AI-Augmented Job Performance
HR & WorkReliability: alpha 0.884 sample items
About this scale
An 8-item self- and supervisor-rated measure of the extent to which AI tools improve an employee's task performance, decision quality, and creative output. Developed for human–AI collaboration research and treats AI as a complement to, rather than substitute for, human work.
Sample item(s)
“Using AI tools improves the quality of my work output.”
“AI tools help me solve work problems more effectively.”
“I am able to make better decisions when I use AI tools at work.”
“AI tools help me complete creative tasks I could not complete alone.”
Reliability
Reported internal consistency: alpha 0.88. As a rule of thumb, Cronbach’s α ≥ .70 is considered acceptable, ≥ .80 good, and ≥ .90 excellent for established measures.
Notes
Pair with AI use intensity (frequency of use) to separate exposure from outcome. Self-report bias is non-trivial — collect supervisor ratings when feasible.
Source & citation
Dell'Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023): Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality. Harvard Business School Working Paper 24-013.
Source. Scale details are summarised from the publication cited above. Always consult the original source for the full item set, scoring, and permission to use.
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