Managing Production Processes in TV Advertising Using AI

This paper investigates the role of artificial intelligence (AI) in operational management of production process of TV advertising. But as AI technology swiftly develops, it opens new doors for the ad industry to improve efficiency, optimize creative approaches and fine-tune messaging. Integrating AI into the production cycle can help advertising companies streamline the functioning of the operation, improve the decision-making process, and better predict consumer behavior. The paper examines different forms of AI-based machine learning and automation tools such Decision Trees, Random Forest, and Gradient Boosting Machines (GBMs) that can help enhance the efficiency and efficacy of TV and production processes. The results show that GBMs got the highest accuracy with 87 % line up with findings previously reported that show AI applications in this space can help provide significant cost savings, speed, and relevancy of content. The paper also addresses the challenges and ethical implications of using AI in media, especially how it affects data privacy and creates the possibility of bias in automated decision-making. AI is a transformative force in TV advertising, fostering more precise, effective, and personalized marketing strategies.

Authors

Institutions

Publication Details

Published
2025-04-05
DOI
https://doi.org/10.1109/icmi65310.2025.11141255
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Managing Production Processes in TV Advertising Using AI

Nassif Jassim Mohammed, Omar Yassein Abdul Jalil, Noor Mohammed Shaker
Assembly Line Balancing Optimization
article

Managing Production Processes in TV Advertising Using AI

Nassif Jassim Mohammed, Omar Yassein Abdul Jalil, Noor Mohammed Shaker
article en

Abstract

This paper investigates the role of artificial intelligence (AI) in operational management of production process of TV advertising. But as AI technology swiftly develops, it opens new doors for the ad industry to improve efficiency, optimize creative approaches and fine-tune messaging. Integrating AI into the production cycle can help advertising companies streamline the functioning of the operation, improve the decision-making process, and better predict consumer behavior. The paper examines different forms of AI-based machine learning and automation tools such Decision Trees, Random Forest, and Gradient Boosting Machines (GBMs) that can help enhance the efficiency and efficacy of TV and production processes. The results show that GBMs got the highest accuracy with 87 % line up with findings previously reported that show AI applications in this space can help provide significant cost savings, speed, and relevancy of content. The paper also addresses the challenges and ethical implications of using AI in media, especially how it affects data privacy and creates the possibility of bias in automated decision-making. AI is a transformative force in TV advertising, fostering more precise, effective, and personalized marketing strategies.

Middle Technical University (IQ), Ministry of Higher Education and Scientific Research (IQ)
Openalex Percentile: Top 66%
Assembly Line Balancing Optimization
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.

Managing Production Processes in TV Advertising Using AI — Nassif Jassim Mohammed, Omar Yassein Abdul Jalil, et al. · (2025) | TGRS Research Map | TGRS