The research explores the ways in which artificial intelligence (AI) contributes to the evolution of personalized learning practices at the university level, with a focus on adaptive learning systems, intelligent tutoring technologies, and AI-driven analytics. Uniquely, it provides a novel synthesis of comparative evidence from universities in the U.S. and Europe, and operationalizes these insights into a strategic adoption framework tailored for higher education. While existing research highlights AI’s potential, outcomes remain inconsistent: some implementations report notable gains in student achievement, whereas others observe only modest benefits relative to conventional teaching. Through a cross-contextual analysis, this study extracts key insights from case studies and empirical evidence, illustrating that adaptive learning approaches may increase pass rates by up to 20 percentage points, that intelligent tutoring can enhance academic results, and that analytics-based strategies have a substantial effect on student retention. Crucially, sustained success is linked to human-centered implementation, ongoing faculty training, and iterative evaluation. This paper offers actionable recommendations and a roadmap for Romanian universities to pilot and scale AI-powered personalized learning. In line with the EED Conference theme, it bridges best practices and local needs, highlighting how thoughtful AI integration can drive both educational innovation and student success in Romania.