The Impact of Artificial Intelligence–Driven Business Analytics on Innovation and Financial Performance in the Indian IT Sector: A Data Driven Study

Abstract

Artificial Intelligence–driven Business Analytics (AIBI) is reshaping how IT firms generate insights, allocate resources, and innovate. This paper empirically examines the relationship between AIBI adoption, R&D investment, and firmlevel innovation and financial performance in the Indian IT sector. Using a constructed multiyear panel of 150 firms (2015–2025; N=1,650 firmyears), we estimate OLS models, perform independent samples ttests, and conduct oneway ANOVA. Descriptive and inferential results reveal: (i) significant positive associations between AIBI adoption, R&D intensity, and innovation; (ii) strong explanatory power for innovation outcomes (Adj. R² ≈ 0.704); and (iii) statistically significant performance differences between low and high AI adopters (t ≈ 27.23, p < 0.001) and across AI adoption tiers (ANOVA F ≈ 361.22, p < 0.001). While automation and market share contribute, the interaction of AI adoption with R&D intensity emerges as the strongest lever for innovation. We discuss managerial implications for capital allocation, capability building, and governance, and propose a staged AIBI maturity roadmap for Indian IT firms. The paper contributes a transparent, reproducible methodology with openly provided dataset and scripts to support replication and instructional use.