AI has become remarkably good at answering questions.
Ask why margins have changed, which entities are driving growth, or where costs are increasing, and modern AI tools can help uncover the answer in seconds.
But for finance teams, finding the answer is often just the beginning. Once the insight is identified, reports need to be built, adjustments reviewed and actions taken. The real work starts with turning information into outcomes.
Reports need building. Eliminations need reviewing. Charts of accounts need maintaining and standardising. Many of the tasks that sit behind accurate financial reporting are still repetitive, time-consuming and heavily manual.
That’s where AI agents enter the conversation.
Unlike traditional AI assistants, agents are designed to take action. They don’t just provide information. They help complete tasks, automate workflows and reduce the manual effort involved in getting work done.
For finance teams, this creates an opportunity to reduce repetitive work and focus more on analysis and decision-making. It also raises an important question: how much responsibility should AI have when financial data is involved?
The challenge with agentic AI in finance
Across the software industry, AI agents are being introduced to automate increasingly complex tasks, with a simple goal: save time and reduce manual effort.
Finance, however, operates under different expectations.
A mistake in an email draft is usually easy to fix. A mistake in financial reporting can affect management decisions, audit processes and reporting outcomes. Every adjustment needs to be understood, reviewed and traceable.
That’s why AI agents in finance can’t be judged on automation alone.
Control matters just as much.
Finance teams need visibility into what actions have been taken, why they were taken and what changed as a result. They also need confidence that changes can be reviewed and, where necessary, reversed.
Rather than getting in the way of innovation, those requirements are what make it genuinely useful in a finance environment. Without them, even the most capable AI quickly becomes difficult to trust.
Built around the way finance teams work
Joiin Intelligence recently introduced three specialist AI agents designed to help with some of the most time-consuming aspects of financial reporting.
- The Report Pack Agent can build rich, multi-page report packs from a simple description, helping teams spend less time assembling reports and more time analysing them.
- The Eliminations Agent helps manage intercompany eliminations while maintaining a clear record of every adjustment made throughout the process.
- The Chart of Accounts Agent assists with restructuring and standardising charts across multiple entities, reducing the manual effort often required to keep reporting consistent across a group.
Each agent solves a different challenge, but they all share the same philosophy.
Actions are reviewed before they’re applied. Changes remain visible and traceable. Every step is recorded, creating a clear audit trail. Where appropriate, changes can be rolled back, giving users confidence that they’re always in control.
For finance teams, that’s an important distinction.
Finance teams aren’t looking for AI to make decisions on their behalf. They want it to take care of the repetitive work, freeing them up to focus on analysis, while keeping every action visible and firmly under their control.
– Lucien Wynn, CEO and Co-founder of Joiin.
Trust is what makes AI useful
AI demonstrations often focus on capability.
- What can the technology do?
- How fast can it work?
- How much can it automate?
They’re fair questions. But they’re not the only ones that matter – when financial data is involved, trust comes first.
An AI agent only becomes useful when people understand what it’s doing and feel confident in the outcome. This matters even more across multiple entities, intercompany relationships and group reporting structures. Without visibility and control, automation can create as many questions as it solves.
The best AI removes effort, not oversight. It’s the one that helps people work faster, while staying firmly in control.
Three agents. One goal.
As AI continues to evolve, finance teams will increasingly expect software to do more than analyse data. They’ll expect it to help complete tasks, streamline workflows and reduce manual effort across the reporting process.
The organisations that benefit most won’t be the ones handing control over to AI. They’ll be the ones using AI within a framework that supports accuracy, transparency and accountability.
That’s the principle behind every Joiin Intelligence agent. It’s an approach shaped not only by the needs of finance teams, but also by the feedback our customers share, which in turn helps to guide how Joiin continues to evolve and improve.
Not because finance teams need more complexity, but because they need confidence in every action performed on their data.
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