Applied IT & Engineering
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Applied IT & Engineering

Volume 2 Number 1 2024

Article Contents

RESEARCH ARTICLE   (Open Access)
Contents Vol 2 (1)

The Role of Deep Learning and AI in Revolutionizing Business Analytics: Frameworks, Applications, and Managerial Implications

 Sonia Nashid1*, Sonia Khan Papia2, Ariful Islam3, Al Akhir3, Fahim Rahman4, Anik Biswas5

+ Author Affiliations

Applied IT & Engineering 2 (1) 1-8 https://doi.org/10.25163/engineering.2110365

Submitted: 09 July 2024 Revised: 21 September 2024  Published: 23 September 2024 

Abstract

Background: The evolution of Artificial Intelligence (AI) and deep learning has changed the context within which business analytics previously functioned, allowing businesses to take advantage of predictive and prescriptive versions of decision making in relation to traditional data driven methods. Although AI and deep learning methodologies hold promise, their implementation merits rigorous empirical investigation to establish the nature and extent of the adoption, applications, and implications for management purposes. Methods: A survey was conducted with 125 respondents that are managers, data analysts, and IT professionals to examine the adoption and influence of AI and deep learning in business analytics. Data were analyzed using descriptive statistics and percentage distributions to articulate distinct adoption trends and managerial perspectives. Results: The research shows that 73.6% of participants use AI predictive analytics and 64.8% use NLP for sentiment analysis and 60.8% use AI process automation. The study shows that 53.6% of respondents use AI to forecast strategically and 47.2% use it for fraud detection. The survey results show that better decision-making (78%) and better customer engagement (65%) and decreased operational inefficiencies (70%) are all important managerial implications. The research reveals that ethical use along with data privacy and workforce skill gaps remain major problems. The research proves that deep learning together with AI transforms business analytics by providing better predictive functions alongside improved operational efficiency. Conclusion: The successful integration of these systems depends on solving ethical and technical problems as well as organizational challenges. Management needs to develop strategic frameworks which focus on training and governance and scalability to optimize benefits.

Keywords: Artificial Intelligence (AI); Deep Learning; Business Analytics; Managerial Implications; Predictive Modeling

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