Cultured Meat in the Age of Artificial Intelligence: Is the Time Now?

The unsustainable trajectory of global meat consumption continues to create an urgent need for alternatives or to rethink livestock systems. While plant-based options are available, consumer acceptance remains limited due to sensory shortcomings and neophobia. In contrast, cultured meat has the potential for theoretical biological equivalence to conventional meat; however, the development of cultured meat is currently constrained by unresolved biological and technical challenges. Meanwhile, artificial intelligence (AI) has emerged as a transformative tool for addressing these limitations. This systematic review evaluates the potential for AI to optimize the efficiency of cultured meat production, enhance sustainability, and accelerate market introduction. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and included 28 studies. Key findings are presented across several critical domains. Computational modeling can compensate for data scarcity by simulating industrial scenarios where experimental data are limited. AI algorithms are also shifting media development from trial-and-error approaches to predictive optimization, enabling the identification of cost-effective plant-based alternatives to animal serum. In tissue engineering, strategies vary between optimizing biological efficiency and digitally reconstructing the architecture of conventional meat. These production advances are supported by quality control systems that combine non-invasive visual monitoring with predictive safety analysis for real-time hazard detection. AI also extends to consumer intelligence, moving from passive sentiment analysis to active engagement that addresses misinformation and presents cultured meat as a transparent, personalized nutrition option. Overall, this review establishes a foundational framework that synthesizes fragmented research. Additionally, this review reveals critical economic constraints that may have previously been obscured by technical optimism. Moreover, this review identifies strategic priorities that emphasize systemic integration, open data ecosystems, and consumer-aligned value propositions, all of which are essential to translating laboratory achievements into commercial reality.