Assessing the Impact of Artificial Intelligence on Community-Level Negotiations in Akwa Ibom North-West Senatorial District

Authors

Bimpe Omolola Fayigbe

Department of General Studies, Federal Polytechnic (Ukana)

Bulus Simon

Department of Environmental Science and Management Technology, Federal Polytechnic (Ukana)

Ademola Oyeleye Oyebanji

Department of General Studies, Federal Polytechnic (Ukana)

Article Information

DOI: 10.51244/IJRSI.2025.1210000283

Subject Category: Management

Volume/Issue: 12/10 | Page No: 3250-3258

Publication Timeline

Submitted: 2025-10-30

Accepted: 2025-11-06

Published: 2025-11-19

Abstract

This study assesses the impacts of Artificial Intelligence (AI) adoption on community negotiation outcomes in Akwa Ibom North-West Senatorial District, Nigeria. Data were obtained from 308 respondents using a structured questionnaire; data were analyzed with descriptive and inferential statistics (Chi-square and multiple regression techniques). The findings revealed that, there is a moderate level of AI adoption (Mean = 2.99, SD = 1.05) in the study area, indicating growing awareness but limited application. AIbased interventions enhanced equity in dispute resolution (Mean = 3.41) and improved mediation turnaround time (Mean = 2.99). the findings (χ² = 23.14, p = 0.001) found that, there is a significant relationship between AI adoption and negotiation outcomes, while the findings from regression analysis (R² = 0.579, F(3,304) = 60.97, p < 0.001) indicated that AI adoption (β = 0.426) and stakeholder engagement (β = 0.355) significantly predicted outcomes, whereas ethical challenges (β = -0.212) had a negative influence. The findings suggest that AI can enhance transparency and inclusiveness in community governance if digital literacy and ethical challenges are addressed. The study recommends targeted AI training, infrastructural improvement, and ethical regulation to optimize AI use in local negotiations.

Keywords

Artificial Intelligence, Community Negotiation, Decision-Making, Stakeholder Engagement

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