A Study on Artificial Intelligence and Cloud Computing Assistance for Enhancement of Startup Businesses
DOI:
https://doi.org/10.71426/Keywords:
Artificial Intelligence, Cloud computing, Natural Language Processing, Cloud storage systems, Business Enhancement, ScalabilityAbstract
Startups are dynamic enterprises that often operate under high uncertainty and resource constraints while seeking rapid innovation and scalability. Technological advances, particularly in Artificial Intelligence (AI) and Cloud computing, have opened transformative opportunities to overcome these challenges. AI tools, such as machine learning algorithms, chatbots, recommendation engines, and predictive analytics, enable startups to optimize decision-making, automate workflows, and enhance customer engagement. Meanwhile, cloud storage systems and platforms offer cost-efficient, scalable infrastructure that mitigates the need for heavy upfront investments and allows businesses to adapt quickly to market demands. This paper explores how AI and cloud computing synergistically drive the growth of startup businesses by analyzing their applications, benefits, and challenges. A detailed literature survey elucidates existing research and practical implementations. Furthermore, this work proposes a methodology demonstrating the integration of AI tools with cloud storage systems to enhance key business processes. A case study is discussed to illustrate tangible outcomes, and a comparative analysis highlights the effectiveness of AI and cloud computing for the startup business. The findings underscore that startups leveraging these technologies achieve superior operational efficiency, market agility, and competitive advantage. Future research avenues include sector-specific strategies, ethical considerations, and long-term performance analysis.
References
[1]. Blank S, Eckhardt JT. The lean startup as an actionable theory of entrepreneurship. Journal of Management. 2024 Nov;50(8):3012-34. https://doi.org/10.1177/01492063231168095
[2]. Reis E. The lean startup. New York: Crown Business. 2011;27:2016-20.
[3]. Davenport TH, Ronanki R. Artificial intelligence for the real world. Harvard business review. 2018 Jan 1;96(1):108-16.
[4]. Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A. Cloud computing—The business perspective. Decision support systems. 2011 Apr 1;51(1):176-89. https://doi.org/10.1016/j.dss.2010.12.006[5]
[5]. Nambisan S. Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship theory and practice. 2017 Nov;41(6):1029-55. https://doi.org/10.1111/etap.12254
[6]. Vial G. Understanding digital transformation: A review and a research agenda. Managing digital transformation. 2021 May 26:13-66. https://doi.org/10.1016/j.jsis.2019.01.003
[7]. Chen S. How Does Digital Technology Drive Total Factor Productivity in Enterprises? Empirical Evidence from Text Analysis. Open Journal of Business and Management. 2023 Aug 11;11(5):2525-54. 10.4236/ojbm.2023.115140
[8]. Fitzgerald M, Kruschwitz N, Bonnet D, Welch M. Embracing digital technology: A new strategic imperative. MIT sloan management review. 2014;55(2):1.
[9]. Gnewuch U, Morana S, Maedche A. Towards Designing Cooperative and Social Conversational Agents for Customer Service. InI CIS 2017 Dec 10 (pp. 1-13).
[10]. Norvig P, Russell S. Artificial Intelligence: A Modern Approach, 4th US ed.
[11]. [Available]: Accenture digital: CHATBOTS ARE HERE TO STAY So what are you waiting for? Copyright © 2018 Accenture All rights reserved.
[12]. Necula SC, Păvăloaia VD. AI-driven recommendations: A systematic review of the state of the art in e-commerce. Applied Sciences. 2023 Apr 29;13(9):5531. https://doi.org/10.3390/app13095531
[13]. Waller MA, Fawcett SE. Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. Journal of Business logistics. 2013 Jun;34(2):77-84. https://doi.org/10.1111/jbl.12010
[14]. Cloud H. The NIST definition of cloud computing. National Institute of Science and Technology, special publication. 2011 Jan;800(2011):145.
[15]. Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I, Zaharia M. A view of cloud computing. Communications of the ACM. 2010 Apr 1;53(4):50-8. doi: 10.1145/1721654.1721672
[16]. Sean Marston ZL, Bandyopadhyay S, Zhang J, Ghalsasi A. Cloud computing—The business perspective. https://doi.org/10.1016/j.dss.2010.12.006
[17]. Hashem IA, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU. The rise of “big data” on cloud computing: Review and open research issues. Information systems. 2015 Jan 1;47:98-115. https://doi.org/10.1016/j.is.2014.07.006
[18]. Subashini S, Kavitha V. A survey on security issues in service delivery models of cloud computing. Journal of network and computer applications. 2011 Jan 1;34(1):1-1. https://doi.org/10.1016/j.jnca.2010.07.006
[19]. Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems. 2009 Jun 1;25(6):599-616. https://doi.org/10.1016/j.future.2008.12.001
[20]. Sandhu AK. Big data with cloud computing: Discussions and challenges. Big Data Mining and Analytics. 2021 Dec 27;5(1):32-40. 10.26599/BDMA.2021.9020016
[21]. Pearson S, Yee G. Privacy and Security for Cloud Computing: Computer Communications and Networks. Springer London, 2013. https://doi.org/10.1007/978-1-4471-4189-1
[22]. Khajeh-Hosseini A, Greenwood D, Smith JW, Sommerville I. The cloud adoption toolkit: Addressing the challenges of cloud adoption in enterprise. arXiv preprint arXiv:1003.3866. 2010 Mar 19. https://doi.org/10.48550/arXiv.1003.3866
[23]. [Online]: https://www.mckinsey.com/capabilities/quantumblack/our-insights/global-survey-the-state-of-ai-in-2020 (Accessed on May 15, 2025).
[24]. Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A. A survey on bias and fairness in machine learning. ACM computing surveys (CSUR). 2021 Jul 13;54(6):1-35. https://doi.org/10.1145/3457607
[25]. [Online]: Amazon Web Services. How Snoonu revolutionized its business using Amazon Bedrock and Amazon Personalize [Internet]. AWS Startup Case Study. 2024 [cited 2025 June]. Available from: https://aws.amazon.com/startups/learn/howsnoonu-revolutionized-its-business-using-amazon-bedrock-and-amazon-personalize
[26]. Reetha Vadakke Kara. SmartBio: An AI-Enabled Smart Medical Device for Early Cancer Detection using Variational Autoencoders and Multimodal Sensor Integration. Journal of Modern Technology [Internet]. 2025 Jun. 28;2(01):292-301. https://review.journal-of-modern-technology.com/index.php/jmt/article/view/63
[27]. Akuthota S. Enhancing Chronic Obstructive Pulmonary Disease (COPD) Diagnosis through Machine Learning Models Trained on Respiratory Sounds. In 2025 2nd International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE) 2025 May 7 (pp. 1-6). IEEE. doi: 10.1109/RMKMATE64874.2025.11042677
[28]. Vidhyalakshmi MK, Dhanabalan SS, Nithiyanandam N, Rajesh M. Leveraging Machine Learning for Paddy Disease Identification in Sustainable Agriculture. In Smart Technologies for Sustainable Development Goals 2025 May 26 (pp. 195- 211). CRC Press.
[29]. Elsayed EE, Hayal MR, Juraev DA. Ensemble Machine Learning Approaches for Robust Classification of Maize Plant Leaf Diseases. Journal of Modern Technology. 2024 Nov. 25;1(2):87-93. https://review.journal-of-moderntechnology.com/index.php/jmt/article/view/17
[30]. Soma A kumar. Hybrid RNN-GRU-LSTM Model for Accurate Detection of DDoS Attacks on IDS Dataset. Journal of Modern Technology. 2025 May 14;2(01):283-91. https://review.journal-of-moderntechnology.com/index.php/jmt/article/view/55
[31]. Soma AK. Weighted Graph Clustering with PaCCo. In 2025 International Conference on Emerging Systems and Intelligent Computing (ESIC) 2025 Feb 8 (pp. 815-818). IEEE. doi: 10.1109/ESIC64052.2025.10962723
[32]. Dintakurthy Y, Innmuri RK, Vanteru A, Thotakuri A. Emerging Applications of Artificial Intelligence in Edge Computing: A Comprehensive Review. Journal of Modern Technology. 2025 Jan. 25;1(2):175-8. https://review.journal-of-moderntechnology.com/index.php/jmt/article/view/31
[33]. Nithiyanandam N, Rajesh M, Sitharthan R, Shanmuga Sundar D, Vengatesan K, Madurakavi K. Optimization of performance and scalability measures across cloud based IoT applications with efficient scheduling approach. International Journal of Wireless Information Networks. 2022 Dec;29(4):442-53. https://doi.org/10.1007/s10776-022-00568-5
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Kiran Saripudi (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.