Anigboro, Oghenetega Deborah Wash and Odinaka, Nnadozie and Ajayi, Olajumoke Oluwagbemisola (2025) How big data and AI are changing business growth. GSC Advanced Research and Reviews, 23 (3). pp. 258-264. ISSN 2582-4597
Abstract
Big data analytics has totally changed how people grow businesses. It used to be all about guesses and experience, but now it’s about using data to figure things out. This article looks at how big data, Artificial Intelligence (AI), and business tools help with things like studying markets, figuring out who customers are, and making smart decisions. By using all kinds of data organized or messy people growing businesses can make things run smoother, find new customers automatically, and keep growing even when competition is tough. However, transitioning to a data-driven approach comes with its challenges. There are problems like data privacy, dealing with too much information, and figuring out if using AI and big data is fair. This article explains these tricky parts and gives tips on how businesses can handle them while following rules and doing the right thing. It also shares the best ways to use big data like making sure the data is good, working as a team, and using new technology tools. Looking ahead, the future of growing businesses is going to be exciting, with AI, machine learning, and real time analytics will further enhance business predictions, personalization and strategic decision making. The article concludes by discussing what this means for business developers and how they need to keep learning and adapting to the changes. In the end, mixing big data and AI into business growth is both a challenge and a big chance to come up with new ideas, stand out, and win big in today’s digital world.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/gscarr.2025.23.3.0161 |
Uncontrolled Keywords: | Business Growth; Big Data; Data Tools; Artificial Intelligence; Predictive Modeling; Ethical Challenges |
Date Deposited: | 01 Sep 2025 15:01 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/5946 |