AI automation software is rapidly reshaping how modern businesses operate. For finance teams, it marks a fundamental shift in how work gets done — not by layering more tools or manual steps, but by removing them entirely.

At its core, AI automation software refers to platforms that use machine learning and data-driven decisioning to handle complex tasks autonomously. Unlike traditional automation methods (think OCR or RPA) that rely on static rules or templates, AI learns from context. It adapts. It gets smarter over time. And most importantly, it delivers results at scale.

But let’s take a step back. AI might sound like a buzzword or an overly complex leap. The truth is, it’s simply the next evolution in how software is built. The same way cloud computing modernized infrastructure or mobile apps changed user interaction, AI is redefining how automation actually works — making it more intelligent, efficient, and autonomous.

How AI automation software works

AI automation software uses machine learning models that are trained on vast datasets to recognize patterns, make predictions, and automate decision-making. In finance, this could mean ingesting an invoice, recognizing the vendor and amount, accurately applying GL codes, and even flagging anomalies or approval bottlenecks — all without human input.

According to industry research, manual invoice processing costs around $12–$13 per invoice and takes over 10 minutes on average. AI-powered platforms like Vic.ai can reduce this to roughly $2 and just 1 minute of processing time. That’s an 80% reduction in cost, and over 90% time savings per invoice. 

Unlike rule-based tools, AI doesn’t follow rigid instructions. It makes contextual decisions. If a vendor changes invoice formats or a new GL code is introduced, the system adapts. It doesn’t need to be reprogrammed or retrained by a human, and no new templates need to be built. This is especially powerful in high-volume, variable environments like accounts payable (AP).

Use cases in finance and accounting

AI automation is particularly well-suited for finance functions, where the work is data-heavy, repetitive, and dependent on accuracy. Here are a few areas where AI automation can deliver measurable impact:

• Accounts payable (AP): Automating invoice intake, classification, PO matching, approval routing, and even payment execution.
  
• GL coding: Automatically applying the correct codes based on historical patterns.
  
• Anomaly detection: Flagging outliers or potential fraud based on real-time behavioral patterns.
  
• Cash flow management: Surfacing early payment discounts and optimizing timing.
  
• Spend visibility: Providing analytics on vendor trends and expense categories.
  

As Gartner noted, finance teams are rapidly closing the gap with other functions in adopting AI, with 58% of finance leaders now using AI tools and half of the rest planning to implement them soon. And, recent data from Insight found that 72% of CFOs believe adopting AI will improve employee productivity. AI adoption is already here in finance, and transformative leaders are embracing this new technology to stay ahead of the curve.

The key benefits of AI automation

The transition from manual or rules-based automation to AI-powered automation introduces a number of business-critical benefits. These are just some of the key results that Vic.ai customers have experienced:

• Increased accuracy: AI delivers superhuman precision in tasks like GL coding and invoice processing, achieving up to 97–99% accuracy.
  
• Faster processing times: With no need for manual intervention, throughput increases dramatically. Best-in-class AP departments leveraging AI report invoice processing times up to 81% faster than peers.
  
• Lower costs: AI reduces the cost per invoice by up to 80%, saving over $10 per invoice in hard costs.
  
• Real-time visibility: AI platforms can surface insights as work happens—not at month-end.
  
• System adaptability: AI learns from exceptions and doesn’t break when formats or processes shift.

For example, Vic.ai helped one leading transportation company reduce their financial close process by an entire business day, while seeing time savings equivalent to three FTEs.

AI vs. OCR, RPA, and traditional automation

To truly understand the value of AI automation, it helps to do a simple comparison to legacy tools that finance teams have relied on:

OCR

What it does: Extracts text from documents‍

Limitation: Static, doesn’t understand context

RPA

What it does: Mimics user clicks/rules ‍

Limitation: Breaks when processes change

AI

What it does: Learns and makes decisions 

Limitation: Improves over time with data

Vic.ai, for example, uses proprietary AI trained on over one billion invoices. This isn’t a bolt-on solution; rather, it’s a purpose-built, end-to-end platform that autonomously handles the end-to-end process, from invoice processing all the way through to payment.

What to look for in AI automation software

The intelligent process automation market is projected to triple by 2032, growing from $14.4 billion to over $42 billion. This signals increasing demand and investment across enterprises to adopt smarter, AI-first automation tools.

However, not all platforms claiming to have "AI" technology are purpose-built with AI in mind or offer true autonomous capabilities. When evaluating solutions, finance leaders should look for:

• Purpose-built for finance: Not a generic tool rebranded with AI
  
• Training data volume and quality: More data = better predictions
  
• Autonomous capabilities: Can it complete tasks without manual steps?
  
• ERP and payment integration: Should work with your tech stack, not around it
  
• Built-in analytics: Surface insights and trends in real time
  

Final thoughts: Smarter software, not just smarter tools

AI doesn’t need to feel complicated. It’s not about replacing people or building a futuristic finance department overnight. It’s about upgrading the software your team relies on every day.

The best platforms today don’t just automate steps — they think, learn, and act. That’s what makes AI automation so transformative. For finance teams under pressure to move faster, reduce costs, and gain better visibility, it offers a smarter, more sustainable way forward.

According to Deloitte, 81% of CFOs plan to use digital technologies like AI to free their staff for higher-value work. And, McKinsey finds that most CFOs believe AI will help finance functions move away from manual tasks and into strategic leadership roles, and are strategically rethinking finance organizations from the ground-up to embrace the hybrid model.

Want to see true AI automation in action? Take a self-guided Vic.ai product tour, or book a call with our team.