RPA vs AI Agents for ERP Automation: An Honest Comparison
Robotic Process Automation (RPA) and AI agents both promise to automate ERP tasks, but they operate on fundamentally different principles. RPA records and replays user actions—clicking buttons, filling fields, copying data between screens. AI agents understand business context, make decisions, and adapt to changing conditions. For Infor CloudSuite environments, the choice between RPA and AI agents has significant implications for maintenance burden, reliability, and the scope of tasks you can automate.
RPA: Strengths and Breaking Points
RPA excels at automating repetitive, rule-based tasks with stable UI elements. In Infor environments, RPA handles data entry, report extraction, and cross-system data transfer effectively. But RPA bots are fragile—they break when Infor updates change screen layouts, field IDs, or navigation paths. Multi-tenant CloudSuite customers receive automatic updates from Infor that frequently break RPA scripts, creating an ongoing maintenance burden that erodes ROI.
- RPA bots break on 30-40% of Infor CloudSuite updates requiring script maintenance
- Average RPA maintenance cost is 25-40% of initial development cost annually
- RPA cannot handle exceptions or variations—every edge case needs explicit programming
- Screen-scraping approach makes RPA dependent on UI elements that Infor may change anytime
AI Agents: Context-Aware Automation
AI agents interact with Infor systems through APIs and data interfaces rather than screen manipulation. They understand business rules, can make decisions within defined parameters, and adapt to data variations without explicit programming. When Infor updates change the UI, AI agents continue operating because they communicate through stable API endpoints. The trade-off is that AI agents require more initial setup and domain knowledge to configure.
- API-based integration survives UI updates without modification in 95%+ of cases
- AI agents handle exceptions by applying business rules rather than failing and alerting
- Decision-making capability enables automation of judgment-based tasks like approval routing
- Self-learning agents improve accuracy over time by learning from correction patterns
The Netray Approach
Netray's AI agents are purpose-built for Infor CloudSuite environments. They combine deep ERP domain knowledge with API-first integration and contextual decision-making. Unlike generic RPA or general-purpose AI, Netray agents understand SyteLine transactions, LN business logic, and M3 data structures natively—resulting in faster deployment and higher reliability than either traditional approach alone.
See the difference AI agents make vs RPA—request a side-by-side automation comparison.
Related Resources
ERP AI Agents vs RPA: Which Is Right for You?
Compare AI agents and RPA for ERP automation. Understand when each approach works best and why manufacturers are moving beyond traditional RPA.
AI & AutomationAI Agents for ERP: The Complete Guide
Everything you need to know about AI agents for ERP systems. How they work, ROI expectations, implementation approaches, and real-world results.
AI & AutomationInfor Coleman AI: Capabilities and Implementation Guide
Explore Infor Coleman AI capabilities for manufacturing. Demand forecasting, anomaly detection, chatbot, and custom ML model deployment guide.