Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM45403
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In today’s logistics sector, customer service is critical to guaranteeing smooth operations, customer happiness, and competitive advantage. Artificial intelligence (AI) has become a game-changing tool in improving customer service due to the growing need for quick, precise, and effective communication. With an emphasis on response time, problem solving, customer happiness, and overall operational efficiency, this study investigates the efficacy of AI-powered customer service solutions at Syena Logistics Pvt Ltd. Key performance metrics like average response time, resolution rate, customer feedback scores, and service efficiency before and after AI adoption are evaluated in this quantitative data analysis study. The study looks at how predictive analytics, automated query processing, and AI-driven chatbots help to streamline customer encounters while resolving typical logistical issues. The study also cites several obstacles to the implementation of AI, such as financial limitations, issues with data accuracy, staff flexibility, and integration challenges with current systems.Notwithstanding these difficulties, there are a lot of chances to improve service quality, lessen operational burden, and reduce human mistake with AI-powered solutions. The study’s conclusions give data-driven insights on the viability of enhancing customer service in the logistics industry with AI, along with suggestions for best practices to maximise AI adoption. In order to facilitate more effective and customer-focused service delivery in the dynamic global supply chain, this research attempts to assist logistics companies in comprehending the real- world advantages and difficulties of AI-driven solutions.
KEYWORDS
Publication Date
4/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
0
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...