Assessing Public Sector AI Readiness in Monkayo, Davao de Oro, Philippines: A Technology-Organization-Environment (TOE) Framework Analysis

This study evaluates Artificial Intelligence (AI) readiness in the public sector of Monkayo, Davao de Oro, Philippines, using the Technology-Organization-Environment (TOE) framework. For purposes of this study, the public sector refers to the Local Government Unit (LGU) and National Government Agency (NGA) offices operating within the municipality, whose personnel are responsible for delivering frontline administrative and public services to constituents. Using a descriptive-quantitative approach, the researcher collected data from 300 public-sector respondents to assess the Technological, Organizational, and Human Resource dimensions of AI readiness. Statistical analysis yielded an overall AI readiness mean of 3.68, indicating High AI readiness. Human Resource Readiness was identified as the most prepared and consistent dimension (M=3.91, SD=1.17), reflecting a workforce that is psychologically receptive to digital transformation. Although Technological (M=3.46) and Organizational (M=3.68) dimensions also attained high levels, they demonstrated greater internal variation, underscoring disparities in infrastructure and policy standardization across municipal offices. Within the TOE framework, the three dimensions are treated as interrelated components that jointly determine overall AI readiness rather than as independent predictors, with Human Resource Readiness acting as the strongest and most consistent component. The findings suggest that, while the workforce is ready for transition, the main obstacles to effective AI adoption are inconsistent technological resources and the lack of centralized protocols. The study recommends that local government units in developing economies prioritize technology parity programs and unified AI governance ordinances rather than culture-change initiatives. These results offer a strategic roadmap for bridging the digital divide in decentralized government structures and advancing data-driven public service delivery in similarly situated local governments in developing economies.