It’s November 2025, three years on since ChatGPT was released on the 30th of November 2022. Large Language Models (LLMs) are now part of our daily lives, and there are companies harnessing LLMs and AI technology to solve problems across the board.
The world of Finance has long been earmarked for disruption. While innovations such as blockchain and RPA have taken shape, finance remains the purple elephant in the room. It’s big, it’s heavy, and it needs a makeover!
Where AI Fits in the Finance Function
The finance function is traditionally broken down into Controlling, FP&A, Treasury & Risk Management, Tax, M&A and Investor relations. We are setting aside Internal Audit for now. Each of these functions we’ve covered has workflows that include routine and judgmental tasks that rely on aspects such as subject matter knowledge, internal controls, and thresholds.
The key terms are routine and judgmental with AI in its current state, there are solutions for both sides. For routine tasks, the answer is AI/ML and RPA, for judgmental tasks, it’s AI Agents and Agentic AI. The true benefit that AI has to offer, though, is scalability.
AI/ML is better suited than humans to handle vast amounts of data and routine tasks when trained appropriately. As with any technology, a botched implementation can be worse than no implementation.
The Role of Controlling
In this article, we delve into the Controlling sub-function in depth. This is the layer in finance that is responsible for transacting, complying with regulations, and reporting results to internal and external stakeholders. In many ways, it’s the backbone of the finance function at any organisation.
Real-World Applications
Let’s look at High Radius, the FinTech Unicorn out of Houston, as an example of a company that currently serves enterprise clients with AI automation, focusing on controlling, treasury, and risk management. They have neatly taken a chunk of the purple elephant and broken it down to its constituent parts, where Agentic AI is being used today to automate the workflows. What’s impressive is sub-functions like Order to Cash have no less than 20 touch points where Agentic AI has demonstrated capabilities to automate the critical path.
Another example is that of VC-backed San Francisco startup Numeric.io, founded in 2020. The company is automating enterprise financial close processes, posting account reconciliations, and connecting natively with ERPs like NetSuite and Xero. They even have a Technical Accounting product that helps with complex accounting treatment and drafting accounting policies based on the latest in GAAP pronouncements.
A third and final example is FloQast, a cloud-based accounting transformation platform established in 2013. They now deploy AI Agents to streamline accounting and financial close on their platform, where humans get to approve transactions before they are posted.
Lessons for Finance Leaders
What these examples show is the narrow application of AI technology weaved into existing systems like ERP, CRM and other enterprise data warehouses to deliver value translated in time and costs saved in grunt work.
A Local Perspective
At Neural Ledger, a homegrown AI startup, our take on the purple elephant is to drive smart financial decision-making powered by AI, helping businesses in the UAE scale.
What’s your take on leveraging AI to drive financial value?
Written by Divesh Nair
Co-founder and CEO
Neural Ledger
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