Authors

1. Meenakshi Yadav
2. Dr. Seema Malik

Affiliation

• Research Scholar, Department of Commerce, Bhagat Phool Singh Mahila Vishwavidyalaya Khanpur Kalan, Sonipat
• Associate Professor, Department of Commerce, Bhagat Phool Singh Mahila Vishwavidyalaya Khanpur Kalan, Sonipat

Abstract

AI is growing quickly, which is changing the way businesses work, speeding up new ideas, and opening up new opportunities in every area. This study examines the significant impact of AI on startups, emphasizing the opportunities it generates, the challenges it presents, and the complexities it introduces for both emerging and established enterprises. The study's findings show that AI's ability to analyse large datasets, automate difficult tasks, and come up with new ideas has led to the creation of new business models that have greatly improved operational efficiency and completely changed the way customers interact with businesses. Also, there are some challenges faced by enterprises while using AI, such as having trouble using AI because it costs more, retraining their workers, losing market share, having trouble integrating AI, and more. Artificial intelligence (AI) could help businesses grow, make better decisions, and compete better. However, it also raises concerns regarding its application, data privacy, and the potential displacement of traditional employment.

Keywords

Artificial Intelligence (AI), Startups, Industries, Disrupting

References

1. European Commission. (2021). Proposal for a Regulation of the European Parliament and of the Council laying down harmonized rules on artificial intelligence (Artificial Intelligence Act) and amending certain union legislative acts. European Commission.
2. Ehteshami Bejnordi, B., Veta, M., Johannes Van Diest, P., et al. (2017). Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. JAMA, 318(22), 2199-2210.
3. Doshi-Velez, F., & Kim, B. (2017). Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608.
4. Deloitte Insights. (2023). AI
5. De La Rosa, W., & Bechler, C. J. (2024). Unveiling the adverse effects of artificial intelligence on financial decisions via the AI-IMPACT model. Current Opinion in Psychology, 101843.
6. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
7. Christensen, C. M. (1997). The Innovator
8. Chalmers, D., MacKenzie, N. G., & Carter, S. (2021). Artificial intelligence and entrepreneurship: Implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5), 1028-1053.
9. Calderon-Monge, E., & Ribeiro-Soriano, D. (2024). The role of digitalization in business and management: a systematic literature review. Review of managerial science, 18(2), 449-491.
10. Cabañas, J. G., & Mochón, F. (2016). Operating an advertising programmatic buying platform: A case study. IJIMAI, 3(6), 6-15.
11. Bimbraw, K. (2015). Autonomous cars: Past, present and future: A review of the developments in the last century, the present scenario, and the expected future of autonomous vehicle technology. Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 1, 191-198.
12. Bessen, J. E., Impink, S. M., Reichensperger, L., & Seamans, R. (2023). The business of AI startups. Boston Univ. School of Law, Law and Economics Research Paper, (18-28).
13. Au, C. D., Klingenberger, L., Svoboda, M., & Frère, E. (2021). Business model of sustainable robo-advisors: Empirical insights for practical implementation. Sustainability, 13(23), 13009.
14. Ashta, A., & Herrmann, H. (2021). Artificial intelligence and fintech: An overview of opportunities and risks for banking, investments, and microfinance. Strategic Change, 30(3), 211-222.
15. Aboshosha, A., Haggag, A., George, N., & Hamad, H. A. (2023). IoT-based data-driven predictive maintenance relying on fuzzy system and artificial neural networks. Scientific Reports, 13(1), 12186.