Artificial Intelligence Driven Management Information Systems for Enhancing Social Equity, Economic Sustainability and Managing Costs and Challenges

Abstract

Artificial Intelligence driven Management Information Systems are reshaping organizational practice by improving efficiency, promoting social equity, and strengthening economic sustainability. Compared with traditional MIS that often struggle with large scale data handling and fair decision processes, AI enabled systems provide adaptive analytics that optimize resource allocation and decision support. This study used a cross-sectional survey of 350 respondents from diverse organizational sectors in the United States to evaluate AI based MIS performance across three domains, operational efficiency, social equity, and sustainable economic outcomes, alongside cost considerations and barriers to implementation. Data were analyzed with descriptive statistics, correlation, regression, and chi square (χ²) tests. Results indicate notable efficiency gains, with 72 percent of respondents reporting faster decision making (β = 0.54, r = 0.61). Equity indicators improved, as 68 percent observed fairer distribution of resources (β = 0.48, p = 0.01, r = 0.57). Economic sustainability also advanced, with 65 percent citing cost savings and more efficient use of inputs (β = 0.51, r = 0.59). Implementation challenges were common, reported by 54 percent of organizations, and were linked to technical integration, workforce training, and data privacy concerns (χ² = 28.7, p = 0.001). Overall, higher AI readiness was associated with fewer obstacles and stronger benefits. The findings suggest that AI driven MIS can meaningfully elevate operational performance while supporting equitable and sustainable outcomes, provided that organizations invest in integration capacity, staff upskilling, and robust data governance.