Trust in government as a mediator in the relationship between AI implementation and citizen satisfaction: Evidence from UAE Policing

Shamsah Rashid Saeed Ali Alhefaity; Effendi Mohamad; Mohamad Ridzuan Jamli; Teruaki Ito; Aisyah Larasati; Nor Akramin Mohamad

doi:10.31893/multiscience.2026292

Keywords:

artificial intelligence

citizen satisfaction

trust in government

United Arab Emirates

Abstract

This study investigates the influence of Artificial Intelligence (AI) implementation on citizen satisfaction with police services in the United Arab Emirates (UAE), with a specific focus on the mediating role of trust in government. As smart policing initiatives expand under the UAE’s digital governance agenda, understanding how AI technologies shape public trust and service perceptions becomes increasingly critical for sustainable public engagement. A quantitative research design was adopted using a cross-sectional survey method. Data were collected from 365 police personnel within the Abu Dhabi Police across AI-enhanced, operational, and administrative units. Structural Equation Modeling (PLS-SEM) was employed to assess both direct and indirect relationships among AI implementation, trust in government, and citizen satisfaction. Validated scales and reliability checkswere used to ensure measurement accuracy. The results demonstrate that AI implementation has a significant positive effect on citizen satisfaction (β = 0.400, p < 0.001) and trust in government (β = 0.511, p < 0.001). Trust in government, in turn, significantly influences citizen satisfaction (β = 0.321, p < 0.001) and mediates the relationship between AI implementation and satisfaction (indirect effect β = 0.164, p < 0.001). These findings support the conceptual framework grounded in Public Value Theory and Expectation-Confirmation Theory, highlighting the importance of trust as a critical mechanism through which AI influences public attitudes toward policing services. This study offers actionable guidance for policymakers and law enforcement agencies seeking to integrate AI responsibly. Emphasis should be placed on transparency, citizen-centric design, and ethical AI governance to reinforce trust and ensure positive service experiences. AI strategies must be aligned with public expectations to sustain long-term satisfaction. The study contributes to emerging literature on digital public service delivery by empirically validating the mediating role of trust in government in AI-supported law enforcement. It is among the first to explore this dynamic in the context of UAE policing, offering region-specific insights into the interplay between technology, institutional trust, and citizen satisfaction.
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How to cite

Alhefaity, S. R. S. A., Mohamad, E., Jamli, M. R., Ito, T., Larasati, A., & Mohamad, N. A. (2025). Trust in government as a mediator in the relationship between AI implementation and citizen satisfaction: Evidence from UAE Policing. Multidisciplinary Science Journal, 8(5), 2026292. https://doi.org/10.31893/multiscience.2026292

[1] Abdulkareem, A.K. and Mohd Ramli, R., 2022. Does trust in e-government influence the performance of e-government? An integration of information system success model and public value theory. Transforming Government: People, Process and Policy, 16(1), pp.1-17.

[2] Abdulkareem, A.K., Abdulkareem, Z.J., Ishola, A.A. and Akindele, I.T., 2022. Does e-government impact e-participation? The influence of trust in e-government. International Review of Public Administration, 27(2), pp.91-110.

[3] Agrawal, G., 2024. Accountability, Trust, and Transparency in AI Systems From the Perspective of Public Policy: Elevating Ethical Standards. In AI Healthcare Applications and Security, Ethical, and Legal Considerations (pp. 148-162). IGI Global.

[4] Ahn, M.J. and Chen, Y.C., 2022. Digital transformation toward AI-augmented public administration: The perception of government employees and the willingness to use AI in government. Government Information Quarterly, 39(2), p.101664.

[5] Al Shamsi, H.R.S. and Safei, S., 2023. PLS-SEM Model of Crime Mitigation Performance of Abu Dhabi Police Predictive Policing. Tropical Scientific Journal, 2(2), pp.95-113.

[6] Al Shamsi, H.R.S. and Safei, S.A., 2023. Artificial Intelligence Adoption in Predictive Policing to Predict Crime Mitigation Performance. International Journal of Sustainable Construction Engineering and Technology, 14(3), pp.289-298.

[7] AlAwadhi, S., Alansari, H. and Alsaber, A.R., 2023. Explicating Trust-building Factors Impacting the Use of e-government Services. Social Science Computer Review, p.08944393231220757.

[8] Alghafli, A., Mohamad, E. and Zaidy, A.A., 2021. The relationship between the elapsed time from the onset of red signal until its violation and traffic accident

[9] occurrence in Abu Dhabi, UAE. Safety, 7(3), p.53.

[10] Alkaabi, F.A., Maghelal, P.K. and AlShkeili, J.A., 2024. Determinants of sickness absence in police: Case study of Abu Dhabi police department, UAE. Heliyon, 10(1).

[11] Alkraiji, A. and Ameen, N., 2022. The impact of service quality, trust and satisfaction on young citizen loyalty towards government e-services. Information Technology & People, 35(4), pp.1239-1270.

[12] Alkraiji, A.I., 2021. An examination of citizen satisfaction with mandatory e-government services: comparison of two information systems success models. Transforming Government: People, Process and Policy, 15(1), pp.36-58.

[13] Almarzooqi, A., 2019. Towards an artificial intelligence (AI)-driven government in the United Arab Emirates (UAE): a framework for transforming and augmenting leadership capabilities. Pepperdine University. PhD Thesis. Available at: https://core.ac.uk/download/pdf/288854477.pdf (Accessed: 1 September 2024).

[14] Almesafri, A. and Habes, M., 2022, March. Understanding the use of Artificial Intelligence (AI) for human resources in the Dubai government. In International Conference on Business and Technology (pp. 417-428). Cham: Springer International Publishing.

[15] Alsarraf, H.A., Aljazzaf, S. and Ashkanani, A.M., 2022. Do you see my effort? An investigation of the relationship between e-government service quality and trust in government. Transforming Government: People, Process and Policy, 17(1), pp.116-133.

[16] Al-Shamsi, A. and Ahmad, N.B., 2024. Opportunities and Challenges of AI Adoption by the Abu Dhabi Police: A Review Study. International Journal of Academic Research, 13(3), pp.627-637.

[17] Alzahrani, L., Al-Karaghouli, W. and Weerakkody, V., 2017. Analysing the critical factors influencing trust in e-government adoption from citizens’ perspective: A systematic review and a conceptual framework. International business review, 26(1), pp.164-175.

[18] Amosun, T.S., Chu, J., Rufai, O.H., Muhideen, S., Shahani, R. and Gonlepa, M.K., 2022. Does e-government help shape citizens' engagement during the COVID-19 crisis? A study of mediational effects of how citizens perceive the government. Online Information Review, 46(5), pp.846-866.

[19] Bagaric, M., Svilar, J., Bull, M., Hunter, D. and Stobbs, N., 2022. The solution to the pervasive bias and discrimination in the criminal justice system: transparent and fair artificial intelligence. Am. Crim. L. Rev., 59, p.95.

[20] Bastiaansen, M., Lub, X.D., Mitas, O., Jung, T.H., Ascenção, M.P., Han, D.I., Moilanen, T., Smit, B. and Strijbosch, W., 2019. Emotions as core building blocks of an experience. International Journal of Contemporary Hospitality Management, 31(2), pp.651-668.

[21] Bhattacherjee, A., 2001. Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, pp.351-370.

[22] Brayne, S. and Christin, A., 2021. Technologies of crime prediction: The reception of algorithms in policing and criminal courts. Social problems, 68(3), pp.608-624.

[23] Bryson, J.M., Crosby, B.C. and Bloomberg, L., 2014. Public value governance: Moving beyond traditional public administration and the new public management. Public administration review, 74(4), pp.445-456.

[24] Chan, F.K., Thong, J.Y., Brown, S.A. and Venkatesh, V., 2021. Service design and citizen satisfaction with e‐government services: a multidimensional perspective. Public Administration Review, 81(5), pp.874-894.

[25] Chatterjee, S. and Sreenivasulu, N.S., 2019. Personal data sharing and legal issues of human rights in the era of artificial intelligence: Moderating effect of government regulation. International Journal of Electronic Government Research (IJEGR), 15(3), pp.21-36.

[26] Chatterjee, S., 2020. AI strategy of India: policy framework, adoption challenges and actions for government. Transforming Government: People, Process and Policy, 14(5), pp.757-775.

[27] Chatterjee, S., Kar, A.K., Dwivedi, Y.K. and Kizgin, H., 2020. Prevention of cybercrimes in smart cities of India: from a citizen’s perspective. Information Technology & People, 32(5), pp.1153-1183.

[28] Chatterjee, S., Khorana, S. and Kizgin, H., 2022. Harnessing the potential of artificial intelligence to foster citizens’ satisfaction: An empirical study on India. Government Information Quarterly, 39(4), p.101621.

[29] Chen, Y.C., Ahn, M.J. and Wang, Y.F., 2023. Artificial intelligence and public values: value impacts and governance in the public sector. Sustainability, 15(6), p.4796.

[30] Chohan, S.R., Hu, G., Khan, A.U., Pasha, A.T. and Sheikh, M.A., 2021. Design and behavior science in government-to-citizens cognitive-communication: a study towards an inclusive framework. Transforming Government: People, Process and Policy, 15(4), pp.532-549.

[31] Fjaeran, L. and Aven, T., 2021. Creating conditions for critical trust–How an uncertainty-based risk perspective relates to dimensions and types of trust. Safety science, 133, p.105008.

[32] Fornell, C. and Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp.39-50.

[33] Garritzmann, J.L., Neimanns, E. and Busemeyer, M.R., 2023. Public opinion towards welfare state reform: The role of political trust and government satisfaction. European Journal of Political Research, 62(1), pp.197-220.

[34] Guo, Y. ed., 2024. Digital Government and Public Interaction: Platforms, Chatbots, and Public Satisfaction: Platforms, Chatbots, and Public Satisfaction. IGI Global.

[35] Guo, Y., 2022. Digital trust and the reconstruction of trust in the digital society: An integrated model based on trust theory and expectation confirmation theory. Digital Government: Research and Practice, 3(4), pp.1-19.

[36] Hair Jr, J.F., Howard, M.C. and Nitzl, C., 2020. Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, pp.101-110.

[37] Hair, J. and Alamer, A., 2022. Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), p.100027.

[38] He, A.J. and Ma, L., 2021. Citizen participation, perceived public service performance, and trust in government: Evidence from health policy reforms in Hong Kong. Public performance & management review, 44(3), pp.471-493.

[39] Hooda, A., Gupta, P., Jeyaraj, A., Giannakis, M. and Dwivedi, Y.K., 2022. The effects of trust on behavioral intention and use behavior within e-government contexts. International Journal of Information Management, 67, p.102553.

[40] Ingrams, A., Kaufmann, W. and Jacobs, D., 2022. In AI we trust? Citizen perceptions of AI in government decision making. Policy & Internet, 14(2), pp.390-409.

[41] Kamarudin, S., Omar, S.Z., Zaremohzzabieh, Z., Bolong, J. and Osman, M.N., 2021. Factors predicting the adoption of e-government services in telecenters in rural areas: The mediating role of trust. Asia-Pacific Social Science Review, 21(1), p.3.

[42] Kim, N.Y., Kim, H.J. and Kim, S.H., 2022. Are satisfied citizens willing to participate more? An analysis of citizens’ life satisfaction in the public service domain and public participation. International Review of Public Administration, 27(3), pp.211-227.

[43] Kleizen, B., Van Dooren, W., Verhoest, K. and Tan, E., 2023. Do citizens trust trustworthy artificial intelligence? Experimental evidence on the limits of ethical AI measures in government. Government Information Quarterly, 40(4), p.101834.

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