AI-enabled ESG consultancy capability building in small audit firms

This study investigates how small audit firms develop artificial intelligence-enabled environmental, social, and governance (ESG) consulting capabilities through strategic transformation pathways. Drawing upon dynamic capabilities theory and employing a mixed-methods research design, the research integrates qualitative interviews with 28 practitioners across 18 small audit firms and quantitative surveys from 156 respondents representing 87 organizations, supplemented by six in-depth case studies. The empirical analysis reveals substantial capability heterogeneity, with only 12.2% of firms deploying advanced AI applications and merely 11.5% achieving established ESG service maturity levels. A significant positive correlation between AI Intensity Index and Capability Maturity Index (r=0.68, p<0.01) demonstrates mutually reinforcing dynamics between technological adoption and domain expertise development. Cluster analysis identifies three transformation pathway archetypes—Technology-Led, Knowledge-Led, and Balanced—with Knowledge-Led approaches achieving marginally higher success rates (72.3%) compared with Technology-Led pathways (67.5%). The research develops a four-stage transformation pathway model spanning 30-36 months, delineating critical activities, resource requirements, and success indicators across foundation, development, integration, and optimization phases. AI-enabled resource optimization yields average efficiency improvements of 46.2% across operational functions, with report generation achieving 61.7% gains. The findings extend dynamic capabilities theory to resource-constrained professional services contexts and provide evidence-based guidance for practitioners navigating digital transformation in expanding ESG advisory markets.