AL AND BIG DATA IN FINANCIAL PLANNING: ANEWERAFORINDIAN MARKETS

Using a mixed-methods approach that includes secondary regulatory and financial recordsinaddition to primary survey data from investors and financial professionals, this study exploresthe revolutionary effects of AI and Big Data on financial planning in Indian markets. Theobjective was to evaluate how well AI-powered solutions could improve financial inclusion, investing strategies, and risk management. Using IBM SPSS, the data was analyzedusingChi-Square tests to look at relationships between categorical variables, Independent t-teststocompare the financial results of AI adopters and traditional planners, and One-Way ANOVAto look at differences in AI adoption across demographic categories. Chi-Square tests showedgreat agreement on the usefulness of AI-driven financial instruments (p < 0.283), andtheresults showed statistically significant positive impressions of these instruments. Whencomparing the reliability of robo-advisors to human planners, independent t-tests revealednosignificant difference between groups. One-Way ANOVA, on the other hand, revealeddemographic implications on AI adoption, but with only modest statistical significance(p>0.05). Despite issues with data accessibility and differences in demographic adoption, thestudy finds that AI and Big Data are dramatically changing Indian financial planning, providing increased accuracy and efficiency.