Industries’ Generative AI Adoption: A Functional and Comparative Analysis

Abstract

This research analyzes the adoption of Gen AI in industries and business functions based on secondary data from McKinsey Global Survey on AI (2024). The research works towards achieving three fundamental goals: (1) comparing industry patterns of AI use, (2) assessing if adoption rates of AI vary significantly between business functions, and (3) identifying functions with highest and lowest adoption rates. Eight industry segments and eleven business activities were examined using a mix of correlation analysis, one-way ANOVA, and visualization (heatmap, donut chart). The heatmap of correlations showed strong similarity in AI adoption behavior across digitally high-end industries like Technology & Media and Telecom (r = 0.91) and Technology & Financial Services (r = 0.90), and maximum divergence was exhibited by Media and Telecom & Consumer Goods and Retail (r = 0.61). One-way ANOVA outcomes showed statistically significant differences in mean AI adoption rates across business functions (F = 19.31, p < 0.001), rejecting the null hypothesis of equal adoption. Marketing and Sales was the top function (20.9%), followed by Product/Service Development (13.9%), while Supply Chain/Inventory Management (3.5%) and Manufacturing (2.5%) had the lowest adoption. Findings point out that Gen AI adoption is not balanced over both industry and function lines, with implications for AI investment, workforce planning, and industry-specific digital transformation strategies. This study offers a cross-sectional baseline for policymakers, executives, and academics to grasp existing adoption trends and guide focused AI implementation strategies.