---
title: "Agentic AI in Financial Services: A SoftServe Report"
description: See how financial services leaders are turning governance into the capability that helps agentic AI scale.
image: https://info.softserveinc.com/hubfs/2026/agentic-ai-financial-services-social/agentic-ai-financial-services-social.png
---

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## Governed to Go Faster: Agentic AI in Financial Services & Insurance

Financial institutions have plenty of AI pilots, but many still need to prove they can meet regulatory requirements and improve the bottom line. Our [MIT Technology Review Insights global survey of 300 senior technology leaders](https://info.softserveinc.com/future-of-software-engineering-with-agentic-ai?hsLang=uk-ua) shows financial services moving cautiously on agentic AI. Adoption trails most other industries, and 76% cite governance as a top challenge—more than twice the 37% overall. Even so, 55% plan to adopt within 6 to 12 months. This analysis explores how building governance into everyday work can help financial institutions move faster with future deployments.

Inside, you’ll find five insights:

- **Behind today, moving quickly tomorrow.** More than a third (39%) of use agentic AI today, and 55% plan to adopt within 6 to 12 months — 10 points above the all-industry figure.
- **Confident has to be earned.** Just 27% expect significant or game-changing gains, while 36% expect only slight improvement. The business case will need results in production with the audit trail attached.
- **Early wins come from checking.** Nearly half (48%) expect benefits in year one to come from testing. The same percentage expect architecture design to be the source of benefit in year three.
- **Governance sets the pace of scale.** Roughly a third (76%) cite governance as a top challenge — the highest of any industry. Institutions that develop reusable controls should move faster on every use case that follows.
- **Talent tilts toward design.** Software architect leads hiring priorities at 55%, up from 24% — the highest of any industry — while data engineers climb from 9% to 39%.

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