Regulatory Change Reaches the Front Office: Lessons from a Recent ISC Forum

Orbit recently joined a regulatory forum hosted by Investment Solutions Consultants (ISC), sitting alongside investment managers working through how artificial intelligence is changing their regulatory work. Orbit is an award-winning AI investment research platform, and these are conversations that matter deeply to us at Orbit, so we listened closely. One pattern ran through the discussion. Regulatory change increasingly lands on the desks of the people who make investment and product decisions every day, and AI has become the first tool they reach for. The room was candid about where that works and where it quietly falls short.

A few themes stood out, and each points back to the same lesson about putting AI to work in a regulated setting.

AI inherits the quality of the data beneath it

The theme attendees returned to most was data. An AI tool can only be as good as the data it can reach and the structure of that data. Where the underlying records are inconsistent or poorly governed, AI carries those weaknesses into every answer it produces. It amplifies the state of the data it is given. For regulated work, where an output might inform a fund launch or a governance review, that has real consequences.

Consider a team asking an AI assistant to compare disclosures across a set of funds. If the source documents are stored inconsistently and the metadata is patchy, the assistant returns an answer that looks complete while hiding the gaps. Checking that answer then costs more than doing the work by hand.

This is the part of the problem that gets the least attention and decides the most. A foundation of well organized, machine-readable data is the precondition for AI that teams can trust. Orbit was designed as an AI-native platform for exactly this reason. The data layer underneath Orbit Insight is structured and machine-readable from the point of ingestion, which is what allows the AI built on top of it to produce answers a professional can stand behind.

General assistants hit a wall on regulatory documents

Attendees were clear about the limits of general purpose tools. Broad assistants handle simple drafting and summarizing well, and almost everyone in the room used them. The harder tasks were where they faltered. Interpreting the FCA Handbook and analyzing dense fund and regulatory documents came up as two consistent weak spots.

The reasons are practical. The sources that matter often sit behind firewalls or login walls that a general tool cannot reach. Regulatory documents arrive in formats that confuse standard extraction. And a general model has no reliable grounding in the specific rulebook a firm needs to follow, so its confident answers can miss the detail that counts.

RegAware was built for this gap. It pairs ISC's regulatory expertise with Orbit's AI to read regulatory documents across 47 jurisdictions, processing more than 5,000 of them each month. It turns dense regulatory text into structured updates a firm can act on, filtered down to the rules that actually apply to its business.

Outputs experts can verify

A concern about black boxes surfaced repeatedly. Prompt based tools give a quick read on a topic, and the detail often fails the scrutiny of an expert, so every output still needs expert review. The group talked about what makes AI output trustworthy: grounding answers in real sources, designing checks against hallucination, and keeping a human in the loop on anything that carries regulatory or legal weight.

RegAware is built around that principle. It produces summary reports of the updates that matter, a regulatory timeline showing what is coming and when, and change alerts when something new appears. Each output is configured to a firm's products, locations, and legal structures, so a reviewer sees relevant material traced back to its source. Analysts spend their time on judgment, with the collection and first pass of analysis handled for them.

From admin efficiency to regulated workflows

There was honest reflection on how far AI has actually reached inside these firms. It saves real time on administrative work such as note taking and preparing board and committee papers. The workflows that carry genuine regulatory weight, like fund and share class launches and governance reviews such as Assessment of Value, have seen far less adoption. One reason raised was simple. Teams are stretched thin, with little room to step back and rethink how the work could be done.

Agentic AI changes the math here, and it suits workflows that have clearly defined steps and outcomes. Regulatory change monitoring is a strong example, because the inputs and the decisions follow a repeatable pattern. This is where the platform matters. With Orbit Agent Builder, a team can stand up agents for repeatable regulatory and research workflows without writing code, and Orbit MCP acts as the distribution layer that connects Orbit's data and agents into the tools a firm already uses. RegAware then works as one agent inside a wider operating model, connected to the research and decision workflows around it.

What the front and mid office can take from this

The firms getting value from AI share a pattern. They begin with well organized data and choose tooling built for the specific job. Above all, they keep their experts close to the output, reviewing what the system produces rather than trusting it blindly. For front and mid office teams, getting this right turns regulatory change from background noise into an early signal they can act on, ahead of the firms still treating it as a back office task.

These are conversations that matter deeply to us at Orbit, and RegAware is how we help investment managers stay ahead of them.