This study critically assessed Uganda's readiness to integrate Artificial Intelligence (AI) in teaching and learning environments across secondary and tertiary educational institutions. Anchored in the Technology Acceptance Model (TAM) and the Concerns-Based Adoption Model (CBAM), the study employed a cross-sectional survey design involving 420 teachers and educators drawn from 42 purposively selected schools and universities across five regions of Uganda. Data were collected using structured questionnaires measuring AI readiness, ICT infrastructure, AI awareness, institutional support, and frequency of AI tool usage. Employing a three-tier analytical framework — univariate descriptive statistics, bivariate Pearson correlations, and multilevel regression modelling — the study revealed a national mean AI readiness score of 47.3 (SD = 15.2), indicating moderate but highly unequal readiness levels across geographic and institutional divides. Institutions in Kampala recorded significantly higher readiness scores (M = 74.6) compared to Northern Uganda (M = 27.3), reflecting deeply entrenched structural inequalities. ICT infrastructure (β = 0.48, p < 0.001), AI awareness (β = 3.72, p < 0.001), and institutional support (β = 2.15, p < 0.001) emerged as the strongest predictors of AI readiness. Multilevel modelling confirmed significant school-level variance (ICC = 0.213), indicating that 21.3% of the variability in AI readiness was attributable to between-school differences rather than individual teacher characteristics. The study concludes that Uganda's education system is at a nascent and inequitable stage of AI integration, and recommends urgent policy reforms targeting infrastructure investment, educator capacity building, and national AI curriculum frameworks to ensure equitable and transformative AI-driven education for all Ugandans.