Automation in finance is no longer just about saving costs – it’s about transforming your finance function into a strategic powerhouse. In the first episode of RegTech Talks, a webinar series by IRIS CARBON, Aakanksha Swaminathan and Medha Ganti spoke about why automation shouldn’t be conflated with AI and how the former plays a pivotal role in the world of financial reporting that runs on compliance, cost savings and correctness.
This blog is a breakdown of the webinar hosted on 11 September 2025, and in case you missed joining us live, read on to discover:
- How to embrace automation strategically through small, trust-building steps
- The real difference between automation and AI
- The areas where automation can come handy in finance
- Why most AI projects stall
- How to define an order of priority to implement automation in your business
From Manual Cars to Self-Driving Finance: The Journey of Automation
Consider this: You’ve been driving a manual car all your life.
The arch of the steering set in a mishmash of deep-seated analog meters that makes you feel in control, the gear stick that has the thrum of the engine, and the slow release of the clutch pedal that sets the car in motion. You’re used to these mechanics – the push, the release, the roar. You can probably do this in your sleep – not that you should. But that’s the power of muscle memory – it feels effortless.
But overnight, you take the leap of faith and switch to a fully automatic car. No preparation, no training, a completely impulsive upgrade – and just like that, you find yourself at the driver’s seat sans everything you associated driving with. The steering, clutch, and gear – all gone. Replaced by wide touchscreen panels, swanky buttons, and a sunroof so wide you’d wonder if the car’s roof is missing.
Embracing automation, too, can feel just as overwhelming for finance teams, especially when they’re not ready for that transition. Jumping straight from spreadsheets to AI-powered digital twins is a recipe for failure. The smarter approach is incremental: automating high-friction tasks first, building adoption, and scaling up once trust is established.
“Don’t aim for a giant leap, aim for steady, trust-building steps.”
Aakanksha Swaminathan
Functional Expert – IRIS CARBON®
Automation vs AI: Execution vs Intelligence
Automation and AI are often lumped together, but they’re not the same. Automation is all about rules and setting a logic, and the system executes it consistently every time. AI and machine learning, on the other hand, don’t just execute; they learn. They recognize patterns in data, adapt with experience, and make complex decisions. We drew a clear line between the two:
| Automation = ExecutionIt follows rules and gets repeatable tasks right every time (OCR invoice capture, PO matching, reconciliations). | AI = IntelligenceIt learns from patterns, reasons with data, and makes predictions (fraud detection, churn forecasting, anomaly spotting). |
The question finance leaders need to ask isn’t “Should we use AI?” but “Do we need efficiency, or do we need intelligence?”
Medha Ganti
Functional Expert – IRIS CARBON®
High-Impact Areas for Finance Automation
Not all finance processes are equal candidates for automation. But some areas consume so much time and effort that the payoff is impossible to ignore.
Take Accounts Payable (AP). Finance teams lose the equivalent of 65 working days a year on AP tasks alone. Even more concerning, nearly one in three finance leaders say AP directly slows down business growth. That’s not just inefficiency; it’s a drain on strategy, innovation, and the team’s ability to focus on what really drives value. Automating high-friction processes like AP isn’t about cutting costs; it’s about reclaiming time for smarter decisions.
Where Finance Is Losing Time and Focus
| Accounts Payable:72% of finance teams spend the equivalent of 520 hours per year on AP tasks. Nearly a third admit AP slows down growth. | Accounts Receivable: 67% of staff still manually key invoices into ERPs; most invoices are paid late. | Forecasting: 80% of teams take three days or more to produce a forecast. | Reporting: 2,100+ hours go into an annual report every year. Even a quarterly one eats up to 180 hours. |
We urged finance leaders to see these pain points not just as inefficiencies, but as missed opportunities. What would your team do if they got even half that time back? More analysis? Better scenario planning? Or simply more room to think strategically?
Turning Constraints into Catalysts
Finance teams often stall because automation feels overwhelming. IRIS CARBON®’s webinar introduced a scoring model to evaluate initiatives by both value drivers (time saved, error reduction, cost impact, strategic value, scalability) and implementation constraints (integration complexity, change management, user adoption).
This structured approach helps teams prioritize initiatives that deliver the fastest, most strategic wins.
Why 95% of AI Projects Fail
We didn’t sugarcoat the challenges. Most AI pilots never scale. And the reasons have little to do with technology:
- Lack of user involvement: Adoption fails if the people closest to the work aren’t part of the design and rollout.
- Unclean data: Without reliable inputs, even the smartest AI produces poor outcomes.
- Overambition: Trying to automate everything at once almost always derails progress.
Involve the people who do the work every step of the way, prioritize clean data, and scale gradually.
Aakanksha Swaminathan
Functional Expert – IRIS CARBON®
From Manual to Digital Twin: Where Are You on the Journey?
The automation journey mirrors the shift from driving a manual car to trusting a fully autonomous one:
- Driver Only (Manual): Spreadsheets, manual reconciliations, endless data prep.
- Assisted Driving: Basic workflow automation, report distribution, reminders.
- Partially Automated: Predictive forecasting, rolling models.
- Highly Automated: AI-driven recommendations, natural language queries, automated disclosure-ready reports.
- Fully Automated (Digital Twin): A connected model of your business enabling real-time what-if analysis and scenario planning.
The goal is to progress steadily, building confidence and capability along the way.
The Big Picture
Finance isn’t just a back-office function anymore. It sits at the crossroads of compliance, strategy, and business growth. And in this role, automation is essential.
As Aakanksha Swaminathan put it: “Automation in finance is not just about a tool. It is a strategic pillar for transformation.”
The challenge for finance leaders is to treat automation not as an IT upgrade, but as a CFO priority. Done right, automation frees finance from recording the past to actively shaping the future.
