Product Management Strategies For Ai Integration In American Higher Education
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AI in Higher Education, Product Management in AI, AI Integration StrategiesAbstract
The adoption of Artificial Intelligence (AI) in American Higher Education is becoming more and more viewed as a strategic direction to improving learning outcomes and endeavors of institutions. However, the actualisation of AI technologies call for proper management of products so as to avoid unsuccessful deployment. This article aims to examine the function of product management with reference to the implementation of AI in the context of higher education considering the main problem and specifics of working with it for the educational institution. The research focuses on the identification of the current global practices in the implementation of AI, practices of developing AI products, management of such solutions in higher education institutions and the identification of general practices and trends in the context of AI in general. Based on the examples of AI projects in education this article defines key lessons on how to approach AI projects: · Communication with the stakeholders · Systems’ development in accordance with the agile methodologies and iterative approach. The identified challenges point to the need to integrate AI products to the overall institutional objectives, create cross-sector ties between academic and administrative divisions and consider the issues of AI solutions’ scalability and future-proofing. By applying the strategy set by Icomp, the product managers and educational leaders of higher education institutions will find guidance in integrating AI into their institutions. Several of the approaches presented in this article are intended to help address main challenges, unlock AI’s potential, and foster innovation in learning environment.
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Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education Sciences, 13(9), 856.https://doi.org/10.3390/educsci13090856
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22.https://doi.org/10.1186/s41239-023-00392-8
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International Journal of Educational Technology in Higher Education, 16(1), 1-27.https://doi.org/10.1186/s41239-019-0171-0
Hannan, E., & Liu, S. (2023). AI: new source of competitiveness in higher education. Competitiveness Review: An International Business Journal, 33(2), 265-279.https://doi.org/10.1108/CR-03-2021-0045
Perera, P., & Lankathilake, M. (2023). AI in higher education: A literature review of chatgpt and guidelines for responsible implementation.https://dx.doi.org/10.47772/IJRISS.2023.7623
Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education?. International Journal of Educational Technology in Higher Education, 17, 1-12.https://doi.org/10.1186/s41239-020-00218-x
Jensen, L. X., Buhl, A., Sharma, A., & Bearman, M. (2024). Generative AI and higher education: a review of claims from the first months of ChatGPT. Higher Education, 1-17.https://doi.org/10.1007/s10734-024-01265-3
Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review. Higher Education, 86(2), 369-385.https://doi.org/10.1007/s10734-022-00937-2
Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities' policies, resources, and guidelines. Computers and Education: Artificial Intelligence, 7, 100326.https://doi.org/10.1016/j.caeai.2024.100326
Chatterjee, S., & Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modelling. Education and Information Technologies, 25, 3443-3463.https://doi.org/10.1007/s10639-020-10159-7
Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and practice in technology enhanced learning, 12(1), 22.https://doi.org/10.1186/s41039-017-0062-8
Ogundipe, D. O., Babatunde, S. O., & Abaku, E. A. (2024). AI and product management: A theoretical overview from idea to market. International Journal of Management & Entrepreneurship Research, 6(3), 950-969.https://doi.org/10.51594/ijmer.v6i3.965
Wang, L., Liu, Z., Liu, A., & Tao, F. (2021). Artificial intelligence in product lifecycle management. The International Journal of Advanced Manufacturing Technology, 114, 771-796.https://doi.org/10.1007/s00170-021-06882-1
Parikh, N. A. (2023). Empowering business transformation: The positive impact and ethical considerations of generative AI in software product management–a systematic literature review. Transformational Interventions for Business, Technology, and Healthcare, 269-293.https://doi.org/10.4018/979-8-3693-1634-4.ch016
Schulze, M., Nitsche-Melkus, E., Jakop, U., Jung, M., & Waberski, D. (2019). New trends in production management in European pig AI centers. Theriogenology, 137, 88-92.https://doi.org/10.1016/j.theriogenology.2019.05.042
Lei, Y., Vyas, S., Gupta, S., & Shabaz, M. (2022). AI based study on product development and process design. International Journal of System Assurance Engineering and Management, 1-7.https://doi.org/10.1007/s13198-021-01404-4
Petrik, D., Saltan, A., & Helferich, A. Digital Product Management in the Era of Data Economy, Artificial Intelligence, and Ecosystems.https://doi.org/10.1007/978-3-031-71515-0
Cooper, R. G., & Brem, A. M. (2024). Insights for Managers About AI Adoption in New Product Development. Research-Technology Management, 67(6), 39-46.https://doi.org/10.1080/08956308.2024.2418734
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2023). Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges. Applied Sciences, 13(12), 7082.https://doi.org/10.3390/app13127082
Elhajjar, S. (2024). Unveiling the marketer's lens: exploring experiences and perspectives on AI integration in marketing strategies. Asia Pacific Journal of Marketing and Logistics.https://doi.org/10.1108/APJML-04-2024-0485
Alet, J. (2024). Effective integration of artificial intelligence: key axes for business strategy. Journal of Business Strategy, 45(2), 107-114.https://doi.org/10.1108/JBS-01-2023-0005
Jankovic, S. D., & Curovic, D. M. (2023). Strategic integration of artificial intelligence for sustainable businesses: implications for data management and human user engagement in the digital era. Sustainability, 15(21), 15208.https://doi.org/10.3390/su152115208
Alqahtani, N., & Wafula, Z. (2024). Artificial Intelligence Integration: Pedagogical Strategies and Policies at Leading Universities. Innovative Higher Education, 1-20.https://doi.org/10.1007/s10755-024-09749-x
How, M. L., & Cheah, S. M. (2024). Forging the future: strategic approaches to quantum ai integration for industry transformation. AI, 5(1), 290-323.https://doi.org/10.3390/ai5010015
Falebita, O. S., & Kok, P. J. (2024). Strategic goals for artificial intelligence integration among STEM academics and undergraduates in African higher education: a systematic review. Discover Education, 3(1), 1-22
.https://doi.org/10.1007/s44217-024-00252-1
Ferrero-Ferrero, I., Fernández-Izquierdo, M. Á., Muñoz-Torres, M. J., & Bellés-Colomer, L. (2018). Stakeholder engagement in sustainability reporting in higher education: An analysis of key internal stakeholders’ expectations. International Journal of Sustainability in Higher Education, 19(2), 313-336.https://doi.org/10.1108/IJSHE-06-2016-0116
Hart, D., Diercks-O'Brien, G., & Powell, A. (2009). Exploring stakeholder engagement in impact evaluation planning in educational development work. Evaluation, 15(3), 285-306.https://doi.org/10.1177/1356389009105882
Grunwald, G., Kara, A., & Spillan, J. E. (2024). Sustainable innovations through project partnerships at higher education institutions: challenges and implications for stakeholder engagement. Management Decision.https://doi.org/10.1108/MD-05-2024-1060
Consortium conjoint pour les écoles en santé (CCES), & Avison, C. (2010). Stakeholder engagement for improved school policy: development and implementation. Canadian Journal of Public Health, 101(Suppl 2), S22-S25.https://doi.org/10.1007/BF03405621
Conner, T. W. (2017). Exploring the diverse effects of stakeholder engagement on organizational performance. The American Review of Public Administration, 47(6), 634-647.https://doi.org/10.1177/0275074015618785
Khilji, S. E. (2022). An approach for humanizing leadership education: Building learning community & stakeholder engagement. Journal of Management Education, 46(3), 439-471.https://doi.org/10.1177/10525629211041355
Hoang, A., Hepburn, S. J., Tomizawa, S., Carroll, A., Edwards, E., & Sanders, M. (2024). Using a stakeholder engagement approach to inform professional development programs to promote education for sustainability in schools. Environmental Education Research, 1-19.https://doi.org/10.1080/13504622.2024.2419903
Haidabrus, B. (2024). Generative AI in Agile, Project, and Delivery Management. In Design, Simulation, Manufacturing: The Innovation Exchange (pp. 100-110). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-61797-3_9
Radwan, A. M., Abdel-Fattah, M. A., & Mohamed, W. (2024). AI-Driven Prioritization Techniques of Requirements in Agile Methodologies: A Systematic Literature Review. International Journal of Advanced Computer Science & Applications, 15(9).https://doi.org/10.14569/ijacsa.2024.0150983
Lumbanraja, H. L., Raharjo, T., & Fitriani, A. N. (2024). Artificial intelligence implementation in agile project management addressing challenges and maximizing impact. The Indonesian Journal of Computer Science, 13(4).https://doi.org/10.33022/ijcs.v13i4.4155
Daraojimba, E. C., Nwasike, C. N., Adegbite, A. O., Ezeigweneme, C. A., & Gidiagba, J. O. (2024). Comprehensive review of agile methodologies in project management. Computer Science & IT Research Journal, 5(1), 190-218.https://doi.org/10.51594/csitrj.v5i1.717
Tominc, P., Oreški, D., & Rožman, M. (2023). Artificial intelligence and agility-based model for successful project implementation and company competitiveness. Information, 14(6), 337.https://doi.org/10.3390/info14060337
Lakshminarasimham, K. C. (2025). Technology Leadership for Program Success: Integrating AI and Agile Methods for Modern Enterprises. In Integrating Blue-Green Infrastructure Into Urban Development (pp. 489-506). IGI Global Scientific Publishing.https://doi.org/10.4018/979-8-3693-8069-7.ch022
Mahboob, M., Ahmed, M. R. U., Zia, Z., Ali, M. S., & Ahmed, A. K. (2024). Future of Artificial Intelligence in Agile Software Development. arXiv preprint arXiv:2408.00703.https://doi.org/10.48550/arXiv.2408.00703
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