Financial services' early adopters of AI report mixed returns

While customer onboarding and risk detection are the primary uses of AI cited by 29% of respondents, data management and customer insights are the most common use cases. "Data is becoming ever more important as organizations increasingly digitize," said Vishal Marria, CEO and founder of Quantexa (which conducted the survey). "However, these huge waves of data often lead to decision gaps that plague organizations, leaving them unable to extract meaningful value. AI and technological advances such as entity resolution are helping close this data decision gap in a strategic and measured way, allowing organizations to connect siloed data to create a meaningful connected view, that directly leads to higher accuracy, productivity and ultimately trusted decision making." Data readiness, integrating internal/external data sources (15%), making AI operational (14%) and the availability of skills (14%) are reported as the biggest challenges in adopting AI in financial services firms.