Artificial Intelligence Applications in Regulated Industries
Yolandi de Weerdt and Shri Nandan discussed the processes of scaling artificial intelligence in regulated sectors such as banking and healthcare.
In a conversation with Comcast Vice President Shri Nandan, Yolandi de Weerdt from Emerj discussed how artificial intelligence can be scaled within the framework of governance, clean data, and human boundaries in strictly regulated sectors such as banking, insurance, and healthcare.
Artificial Intelligence in Customer Service
Customer service is among the first areas where banks, insurers, and healthcare organizations position artificial intelligence directly in front of customers, according to the U.S. Government Accountability Office.
In financial services, all of the country's ten largest commercial banks use chatbots for customer interactions, and according to Consumer Financial Protection Bureau data, more than 98 million U.S. consumers interacted with these systems in 2022.
Adoption Rates in the Healthcare Sector
There is a distinct duality between the adoption trend and the level of institutional readiness in the healthcare sector, with artificial intelligence technologies being actively used in a significant portion of hospitals.
According to data from the Office of the National Coordinator for Health Information Technology, 71% of hospitals in the U.S. use predictive artificial intelligence, while the proportion of those using this technology for appointment scheduling increased from 51% to 67% in one year.
Governance and Oversight Challenges
Regulatory and oversight mechanisms can occasionally struggle to keep pace with the rapid adoption trend of artificial intelligence across industries.
The Government Accountability Office concluded that the federal agency responsible for overseeing credit unions lacks some of the tools required to audit artificial intelligence usage.
Limits for Critical Interactions
Before artificial intelligence agents are deployed in clinically, financially, or legally sensitive customer journeys, it must be clearly defined which problems they can autonomously solve.
High-risk interactions must be safeguarded by pre-determining when to transition to human intervention in situations where autonomous systems fall short.
Unified Data for Reliable Context
For artificial intelligence to offer consistent personalization across different business units, standards for corporate ownership and currency must first be established.
It is of great importance to create unified enterprise data around a single shared customer record in order for systems to build a reliable context.
Scalable Centralized Governance
For artificial intelligence strategies to scale successfully, a strong data structure must be executed hand-in-hand with controlled experimentation processes.
Through a centralized governance approach and clear decision-making authority, successful use cases can be expanded without increasing institutional risk.