RPA Is the Gateway to AI: Why Finance Teams Need to Start Small to Transform Big
Finance leaders hear about AI everywhere conferences, LinkedIn, boardrooms. Yet inside most finance departments, teams are drowning in day-to-day tasks: closing books, chasing invoices, fixing errors, and dealing with outdated systems. The gap between hearing about AI and actually adopting it has never been wider.
And this is exactly why Robotic Process Automation (RPA) matters.
In this blog, the core message is simple: RPA is the gateway to AI. It’s the most practical, accessible first step for finance teams to begin digital transformation without needing huge budgets, complex infrastructure, or advanced technical knowledge.
Why Finance Teams Aren’t Adopting AI Yet
Even when leaders believe in AI’s potential, they’re buried in day-to-day operational fires. They want automation. They want efficiency. But they don’t have the time, clean data, or internal bandwidth to even begin.
There’s a massive disconnect between what’s possible and what’s actually happening inside finance departments.
And that’s where RPA bridges the gap.
RPA: The First Step Toward an AI-Powered Finance Function
I describe RPA this way:
“Excel macros on steroids.”
It’s not smart like AI. It’s not learning or adapting. RPA is simple, rule-based automation copy-paste work, invoice entry, reconciliations, data transfers, and all the repetitive tasks that drain hours every week.
And that simplicity is the entire point.
You can’t jump into AI if you don’t have clean, repeatable processes.
RPA builds that foundation. It standardizes workflows. It cleans up data. It automates the busiest parts of the job so teams can finally breathe and make room for innovation.
RPA Is Still New and That’s a Big Opportunity
People often assume RPA is old or outdated.
But here’s the truth I’ve seen firsthand:
This space is still young.
New players are entering constantly.
Technology is evolving every quarter.
The ecosystem hasn’t stabilized yet which means the opportunities for early adopters are huge.
Even better?
Many RPA companies are so eager to prove themselves that they’ll run free pilots just to showcase what they can do.
Finance Teams Can Experiment for Free
If you’re a finance leader curious about automation, but worried about the cost — this is your window.
There are RPA firms willing to:
Run proofs of concept
Test your processes
Build workflows
Show real results
without charging anything upfront.
And they’ll do it as long as you provide clean data.
If you want to automate invoice processing, then give them invoices.
If you want to automate transaction matching, share those files.
Clean data + an eager RPA partner = instant clarity on what’s possible.
Why Starting Small Matters More Than Thinking Big
Finance teams aren’t avoiding AI because they lack vision.
They’re avoiding it because they’re overwhelmed.
When you’re firefighting every day, innovation becomes a luxury.
That’s why transformation doesn’t begin with a massive AI overhaul. It begins with the smallest possible automation, the one that frees up one hour, then five, then fifty.
RPA is the first domino.
Once it falls, everything else becomes easier.
Final Takeaway: RPA Isn’t the Destination, It’s the Launchpad
AI will reshape the finance function. But most teams aren’t ready yet and that’s completely fine.
RPA gives them a low-barrier, low-risk starting point that builds momentum, strengthens processes, and cleans up data all the things required for AI success.
Start small. Automate a single process. Learn from it. Build on it.
That’s how real transformation happens not in theory, but in practice.
Frequently Asked Questions
Q1. Why is RPA a good starting point on the journey to AI?
RPA helps finance teams clean, structure, and standardize their data by automating repetitive tasks. This creates the foundation AI needs to work effectively. By starting with RPA, teams get quick wins, free up time, and prepare their systems for more advanced AI tools later.
Q2. What is the difference between RPA and AI in finance?
RPA follows fixed rules to automate repetitive tasks like data entry or invoice matching. It doesn’t learn or make decisions. AI analyzes patterns, learns from data, and handles complex judgment-based work. In finance, RPA boosts efficiency, while AI brings intelligence and deeper insights.
Q3. How is RPA used in finance?
RPA automates routine processes like invoice entry, account reconciliations, payroll updates, generating reports, and sending payment reminders. It reduces manual work, cuts errors, and speeds up operations. This allows finance teams to focus on analysis and strategic decision-making.
Q4. Can RPA be replaced by AI?
AI won’t fully replace RPA because they solve different problems. RPA handles rule-based, repetitive tasks, while AI manages judgment-based, learning-driven tasks. When combined, AI enhances RPA by adding intelligence, making automated workflows smarter and more efficient.
Q5. What are the benefits of using RPA?
RPA saves time, reduces errors, speeds up financial processes, and increases accuracy. It helps teams handle high-volume tasks without extra staffing. It also frees employees to focus on strategic work instead of manual data tasks, improving overall productivity and efficiency.
Q6. Can finance be automated by AI?
AI can automate many finance functions like risk analysis, fraud detection, forecasting, customer communication, document processing, and compliance checks. It reduces costs, improves accuracy, and helps teams make smarter decisions by analyzing large volumes of data quickly.
About the Author:
Shawn Kanungo is a globally recognized disruption strategist and keynote speaker who helps organizations adapt to change and leverage disruptive thinking. Named one of the "Best New Speakers" by the National Speakers Bureau, Shawn has spoken at some of the world's most innovative organizations, including IBM, Walmart, and 3M. His expertise in digital disruption strategies helps leaders navigate transformation and build resilience in an increasingly uncertain business environment.