AI-Powered Trend Analysis for Retail

Authors

  • Dr. Daniel Vega Professor of Industrial Engineering, Pontificia Universidad Católica de Chile (PUC Chile) Author

Keywords:

Trend Analysis, Retail

Abstract

AI integration has caught great attention as an extended approach according to the requirements of big data analytics, clear objectives, and an overall reassured model for retail. AI can be utilized for trend analysis, which is helpful for understanding all the transactions throughout the process and supporting the decision-making process by learning from data, so that business units can understand trends and optimize operations for improving management. Moreover, AI can also be applied to produce trend analysis results in order to reduce the costs of consumables while creating a consistent and unified overall system without diverging analyses. Therefore, the ability of AI to perceive business trends accurately and efficiently is playing an increasingly critical role.

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References

S. Kumari, “AI-Driven Cybersecurity in Agile Cloud Transformation: Leveraging Machine Learning to Automate Threat Detection, Vulnerability Management, and Incident Response”, J. of Art. Int. Research, vol. 2, no. 1, pp. 286–305, Apr. 2022

Tamanampudi, Venkata Mohit. "A Data-Driven Approach to Incident Management: Enhancing DevOps Operations with Machine Learning-Based Root Cause Analysis." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 419-466.

Machireddy, Jeshwanth Reddy. "Revolutionizing Claims Processing in the Healthcare Industry: The Expanding Role of Automation and AI." Hong Kong Journal of AI and Medicine 2.1 (2022): 10-36.

Singh, Jaswinder. "Sensor-Based Personal Data Collection in the Digital Age: Exploring Privacy Implications, AI-Driven Analytics, and Security Challenges in IoT and Wearable Devices." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 785-809.

Tamanampudi, Venkata Mohit. "Natural Language Processing for Anomaly Detection in DevOps Logs: Enhancing System Reliability and Incident Response." African Journal of Artificial Intelligence and Sustainable Development 2.1 (2022): 97-142.

J. Singh, “How RAG Models are Revolutionizing Question-Answering Systems: Advancing Healthcare, Legal, and Customer Support Domains”, Distrib Learn Broad Appl Sci Res, vol. 5, pp. 850–866, Jul. 2019

Tamanampudi, Venkata Mohit. "AI and NLP in Serverless DevOps: Enhancing Scalability and Performance through Intelligent Automation and Real-Time Insights." Journal of AI-Assisted Scientific Discovery 3.1 (2023): 625-665.

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Published

02-12-2023

How to Cite

[1]
D. D. Vega, “AI-Powered Trend Analysis for Retail”, J. of Artificial Int. Research and App., vol. 3, no. 2, pp. 709–728, Dec. 2023, Accessed: Nov. 21, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/278

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