AI is reaching finance’s core systems: Here’s what it takes to run it there | Tech Radar

Overview

News, deals, reviews, guides and more on the newest computing gadgets

Start exploring exclusive deals, expert advice and more

Details

Unlock and manage exclusive Techradar member rewards.

Unlock instant access to exclusive member features.

Get full access to premium articles, exclusive features and a growing list of member rewards.

AI is reaching finance’s core systems: Here’s what it takes to run it there

AI is transforming finance, but legacy systems remain the biggest hurdle

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.

AI is rapidly expanding across finance, but most agentic offerings have yet to reach core production systems. Only 10% of enterprises are using AI tools in a meaningful, production-grade way. Not because of a lack of interest, but because connecting AI to core systems to trade capture, risk, and surveillance is still a work in progress.

These systems offer the greatest opportunity for AI to simplify finance operations through efficient workflows and live trading queries. Yet, legacy systems force this technology to operate in isolation. The volume of architecture connected to traditional platforms often creates this constraint.

Managing Director and Solutions Architect at 3forge.

The financial services industry has forced firms to adapt core architecture rather than replace it, preserving operations, but limiting AI compatibility. Now, the challenge is incorporating AI into these existing systems without forcing an infrastructure replacement that would cause platforms to pause or fail.

To bridge the gap between existing systems and modern demands, firms need an architectural layer to help bridge legacy access, implement a governed AI gateway, and introduce AI-native workflows within trusted guardrails. With the right foundation, firms can extend these capabilities directly into production systems and utilize the full value of AI.

Years of regulations, acquisitions, asset-class specialization, and incremental development without a shared core have created an extensive stack of internal software required to keep operations running – a stack that was never designed to support responsive, AI-driven interaction.

From experimentation to execution: where agentic AI is delivering real value

AI is reshaping the finance industry, but governance concerns remain front of mind for CFOs

Rather than rebuilding these systems, financial institutions are introducing an architectural layer that unifies access across fragmented infrastructure. This virtualized approach eliminates the need for costly rewiring while allowing organizations to consolidate access to both static and streaming data.

Instead of adding complexity, it creates a simpler path to deploying AI within existing environments.

IT teams can start this process by establishing a single abstraction layer across fragmented systems, allowing technology integration while applying entitlements at the data layer. In practice, this would allow:

Natural-language interrogation: Organization-specific data through chatbots and AI assistants.

Virtualization of systems: Abstraction of all systems behind a permission-aware access point.

Safe interaction: AI accessible touchpoints within operational infrastructures.

When organizations effectively apply abstraction layers to existing legacy architecture, AI can improve functions while interacting with internal systems through a controlled, permission-aware layer.

Abstraction layers are most effective when financial institutions apply them with gateways for AI access. When organizations apply these models together, this infrastructure creates a controlled AI interaction layer that provides a deliberate medium for producing deterministic, repeatable outputs.

How CIOs Can Implement AI with Real Financial Intelligence

Why building AI applications still means building infrastructure-first

AI agents are creating a major security blind spot in financial services

Agents can then access data exclusively through the created pathway. This architecture creates transparency and provides for the application of a consistent set of data and functional access controls.

Ultimately, it allows stakeholders to gain confidence and trust, allowing agentic solutions to migrate from an assistive layer to an operational one capable of coordinating workflows, executing logic, and interacting with live systems.

Through this channel, agents can operate within defined policies and fully log all outputs, verifying repeatability and providing compliance teams with unified oversight of operations. A single control plane can grant permissions, log events, and instantly kill defective outputs, assuaging regulatory concerns.

These capabilities allow AI to expand financial institution growth in production-ready technological environments.

Accelerating development inside trusted boundaries

Once these foundations are in place, AI development can accelerate inside trusted boundaries. By doing so, organizations can reduce code surface area and shorten audit cycles.

AI is equipped with proper boundaries for successful development.

Agents can generate layouts, workflows, and full applications.

AI can operate inside transparent and fully auditable runtimes.

Advanced coding can often power this controlled scale, offering development workflows that promote multimodal interaction, including voice, visual, and text. These capabilities further facilitate AI to fully operationalize efficient workflows across financial organizations.

However, when implementing AI adoption pathways, many organizations are now working through how to scale these capabilities consistently across systems. Financial firms facing this dilemma should follow the example of other industries.

Other industries have already solved a similar challenge of rebuilding their technology stacks much earlier in the development process. When this issue arose, they standardized their foundation across their industry, focusing on differentiated delivery rather than excessive rebuilding.

This often meant establishing application engines, a feature now used in gaming (Unity/Unreal), E-Commerce (Shopify), and general CRM (Salesforce).

If IT teams adopted these systems, purpose-built for finance, financial firms could focus primarily on delivery.

An engine could lay the foundation for virtualized legacy access, AI-governed gateways, and AI-native development within trusted guardrails, avoiding a full infrastructure replacement and establishing a safe way to integrate technology that reduces manual reconciliation.

As AI moves deeper into core financial systems, the opportunity is not just in deploying models but rethinking how software is built and operated. Application engines provide a path forward by allowing firms to integrate AI into live systems, scale workflows, and generate new functionality from human intent, all within a governed environment.

This article was produced as part of Tech Radar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of Tech Radar Pro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Managing Director and Solutions Architect at 3forge.

You must confirm your public display name before commenting

1'Music is an art of time. Time flows without form': Technics releases a burgundy turntable, ties itself in knots over a matching 1930s lamp collab, we're all confused (but secretly I love it)

2 What is the release date for Rick and Morty season 9 episode 4 on Adult Swim, HBO Max, and Hulu?

3'It doesn't benefit us': Seattle votes for year-long ban on new AI data centers

4 Logitech launches a foldable mouse for workers on the move — and it can charge up 22 hours in just a minute

5 Fake X-VPN installers found to spread credential-stealing malware — here's how to stay safe

Tech Radar is part of Future US Inc, an international media group and leading digital publisher. Visit our corporate site.

Key Takeaways

News, deals, reviews, guides and more on the newest computing gadgets
Start exploring exclusive deals, expert advice and more
Unlock and manage exclusive Techradar member rewards
Unlock instant access to exclusive member features
Get full access to premium articles, exclusive features and a growing list of member rewards