Engineering Leadership Orientation and Perceived Organizational Enablement for Responsible Artificial Intelligence Use in Iraq

The integration of artificial intelligence (AI) into engineering practice is bringing new dimensions to the role of a leader, including professional judgment, collaboration, and responsibility for decisions made with AI's support.However, desirable personal leadership orientations do not necessarily correlate with desirable work conditions.This study examines this perceived capability-enablement divide among engineers in Iraq.Survey data were collected from 144 engineers working in Iraq using 39 Likert-scale questions.The primary withinrespondent comparison used bootstrap estimation, the Wilcoxon signed-rank test, and a cumulative ordinal fixedeffects model covering 5,616 item responses.Adjusted associations were examined using ordinary least squares regression with heteroskedasticity-consistent type 3 (HC3) standard errors and complete-profile permutation tests.Individual Leadership Orientation (ILO) was rated more favorably (M = 3.789, standard deviation [SD] = 0.435) than Organizational Enablement (OE) (M = 3.479, SD = 0.848).The mean paired difference was 0.309 points (95% bootstrap confidence interval [CI] [0.187, 0.443], p < .001;Cohen's d z = 0.394).Using the ordinal model, and controlling for respondent and item differences, the same directionality was found; that is, endorsement of Organizational Enablement was associated with lower odds (odds ratio [OR] = 0.450, 95% CI [0.380, 0.534], p < .001).AI-use frequency was associated with ILO, but its association did not differ significantly from that with OE (p = .242).Education was associated much more strongly with individual orientation than enablement.The results suggest that there is a perceived gap in capability and enablement among the engineers participating, rather than any broad opposition to AI.The results indicate that leadership orientation and perceived organizational support are separate factors to consider when designing responsible AI implementation for engineering organizations.