Only 30% of financial companies use AI for customer retention

The PYMNTS Intelligence report, “Financial Services Advances in the Enterprise AI Race,” is based on a survey of 60 senior technology executives at U.S. companies with more than $1 billion in annual revenue. It found that financial services, healthcare, and media companies are all using AI across their core business functions. The difference is where users are using it, what they expect from it, and what remains an obstacle.

The headline finding is that financial services is expanding AI in more tasks than healthcare or media. But the more telling story is that each area is still unresolved. AI is pervasive, but the next stage is likely to rely more on data, systems, and management discipline than on models.

Some of the findings include:

• Financial companies were spending, but customer growth was slow. Financial services and insurance companies are the most aggressive spenders on AI, with 85% planning to increase their AI budget over the next 12 months. The strongest investment case is productivity and competitiveness, each cited by 65% ​​of these companies.

• For lower use cases, we saw gaps in customer demographics. Just 30% of financial institutions used AI for churn prediction and retention targeting, 20% used AI for customer understanding/business understanding and identity verification, and only 10% used it for A/B testing and experimentation. The sector has leveraged AI deeply for revenue, risk, and prediction, but without much impact on customer growth or experience.

• The healthcare industry was using AI to rescue, not reinvent. The top AI use cases in healthcare were customer service chatbots and virtual agents at 60%. Workforce planning and model risk management follow at 55%. This pattern shows that some sectors are using AI to reduce operational pressures and have not yet redesigned the patient or customer journey. Only 5% of healthcare companies are using AI for customer journey orchestration, and only 30% are using AI to monitor regulatory compliance. This is noteworthy because healthcare is highly regulated and operationally complex.

• Media is strong in audience signals, but weak in experiential infrastructure. Media and advertising companies lead in audience retention, with 55% using AI for churn prediction and retention targeting. It also had high adoption rates for content and operational tasks, including 60% for quality assurance and call analytics.

• Only 10% of media companies use AI for user experience personalization and adaptive interfaces, the lowest percentage in the survey. This suggests that while media companies are using AI to understand and protect their audiences, there is still a lack of investment in systems that personalize viewer experiences in real time.

Some research shows why progress in AI has been uneven. 30% of financial services companies cite data quality and fragmentation as their top barrier. Healthcare companies cited systems integration and data quality at 30% each. Media companies didn’t have one major inhibiting factor. Instead, they cited internal skills, governance, leadership alignment, and integration as separate constraints.

In general, companies have agreed on where AI should go. Across all three sectors, 80% to 85% of leaders say their five-year vision is for AI to help people make decisions, not to replace them. To get there, different sectors will require different modifications. Financial services need cleaner data. Healthcare requires connected systems. The media needs stronger organizational coordination. Adopting AI is no longer difficult. It also scales well.

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