Evaluating the Adoption of Artificial Intelligence in Public Relations Practices of Select Banks in Abuja Municipal Area Council (AMAC)

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Ene Christiana Olowu

Abstract

As the world transitions from the astrological age of Pisces which is the age of believing, to the astrological age of Aquarius which is the age of knowing, information and communication, technology is also evolving and this has given rise to the adoption of Artificial intelligence in many industries in recent times. This study examined the adoption and utilization of Artificial Intelligence in Public Relations practice in some select banks in Abuja Municipal Area Council (AMAC). The study adopted the Uses and Gratification Theory (UGT) for the theoretical framework. Descriptive survey research design was adopted using Taro Yamane to arrive at a sample size of 400 respondents. Furthermore, simple random sampling technique was employed in selecting the respondents. Questionnaire was the main instrument for data collection; the mean score and standard deviation were used to analyze the data. The major findings of the study are that there are positive relations between artificial intelligence and public relations in the select banks in AMAC. In view of the findings, the study concludes that there is adoption of artificial intelligence (AI) in public relations (PR) practices within banking sectors in AMAC.  The study recommended that there is the need to adopt Measurement and Evaluation in determining the performance and effectiveness of AI-driven PR strategies as well as its impact on new media approaches. It also recommends that stakeholders in the banks should establish key performance indicators (KPIs) and metrics to measure the success of level of perception and level of providing information about the use of AI.

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Article Details

How to Cite
Olowu, E. C. (2025). Evaluating the Adoption of Artificial Intelligence in Public Relations Practices of Select Banks in Abuja Municipal Area Council (AMAC). ALSYSTECH Journal of Education Technology, 3(2), 149-169. https://doi.org/10.58578/alsystech.v3i2.5083

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