AHP-BASED FRAMEWORK FOR ASSESSING PROFESSIONAL TASK AUTOMATION RISK: METHODOLOGICAL DESIGN AND CROSS-SECTOR APPLICATION POTENTIAL
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https://orcid.org/0000-0001-6503-4445
Gloria Patricia Calderón Carmona
Gabriel Budiño
Abstract
The rapid advancement of artificial intelligence and automation is reshaping the nature of work, yet most occupational risk estimates remain aggregated, overlooking the variability of automation susceptibility across specific tasks. This study introduces and validates a novel, transferable methodological framework using the Analytic Hierarchy Process (AHP) to assess automation risk at the task level, grounded in structured expert judgment. The framework decomposes an occupation into discrete tasks, evaluates them against five systematically defined criteria—repetitiveness, cognitive complexity, human interaction, regulatory variability, and technological adaptability—and calculates priority vectors through pairwise comparisons. Internal consistency is verified, and inter-rater agreement is measured using Kendall’s coefficient. Applied to the accounting profession with an international panel of experts, the method identifies record keeping and report preparation as the most vulnerable tasks, while data analysis and management demonstrate greater resilience. Beyond generating ranked task vulnerability profiles, the approach reveals diversity in expert perspectives, reflecting differences in regulatory and organizational contexts. The proposed framework offers decision-makers in diverse professional and geographical contexts a replicable, evidence-based tool for anticipating technological disruption and supporting workforce adaptation strategies in the era of digital transformation.
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analytic hierarchy process, task automation, expert judgment, multi-criteria decision-making evaluation, automation risk
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