Harnessing the Power of Artificial Intelligence in Entrepreneurship: Augmentation, Innovation, and Ethical Considerations

Musyokha Sheriefah; Silfa Sain Steva

doi:10.69725/raida.v1i2.167

Authors

Musyokha S a. Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates
Silfa S b. Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates

DOI:

https://doi.org/10.69725/raida.v1i2.167

Keywords:

Artificial Intelligence, Entrepreneurial Innovation, Operational Efficiency, AI Ethics

Abstract

Objective: This research examines the transformative potential of AI in fostering entrepreneurial innovation, highlighting its augmentation capabilities, integration strategies, and the ethical concerns that are essential for sustainable development. This study is contextualized against the backdrop of the fast-changing entrepreneurial ecosystems in the United Arab Emirates (UAE), with AI applications redefining the business landscape.
Methods: Quantitative metrics related to AI adoption were analyzed alongside qualitative insights from entrepreneurs and business owners. Using a sound theoretical base of innovation and technology adoption frameworks, they applied structural equation modeling to delineate the direct, indirect, and mediated relationships of AI use and entrepreneurial innovation
Results: AI's influence on entrepreneurship is complex, shaped through various mediators, including operational efficiency, ethics, and innovative integration strategies. By building businesses around these dimensions, companies are able to both innovate and sustain competitive advantages in an increasingly digital world.
Novelty: This research helps in filling the gap between theoretical understanding and the practical applications of AI in entrepreneurship. As the study focuses on the UAE, a territory which prides itself on being a global leader in AI-driven innovation, insights will be unique on leveraging emerging technologies ethically to drive entrepreneurial growth.
Research Implications: The research highlights the critical role of intentional AI integration within academic settings and the necessity for ethical standards. It is an important reference for policymakers, entrepreneurs, and academics working to maximize the potential of AI for innovation and sustainable business practices

Downloads

Download data is not yet available.

Author Biographies

Musyokha S, a. Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates

Musyokha S

Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates
Silfa S, b. Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates

Silfa Sain T

Faculty of Business, Higher Colleges of Technology, Zayed University, United Arab Emirates

References

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/https://doi.org/10.1002/hbe2.195 DOI: https://doi.org/10.1002/hbe2.195

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 Innovation: Technology, Market, and Complexity, 10(3), 100352. https://doi.org/https://doi.org/10.1016/j.joitmc.2024.100352 DOI: https://doi.org/10.1016/j.joitmc.2024.100352

Alshahrani, A., Dennehy, D., & Mäntymäki, M. (2022). An attention-based view of AI assimilation in public sector organizations: The case of Saudi Arabia. Government Information Quarterly, 39(4), 101617. https://doi.org/https://doi.org/10.1016/j.giq.2021.101617 DOI: https://doi.org/10.1016/j.giq.2021.101617

Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/https://doi.org/10.1016/j.techfore.2020.120420 DOI: https://doi.org/10.1016/j.techfore.2020.120420

Bahoo, S., Cucculelli, M., & Qamar, D. (2023). Artificial intelligence and corporate innovation: A review and research agenda. Technological Forecasting and Social Change, 188, 122264. https://doi.org/https://doi.org/10.1016/j.techfore.2022.122264 DOI: https://doi.org/10.1016/j.techfore.2022.122264

Bessen, J., Impink, S. M., Reichensperger, L., & Seamans, R. (2022). The role of data for AI startup growth. Research Policy, 51(5), 104513. https://doi.org/https://doi.org/10.1016/j.respol.2022.104513 DOI: https://doi.org/10.1016/j.respol.2022.104513

Burström, T., Parida, V., Lahti, T., & Wincent, J. (2021). AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research. Journal of Business Research, 127, 85–95. https://doi.org/https://doi.org/10.1016/j.jbusres.2021.01.016 DOI: https://doi.org/10.1016/j.jbusres.2021.01.016

Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283–314. https://doi.org/https://doi.org/10.1016/j.jbusres.2020.08.019 DOI: https://doi.org/10.1016/j.jbusres.2020.08.019

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2019.08.002 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Kumar, S., Verma, A. K., & Mirza, A. (2024). Digital Revolution, Artificial Intelligence, and Ethical Challenges BT - Digital Transformation, Artificial Intelligence and Society: Opportunities and Challenges (S. Kumar, A. K. Verma, & A. Mirza (eds.); pp. 161–177). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-5656-8_11 DOI: https://doi.org/10.1007/978-981-97-5656-8_11

Kumar, V., Ashraf, A. R., & Nadeem, W. (2024). AI-powered marketing: What, where, and how? International Journal of Information Management, 77, 102783. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2024.102783 DOI: https://doi.org/10.1016/j.ijinfomgt.2024.102783

La Rocca, A., & Snehota, I. (2021). Mobilizing suppliers when starting up a new business venture. Industrial Marketing Management, 93, 401–412. https://doi.org/https://doi.org/10.1016/j.indmarman.2020.08.002 DOI: https://doi.org/10.1016/j.indmarman.2020.08.002

Madanaguli, A., Sjödin, D., Parida, V., & Mikalef, P. (2024). Artificial intelligence capabilities for circular business models: Research synthesis and future agenda. Technological Forecasting and Social Change, 200, 123189. https://doi.org/https://doi.org/10.1016/j.techfore.2023.123189 DOI: https://doi.org/10.1016/j.techfore.2023.123189

Mariani, M. M., Machado, I., Magrelli, V., & Dwivedi, Y. K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122, 102623. https://doi.org/https://doi.org/10.1016/j.technovation.2022.102623 DOI: https://doi.org/10.1016/j.technovation.2022.102623

Mariani, M. M., Machado, I., & Nambisan, S. (2023). Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda. Journal of Business Research, 155, 113364. https://doi.org/https://doi.org/10.1016/j.jbusres.2022.113364 DOI: https://doi.org/10.1016/j.jbusres.2022.113364

Robins, J., & Wiersema, M. F. (1995). A resource-based approach to the multibusiness firm: Empirical analysis of portfolio interrelationships and corporate financial performance. Strategic Management Journal, 16(4), 277–299. https://doi.org/https://doi.org/10.1002/smj.4250160403 DOI: https://doi.org/10.1002/smj.4250160403

Shepherd, D. A., & Majchrzak, A. (2022). Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship. Journal of Business Venturing, 37(4), 106227. https://doi.org/https://doi.org/10.1016/j.jbusvent.2022.106227 DOI: https://doi.org/10.1016/j.jbusvent.2022.106227

Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574–587. https://doi.org/https://doi.org/10.1016/j.jbusres.2021.05.009 DOI: https://doi.org/10.1016/j.jbusres.2021.05.009

Toufaily, E., Zalan, T., & Dhaou, S. Ben. (2021). A framework of blockchain technology adoption: An investigation of challenges and expected value. Information & Management, 58(3), 103444. https://doi.org/https://doi.org/10.1016/j.im.2021.103444 DOI: https://doi.org/10.1016/j.im.2021.103444

Townsend, D. M., & Hunt, R. A. (2019). Entrepreneurial action, creativity, & judgment in the age of artificial intelligence. Journal of Business Venturing Insights, 11, e00126. https://doi.org/https://doi.org/10.1016/j.jbvi.2019.e00126 DOI: https://doi.org/10.1016/j.jbvi.2019.e00126

Uren, V., & Edwards, J. S. (2023). Technology readiness and the organizational journey towards AI adoption: An empirical study. International Journal of Information Management, 68, 102588. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2022.102588 DOI: https://doi.org/10.1016/j.ijinfomgt.2022.102588

Vesnic-Alujevic, L., Nascimento, S., & Pólvora, A. (2020). Societal and ethical impacts of artificial intelligence: Critical notes on European policy frameworks. Telecommunications Policy, 44(6), 101961. https://doi.org/https://doi.org/10.1016/j.telpol.2020.101961 DOI: https://doi.org/10.1016/j.telpol.2020.101961

Vlačić, B., Corbo, L., Costa e Silva, S., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187–203. https://doi.org/https://doi.org/10.1016/j.jbusres.2021.01.055 DOI: https://doi.org/10.1016/j.jbusres.2021.01.055

Yaiprasert, C., & Hidayanto, A. N. (2024). AI-powered ensemble machine learning to optimize cost strategies in logistics business. International Journal of Information Management Data Insights, 4(1), 100209. https://doi.org/https://doi.org/10.1016/j.jjimei.2023.100209 DOI: https://doi.org/10.1016/j.jjimei.2023.100209