International Research Journal of Education and Technology

This study investigates the relationship between artificial intelligence (AI) adoption intensity and financial performance across six global automobile companies Tesla, Toyota, BMW, Tata Motors, Mahindra and Mahindra (M&M), and Maruti Suzuki over a five-year panel (FY2020–FY2024), comprising 30 firm-year observations. A novel AI Disclosure Intensity Index (ADII) was constructed from annual report disclosures as a reproducible, publicly verifiable proxy for AI adoption intensity. Financial performance is measured through Return on Assets (ROA), Operating Profit Margin (OPM), Revenue Growth Rate (RGR), and R&D Intensity (RDI). OLS regression with robust standard errors and Spearman rank-order analysis reveal that ADII is a significant positive predictor of ROA (β = 0.142, p = 0.010) and OPM (β = 0.158, p = 0.012). The ADII–RDI relationship is exceptionally strong (Spearman ρ = 0.943, p = 0.001), confirming the complementarity of AI adoption and research investment. The semiconductor supply chain disruption of 2021–22 provided a natural experiment in which AI-maturity rank predicted revenue resilience rank (ρ = 0.886, p = 0.019). Cross-firm analysis reveals a persistent performance premium for AI-intensive firms, with Tesla's AI-native architecture generating structural ROA advantages of 2–3 percentage points above the panel mean. Sub-period analysis shows strengthening ADII–ROA correlation from ρ = 0.612 to ρ = 0.731 between the pre- and post-2022 periods, consistent with General Purpose Technology (GPT) theory's prediction of compounding returns over time. These findings provide robust empirical support for the strategic and policy case for AI investment in the automotive sector, while highlighting important contextual moderators including firm size, AI maturity stage, and market geography.

Keywords: Artificial Intelligence; Automobile Industry; Financial Performance; AI Disclosure Intensity Index; Return on Assets; Operating Profit Margin; Panel Data; Resource-Based View; Dynamic Capabilities; Supply Chain Resilience; India Automotive; Tesla; Toyota; BMW.