Banking and financial services companies foresee AI-assisted decision-making and real-time fraud prevention becoming common in the near future, as early adopters move beyond experimentation to operational deployment, according to the ET- Cisco AI Readiness & Adoption survey for the BFSI sector.
Meanwhile, the broader BFSI industry’s enterprise readiness is under the spotlight, even as companies plan to scale up AI deployment. Before large-scale adoption, companies need to address key challenges around AI governance, infrastructure and data security.
“The biggest barrier to moving from experimentation to production is not technology readiness, but enterprise readiness,” said Ashish Mittal, Chief Technology Officer at Tata AIG General Insurance. Implementation is often slowed by fragmented data, weak governance frameworks, integration challenges with legacy infrastructure. and difficulties in scaling pilots sustainably, Mittal said.
AI moves to the core
Industry experts say the BFSI sector has already moved beyond the first phase of AI adoption focused on chatbots and customer servicing. “AI in BFSI is no longer just customer-facing experimentation. It has already moved into core operations,” said Anand Mihir, Partner and Financial Services Consulting Leader (Domestic) at EY.
Mihir highlighted customer onboarding, collections, enterprise knowledge management, sales copilots, audit review, and policy compliance work, among others, where companies are deploying AI in the sector. “Fraud and anti-money laundering have used machine learning for years,” he said.
