Integration of Artificial Intelligence and Risk Management: Telecommunications Companies in Najaf as a Model

The research aims to explore the role of artificial intelligence in improving risk management in telecommunications companies in the city of Najaf. A descriptive-analytical approach was used to study and analyze available data on the use of artificial intelligence in telecommunications companies, with a focus on the integration of technologies and risk management. Various data collection tools, such as questionnaires, were employed in the targeted companies, and data were analyzed using statistical tools like SPSS. The study population consisted of managers, department heads, and accountants working at Zain Telecommunications Company in Najaf. A purposive sample of 50 individuals was selected from the study population, and the questionnaire was distributed to them after being reviewed and validated. A total of 40 valid questionnaires were retrieved for statistical analysis. Among the key findings: Artificial intelligence provides advanced tools for risk management, enhancing companies' ability to predict future events and handle them more effectively. It also plays a major role in improving risk management by increasing efficiency and reducing costs. There is a strong, positive, and statistically significant correlation between artificial intelligence and risk management at a significance level of 5%. Among the key recommendations: Specialized training programs should be provided for employees in telecommunications companies on artificial intelligence technologies, particularly in the fields of data analysis and risk management.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
DOI
https://doi.org/10.36325/ghjec.v21i1.19197
Primary Topic
Environmental Monitoring and Data Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integration of Artificial Intelligence and Risk Management: Telecommunications Companies in Najaf as a Model

SHILAP Revista de lepidopterología
Environmental Monitoring and Data Management
article

Integration of Artificial Intelligence and Risk Management: Telecommunications Companies in Najaf as a Model

article en

Abstract

The research aims to explore the role of artificial intelligence in improving risk management in telecommunications companies in the city of Najaf. A descriptive-analytical approach was used to study and analyze available data on the use of artificial intelligence in telecommunications companies, with a focus on the integration of technologies and risk management. Various data collection tools, such as questionnaires, were employed in the targeted companies, and data were analyzed using statistical tools like SPSS. The study population consisted of managers, department heads, and accountants working at Zain Telecommunications Company in Najaf. A purposive sample of 50 individuals was selected from the study population, and the questionnaire was distributed to them after being reviewed and validated. A total of 40 valid questionnaires were retrieved for statistical analysis. Among the key findings: Artificial intelligence provides advanced tools for risk management, enhancing companies' ability to predict future events and handle them more effectively. It also plays a major role in improving risk management by increasing efficiency and reducing costs. There is a strong, positive, and statistically significant correlation between artificial intelligence and risk management at a significance level of 5%. Among the key recommendations: Specialized training programs should be provided for employees in telecommunications companies on artificial intelligence technologies, particularly in the fields of data analysis and risk management.

SHILAP Revista de lepidopterología
Presidency University (BD), University of Kufa (IQ)
Openalex Percentile: Top 43%
Environmental Monitoring and Data Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.