The Bangko Sentral ng Pilipinas says the country’s capital markets are not yet ready to use artificial intelligence for trading, investment advice or market predictions. Mark Anthony Perez, a technology and digital-innovation adviser at the central bank, said investors remain hesitant when new systems are unfamiliar. His assessment highlights a gap between public enthusiasm for consumer AI and the higher trust, transparency and accountability required when algorithms influence financial decisions. It is an assessment of readiness, not a ban on financial institutions testing or researching AI applications.
Perez said AI adoption in capital markets is still limited worldwide and that earlier robo-adviser products did not gain broad traction. He characterized algorithmic trading and market prediction as more complicated than retail use cases because the systems must respond to market movements and investor expectations. The issue is not simply whether a model can generate an answer. Firms also need to explain how it works, manage errors, protect customers and decide when a human should override an automated recommendation or transaction.
The BSP adviser also warned about AI asymmetry and third-party dependence. Philippine organizations may use models, cloud services and platforms developed abroad, but that convenience can create risks involving cost, regulation, infrastructure, skills and local data. Perez linked the discussion to AI sovereignty, arguing that building more domestic capability requires trained people and supporting systems. That can affect resilience when providers change prices, policies or access conditions. He also said institutions should consider the environmental, social and governance impact of the technologies they deploy, not only their potential efficiency gains.
For Philippine banks, brokers and investors, the message is to treat AI adoption as a readiness project rather than a race to deploy. Better governance, data quality, testing, cybersecurity and customer education will be needed before high-stakes applications become routine. The BSP comments also suggest that local institutions will have to balance the benefits of outside AI tools with the strategic risks of depending on a small number of global providers. The timeline for wider use remains uncertain as market maturity and public trust develop.
