Globally, IDC projects over $109.6 billion USD will be spent on AI use cases among financial services organizations in 2026. With a three-year compound annual growth rate (CAGR) of 35.5%, the spend on AI use cases is projected to reach $272.5 billion by 2029.1
In my role as an AI technical solutions architect at Arrow, I am seeing interest across a variety of AI uses cases. While some are clearly aligned to financial services and insurance, others are vertical-agnostic and are being prioritized among the top use cases in the sector. We highlight spending and projected growth data on specific use cases below, relative to overall AI use case spending in financial services.
Let’s dig in and explore why your financial services customers may be interested in bringing some of these to reality in their own organizations.
Augmented claims processing
In the financial sector, AI spending on augmented claims processing worldwide has a CAGR of 39% from 2026 to 2029. Financial and insurance organizations are drawn to this use case, as it supports investigators and adjusters in efficiently investigating and adjudicating claims by leveraging intelligent data capture and analysis. Unlike basic chatbot implementations, augmented claims processing requires advanced expertise to integrate seamlessly into existing workflows, making it a more impactful and innovative approach.
Smart legal
The three-year CAGR of AI spending on smart legal as a use case is 37.4%. Customers trying to manage legal data need to ensure they are complying with regulations. Legal teams often grapple with extensive contracts and documentation that span years, requiring meticulous review and compliance with privacy standards, such as removing personally identifiable information (PII). AI tools streamline these processes by automating tasks like drafting, reviewing, and comparing legal documents, enabling in-house legal teams to focus on higher-value activities. Additionally, these solutions can be tailored for on-premises deployment to address concerns about data privacy and compliance, ensuring sensitive information remains secure.
The value of AI in legal operations extends beyond efficiency. By leveraging AI, organizations can implement repeatable, explainable processes, such as creating formatted templates and extracting insights from legal data. This not only reduces costs associated with expensive legal resources but also enhances accuracy and speed. With multiple vendor demos and tools available, AI-driven legal document assistants are proving to be indispensable for organizations struggling with data overload, offering scalable solutions to meet their compliance and operational needs.
Augmented fraud analysis and investigation
With a worldwide AI spending CAGR of 36.1% from 2026 to 2029, this use case is also attractive to customers in the financial sector and works similarly to claims processing. Arrow’s technical team demonstrates both use cases across various vendors on our line card. One customer example that comes to mind is an insurance company in the early stages of implementing this solution with Arrow's AI services, aiming to make it their first AI-driven initiative.
AI-enabled customer service and self-service
AI-enabled customer service and self-service, or AI tools to help enhance and operationalize customer interactions and experiences, has a three-year CAGR of 32.7% among financial services organizations worldwide. Arrow’s technical team offers many vendor demonstrations that showcase AI technologies designed to improve customer and self-service. While better customer service is not exclusively a goal among financial services customers, our team has some cool use cases to demo to you that are specific to the financial sector. In fact, we helped a customer with a loan approval agent where visitors can inquire about financial-related topics and get meaningful responses. Example prompt: My credit score is 700 and I want to borrow $50,000, what can I expect the interest to be on my loan?
The AI agent will tell you how much you can expect to spend on interest.
Arrow’s technical experts can help you with all of these use cases — or help you discover new ones. Request a meeting with our technical team or visit our AI webpage to learn more about our AI capabilities.
1Source: IDC Worldwide AI and Generative AI Spending Guide - Forecast 2026 | Mar (V1 2026)
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