“Same Direction, Different Roads: How Financial Services, Media & Advertising, and Healthcare Are Navigating Enterprise AI, Together and Apart,” is a PYMNTS Intelligence report based on a March 2026 survey of 60 senior technology executives at U.S. enterprises with at least $1 billion in annual revenue. The research compares artificial intelligence adoption across financial services and insurance, healthcare, and media and advertising. All three sectors are expanding AI use, but financial services have gone furthest, reaching high adoption on 27 of 75 AI-supported tasks, compared with 16 in media and advertising and 10 in healthcare. That’s 26 combined for the other two sectors, one fewer than financial services alone.

The financial services story isn’t that banks, insurers and related firms are using artificial intelligence everywhere. It’s that they’re using it most heavily where the business case is clearest: revenue, risk, compliance and forecasting. Those are areas where financial institutions already have structured processes, documented workflows and established governance, conditions that make AI easier to deploy and easier to trust.

Key financial services findings from the report include:

• 65% of financial services and insurance firms use AI for revenue recognition and accounting close. That’s the highest adoption rate listed for the sector and reflects AI’s role in helping firms manage finance functions that require accuracy, consistency and speed.
• 60% use AI for credit risk assessment and scoring, and 60% use it for sales forecasting and pipeline optimization. Those use cases show how financial firms are applying AI to both sides of the operating model: protecting against bad outcomes while sharpening revenue planning.
• 85% of financial services and insurance firms are increasing AI budgets over the next 12 months. The top justifications are productivity and efficiency gains, cited by 65%, and strategic or competitive positioning, also cited by 65%.

The report also points to where growth is still coming. Adoption lags in customer-facing areas: churn prediction and retention targeting sits at 30%, know your customer (KYC) and know your business (KYB) and identity verification at 20%, and A/B testing at just 10%. Those numbers show AI has gained the most traction where rules and controls are already well established, and that expanding into customer experience and product work will require a different approach. That’s where the sector’s next phase of deployment is likely to take shape.

The main barrier isn’t budget or executive support. Thirty percent of financial services executives cite data quality and fragmentation as their biggest organizational challenge, the highest single barrier in the sector. In practical terms, fragmented data limits how far AI can move beyond structured back-office tasks into broader decisioning and customer work. Financial firms appear to have the resources and the will to close that gap, and the ones that do it first are likely to extend their lead.

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