Artificial Intelligence, Digital Transformation and the Future of Society

Artificial intelligence (AI) is accelerating digital transformation across work, education, healthcare, public administration, communication and everyday decision-making. Yet the social value of this transformation depends not only on technical capability, but also on digital access, human skills, public trust and accountable governance. This article presents a simulated empirical study designed to examine societal readiness for an AI-enabled future. A synthetic, stratified cross-sectional dataset representing 720 illustrative adults across urban, semi-urban and rural settings was generated using reproducible assumptions and five-point scales. The analysis tested the effects of digital access, AI literacy, trust, perceived usefulness, privacy concern, job-displacement concern and support for governance. Simulated results showed an overall societal-readiness mean of 3.35 (SD = 0.70). Urban respondents recorded higher readiness (M = 3.69) than semi-urban (M = 3.32) and rural groups (M = 3.04), F(2, 717) = 62.70, p < .001, η² = .149. The regression model explained 51.3% of the variance in readiness. Digital access (β = .268), trust (β = .238), AI literacy (β = .195) and perceived usefulness (β = .188) were the strongest positive predictors, while privacy concern (β = -.090) and job-displacement concern (β = -.057) had smaller negative effects. The findings are illustrative rather than population estimates, but they demonstrate a coherent empirical framework for studying how inclusion, capability and governance can shape the future of society. The article concludes that AI policy should combine infrastructure, universal AI literacy, human oversight, transparency and social protection.