Breaking the AP Automation Ceiling with AI Agents
For over a decade, GBS and finance leaders have chased the “touchless” dream in document processing. Yet, as we enter 2026, a stark reality has set in: traditional automation has plateaued.
The numbers are revealing. While over 90% of AP teams have digitized their processes, over half of them remain stuck at “medium” levels (over 25-50% automated) and 30% stay below 25%, according to the SSON Research & Analytics report.
Defining AP Automation Rates: Real-World Challenges and The Future of Automation. Join us to learn how real enterprise leaders are shattering the ceiling.
Why traditional automation hits a ceiling
Traditional OCRs and RPA reach a limit where adding more rules doesn’t increase efficiency; it only increases the burden of managing them. When exceptions and coding must be handled manually, the only solution to a growing volume is hiring more staff.
While 52% of leaders (according to the SSON Research & Analytics report) want to pivot to core business support, high-value talent remains trapped matching PO lines and searching for GL codes. To break through, leaders are turning to agentic AI – virtual colleagues that reason with data and act autonomously based on your SOPs. According to the Current State of AI in Finance 2025 report from Gartner, moving AI-powered AP automation into production achieves 8x the impact in cost savings and efficiency compared to the pilot phase. With 80-85% of automated processing a realistic goal if leveraged well. Don’t just take my word for it, read the report by World Journal of Advanced Research and Reviews.
The Rossum solution: empowering finance leaders with AI agents
Rossum moves beyond simple data capture to autonomous decision-making, allowing GBS managers to take full ownership of their operations. By delegating manual hurdles to AI agents, your team moves from basic oversight to active orchestration of a digital workforce.
1. The AI data capture engine
Our platform is powered by Aurora, a proprietary Transactional Large Language Model (T-LLM) trained on the largest dataset on the market. Aurora provides the high-accuracy data capture foundation for automating the entire document lifecycle, from initial sorting to final posting.
- Zero-template learning: Our AI understands 276+ languages and any complex layout instantly. It reads documents contextually eliminating the need to build or maintain templates for new vendors.
- Human-in-the-loop feedback: The system learns from human corrections. If a user fixes a field once, the AI remembers that context and applies it to the next document, driving a continuous increase in accuracy.
2. The digital workforce of AI agents
Rossum combines this engine with a digital workforce of AI agents that work in a strict alignment with your standard operating procedures, like a senior AP specialist would.
- Calculate and enrich data: Agents use Formula Fields for complex calculations and Reasoning Fields to enrich data. They can normalize data points, code invoices, or add missing data to ensure information is comprehensive before it reaches your ERP.
- Autonomous workflow management: Using Rules & Actions, agents dynamically adapt to your business logic: automatically assigning invoices to specific queues, flagging high-value documents, sending Slack/Teams notifications, or preventing exports when critical data like “Invoice Date” is invalid. They help your team automate the process and handle exceptions faster.
- Autonomous communication: Agents can use natural language to email suppliers, resolving discrepancies without a human ever opening an inbox.
Meet the ceiling breakers: 3 new ways to master your process
To move you from basic extraction to complete process mastery, we are introducing three powerful new capabilities designed to eliminate the final manual hurdles in your workflow.
Data Matching Agent
While Rossum has always offered data matching, our new agentic approach empowers business users to take the wheel, autonomously reconciling invoices against purchase orders and master data.
- Plain-language logic: Configure and refine matching rules in natural language. Test new logic instantly without waiting for IT or developer support.
- Intelligent fuzzy matching: The agent uses reasoning to resolve variations in vendor names or line-item descriptions that typically trigger manual exceptions.
- Self-learning logic: As the agent observes how you resolve discrepancies, it absorbs your specific business logic to steadily increase touchless rates.
Conversational Insights
We are transforming AP analytics from static reporting into a real-time conversation. While traditional dashboards show you what happened, Conversational Insights helps you understand why – no data science degree required.
- Identify bottlenecks instantly: Ask natural language questions like “Which five vendors had the most exceptions last month?” for immediate answers.
- Uncover root causes: Identify exactly which process steps are creating your automation ceiling and take action.
- Built dashboards: Effortlessly create reports and combine them into personalized dashboards.
Automation Assistant
We are giving business users the power to reach their desired automation rate. As 45% of organizations plan to replace manual captive activities with agentic AI within three years (according to the SSON Research & Analytics report), the Automation Assistant provides the necessary control to stay ahead.
- Analyze your optimal levels: View the precise automation and precision rates you can reach based on your current data.
- Set up with ease: Easily configure to hit your target without needing technical support. The assistant provides a clear path to your desired state.
- Maintain precision: Set exact thresholds on a specific field level to ensure only validated data enters your ERP.
Beyond the plateau: The real impact of AI agents
We’re already seeing this shift in action across Rossum’s global customer base:
- Trust: Achieved an 80% automation rate in their first month with 95% data extraction accuracy, reducing processing time for complex medical invoices to seconds.
- Fugro: Scaled their global AP program to a 70% average automation rate, with high-performing regions consistently exceeding 85%.
- Veolia: Reduced manual workload by 90% and hit a 90% automation rate, with a clear roadmap to reach 98% through advanced AI orchestration.
Ready to shatter the automation ceiling?
The automation ceiling is no longer a fixed limit; it’s a choice. By delegating manual exceptions to AI agents, you reclaim your team’s capacity for the strategic work 2026 demands. Ready to see the “ceiling breakers” in action? Join us on March 3rd for our upcoming webinar: Defining AP Automation Rates: Real-World Challenges and The Future of Automation.
Sources
- Rossum | Document Automation Trends 2026 Report
https://rossum.ai/document-automation-trends/ - SSON Research & Analytics | State of the Shared Services & Outsourcing Industry 2026
https://www.sson-analytics.com/shared-services-gbs-best-practices/reports/state-of-the-shared-services-outsourcing-industry-global-market-report-2026-2 - World Journal of Advanced Research and Reviews (WJARR), 2025 | AI-enhanced OCR for financial document processing: Advancing recognition accuracy in modern enterprise finance
https://doi.org/10.30574/wjarr.2025.26.2.1653 - Gartner | Current State of AI in Finance 2025 Report https://www.gartner.com/en/newsroom/press-releases/2025-11-18-gartner-survey-shows-finance-ai-adoption-remains-steady-in-2025