Is AI in finance operations widely adopted yet? Or is it only something finance teams are tiptoeing around, not sure where to start? And what value does it bring to accounts payable?
To find out, we surveyed CFOs and finance leaders across the US and dug into our own product data from Rillion’s AP automation platform.
Here’s what we know about AI in finance so far.
Key takeaways
- A majority of finance teams are yet to implement AI in their operations. Nearly 40% have adopted AI to some extent while nearly a third don’t see a need for it at all.
- Almost 50% of the finance leaders from the survey are implementing AI in their finance processes this year.
- The biggest obstacle to implementing AI is budget constraints, according to nearly a third of the respondents.
- AI in accounts payable has the potential to double the level of automation and deliver over 90% accuracy.
The use of AI in finance operations
In many ways, the finance function is the ideal use case for AI. Finance teams can use AI for invoice processing, fraud detection, financial planning, cash flow management, and more.
Thanks to AI’s ability to process large amounts of information, finance teams can get accurate data in seconds. It removes routine tasks and the need to manually handle complex processes, improving both efficiency and quality.
Let’s look at how common AI is in finance operations today, what the plans for 2025 look like, and what’s holding teams back from fully embracing AI.
Are finance departments already using AI in their operations?
We asked finance leaders “Do you currently use AI technologies in any of your finance operations processes?”. Here's what they said:
- Yes, but only in a few specific cases: 28%
- No, and we have no current plans to use AI: 26%
- No, but we’re exploring the potential use of AI: 25%
- No, but we’re in the process of implementing AI solutions: 13%
- Yes, extensively across multiple processes: 8%
The responses were fairly close.
A total of 36% of respondents are ahead of the curve and are already leveraging AI, while 13% are about to implement it.
25% are exploring the potential and possible use cases and 26% don’t have any plans on using it at all.
Takeaway
Using AI in finance is still not the norm. But it looks like we’re slowly starting to see a shift.
We can see that there’s an interest in exploring the potential of AI and some are implementing it as we speak.
The only question is how long it will take before the skeptics soften up — not if.
Emil Fleron, Lead AI Engineer at Rillion, says:
“Because financial workflows are typically well-defined and repetitive, they’re highly suitable for automation. And when those automated processes still require significant time and human oversight to manage, they become strong candidates for AI enhancement.”
Are finance teams considering adopting AI this year?
We wanted to know if finance teams are expanding their AI usage this year and if not, what the reasons are.
- Yes, we are evaluating options and solutions: 36%
- No, but we may consider it in the future: 30%
- No, we don’t see a need for AI in our processes: 12%
- No, due to budget or resource constraints: 11%
- Yes, we already have a roadmap in place for AI adoption: 11%
47% answered that they have a clear plan in place or that they are looking into options to implement it this year. 11% might want to implement AI but are held back by budget or resource constraints.
30% are just not there yet but haven’t shut the door to AI entirely, while 12% don’t see a need for it. Period.
Takeaway
Overall, it looks like AI is entering more finance departments this year.
But let’s linger a bit on why some finance teams don’t see a need for AI in their processes. Is it because of a lack of education on how AI can support their processes and financial management?
Or — to look at it from another angle — could it be that finance teams are naturally more risk-aware? And therefore slower to adopt new technologies?
At this point, we can only speculate. But it will be interesting to see if they stick to their answer in a few years' time.
For finance teams that want to start using AI but are unsure where to begin, our Lead AI Engineer Emil has some advice:
“It’s generally easier to begin with AI implementations that support existing processes, allowing staff to validate and adjust AI-generated outputs. This approach combines the efficiency of AI with the nuance and oversight of human expertise.”
What’s the obstacle to implementing AI in finance departments?
We wanted to dig deeper into what’s holding finance teams back when it comes to implementing AI. Here’s what they said:
- Budget constraints: 29%
- Integration challenges: 28%
- Lack of technical skills: 15%
- Resistance to change: 14%
- Data security concerns: 11%
- Difficulty in proving ROI to leadership: 2%
The clear winners were budget constraints and integration challenges. Followed by 15% who stated that the biggest obstacle was a lack of technical skills.
Takeaway
It’s not surprising that nearly a third of finance teams are held back by budget constraints, considering the tough economic climate.
Adopting AI can also be a challenge when you’re stuck with legacy systems. Ideally, AI should boost your existing workflows — not replace them — by integrating natively with your current finance tools. It’s only natural to be hesitant to adopt a new technology if it means replacing your systems.
Emil comments:
“It’s not surprising that finance leaders struggle with integration challenges. Financial processes are often distributed across multiple independent systems, which makes AI and automation more difficult to implement.”
AI in accounts payable
AI in accounts payable automates tasks like invoice processing, PO matching, data capture, fraud detection, and cost and trend analysis. It can also provide instant answers to user questions and AP data. No wonder AI frees up a lot of time for AP teams and improves accuracy to drive cost savings.
When looking at data from Rillion AI, built into Rillion’s AP automation platform, it’s clear that AI can help finance teams achieve great results in their AP processes.
Let’s take a closer look.
What’s the impact of using AI in account coding and approval workflows?
AI in accounts payable is on the rise. Over the last six months, we’ve seen a 37% increase in customers using AI in their coding and workflows. And the number of predictions has doubled.
But what’s the impact?
Customers using AI to predict account coding and workflow achieve up to 90% touchless process. To put it into perspective, customers who haven’t adopted AI experience on average 40–45% touchless processing. In other words, using AI typically doubles your automation.
Customers are currently experiencing up to 90% accurate AI predictions, and in some cases, even higher. The accuracy in the AI generated predictions depends on how many invoices it processes and how repetitive they are. AI is looking for patterns, so the more repetitive the invoices are, the better results it can generate.
Takeaway
The results speak for themselves. AP teams that use AI reach twice as high automation, leading to significant time savings and a much more accurate process. Without having to fix errors.
Another major benefit is that AI eliminates the need to manage rules and templates, which is a huge relief for AP teams.
As efficiency goes up, the cost per invoice goes down. And with AI, you’re not compromising on quality — you’re enhancing it.
That means your AP team can spend more time on tasks that actually add value to your business. Such as analyzing AP data to improve cash flow, optimizing vendor performance, and supporting smarter financial decisions.
Emil says:
“Human error is common and often overlooked as a risk in finance. AI can act as a second layer of control to catch and reduce mistakes, especially in accounts payable.”
Final thoughts
AI is no longer a distant concept for finance — it's here, and it's starting to make a real difference. While adoption is still uneven, many finance teams are actively exploring or implementing AI to improve efficiency, accuracy, and decision-making.
The biggest roadblocks? Budget, integration challenges, and in some cases, hesitation to embrace new ways of working.
But the results speak clearly. Teams using AI in accounts payable are seeing major gains in automation and accuracy — saving time, reducing errors, and freeing up capacity for more strategic work.
The shift is happening. Slowly, but surely.
The question is: Will your team be ahead of the curve — or playing catch-up a year from now?
What’s The Finance Lab?
The Finance Lab by Rillion is your go-to source for finance automation insights. Each month, we deliver bite-sized reports designed for CFOs and finance leaders, packed with the latest trends in finance and accounts payable automation.
Our insights are backed by real-world data from Rillion’s platform and anonymous surveys of finance leaders across the US and EMEA.
