Franklin Templeton & Western Asset Research Hub

Current research indicates that while central banks and major institutions are increasingly integrating artificial intelligence, implementation remains concentrated in low-risk operational areas such as report generation and anomaly detection. Despite the rapid advancement of AI tools, core portfolio management decisions continue to be human-driven to ensure accountability and control. Institutions, including the Federal Reserve and the Reserve Bank of India, are prioritizing strict data guardrails to mitigate risks to sensitive financial information. However, the emergence of AI-driven market behaviors, particularly algorithmic herding and sophisticated cyber-vulnerabilities linked to models like Anthropic's Mythos, poses structural challenges to market integrity. These findings underscore a cautious approach where technological efficiency is balanced against the preservation of orderly, deep market functionality essential for reserve asset management.