Cybercrime has evolved significantly with the rise of cryptocurrency, encrypted communication platforms, and decentralised systems, presenting major challenges for law enforcement. Criminals exploit these technologies to engage in illicit activities such as money laundering, ransomware, and drug trafficking while maintaining anonymity. This study investigates how digital forensics, blockchain analysis, and artificial intelligence (AI) can enhance cybercrime investigations. A systematic literature review and case study analysis were conducted, focusing on law enforcement’s struggles in tracing cryptocurrency transactions, dismantling Dark Web marketplaces, and adapting to emerging cyber threats. Findings reveal that while forensic tools like blockchain analytics and AI-driven cybersecurity measures offer promising solutions, challenges remain in jurisdictional enforcement, privacy-focused cryptocurrencies, and the rapid evolution of cybercriminal tactics. The discussion highlights gaps in current forensic methodologies and explores the effectiveness of advanced investigative tools in mitigating cybercrime risks. Recommendations include increased investment in forensic research, international collaboration, and the development of AI-assisted policing strategies. As cybercrime continues to evolve, future research must focus on predictive analytics, cross-border regulatory frameworks, and adaptive law enforcement techniques to counter emerging threats in the digital landscape.