This study investigates the transformative potential of integrating Artificial Intelligence (AI) and Blockchain technologies in the mergers and acquisitions (M&A) process. Traditional M&A practices are often hindered by inefficiencies, information asymmetry, and reliance on manual judgment. By combining AI’s analytical capabilities with blockchain’s secure, immutable infrastructure, this research proposes a novel, end-to-end digital framework designed to improve speed, transparency, and decision accuracy throughout the M&A lifecycle. The study applies machine learning and natural language processing to assess financial compatibility and operational risk, while blockchain ensures data integrity, auditability, and stakeholder trust. Empirical validation using a benchmark M&A dataset yielded an AUC score of 0.76, indicating strong predictive performance in evaluating merger success. Blockchain transaction analysis further revealed enhanced transparency during the due diligence and negotiation phases. The findings suggest that this integrated approach offers significant time savings, improved risk assessment, and greater strategic clarity. The paper concludes with practical recommendations for practitioners, developers, and regulators and identifies avenues for future research, including industry-specific adaptations and cross-border implementation. This research not only fills a critical gap in current M&A literature but also offers a validated model for organizations seeking to modernize and de-risk their dealmaking processes through digital innovation.