nike is Using AI to Transform Product Design, Customer Experience, and Operational Effi-ciency. Aimresearch.Co.
Sharma, A., Virmani, T., Pathak, V., Sharma, A., Pathak, K., Kumar, G., & Pathak, D. (2022). Artificial Intelli-gence‐Based Data‐Driven Strategy to Accelerate Research, Development, and Clinical Trials of COVID Vaccine. BioMed Research International, 2022(1). https://doi.org/10.1155/2022/7205241
Tesla. (2025). Autopilot and Full Self-Driving (Supervised). Www.Tesla.Com.
Unilever. (2024). How AI-powered ultra-personalised experiences are boosting our beauty brands. Www.Unilever.Com.
Weidig, J., Weippert, M., & Kuehnl, C. (2024). Personalized touchpoints and customer experience: A concep-tual synthesis. Journal of Business Research, 177, 114641. https://doi.org/10.1016/j.jbusres.2024.114641
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Technology and Society Perspectives (TACIT)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
