AI Literacy and Instructional Design Readiness as Predictors of Instructional Innovation among University Faculty in Lahore: A Cross-Sectional Predictive Study

The rapid adoption of generative artificial intelligence (AI) in higher education is revolutionizing the planning, teaching and evaluation of learning among university teachers. However, adoption of AI by faculty is quite dissimilar, which raises an applied question to institutions regarding what faculty competencies are the strongest predictors of instructional innovation. This study assessed the hypothesis of the presence of association between AI literacy and instructional design preparedness with instructional innovation among university faculty in Lahore, with a non-experimental cross-sectional study design. The survey data was gathered with 108 members of the faculty in two universities; and standardized measures were used in measuring AI literacy, instructional design readiness, and instructional innovation. Moderate to high levels of all three constructs were found in terms of descriptive results. To address the comparative objective, a hierarchical regression model was estimated. Instructional design readiness alone explained 33.6% of variance in instructional innovation (R² = .336, p < .001). Adding AI literacy increased explained variance to 43.6% (ΔR² = .100, p < .001). In the final model, AI literacy showed a significant unique association with instructional innovation (β = .69, p < .001), while instructional design readiness was not statistically significant after accounting for AI literacy (β = −.04, p = .826), consistent with substantial overlap between the two competencies (VIF = 4.80). The findings suggest that, within this sample, AI literacy may be the more distinctive faculty capacity linked to instructional experimentation in AI-rich teaching environments, while instructional design readiness remains foundational but less discriminating when the competencies overlap. Implications are discussed for targeted faculty development and institutional support for responsible AI-enabled teaching innovation.