The power of RPA with AI: automate, understand and decide
You can automate tasks. But what if, beyond executing, automations could interpret data, identify patterns, and make context-based decisions?
This is the leap companies are experiencing with the integration of RPA (Robotic Process Automation) and artificial intelligence, the so-called intelligent automation. And believe me: if your company is still treating RPA only as a repetitive task executor, you’re already falling behind.
According to McKinsey, intelligent automation can reduce operating costs by up to 30% and accelerate critical decisions with up to 80% fewer errors. Deloitte reinforces that RPA with AI allows companies to “automate unstructured processes once considered impossible,” such as analyzing emails, scanned documents, and natural language conversations.
From doing to thinking: what changes with AI embedded in RPA
The difference between traditional RPA and RPA with AI is simple: one executes commands, the other learns and interprets. This happens through integration with technologies such as:
- Machine learning
Able to learn from historical data and adapt rules based on patterns. Ideal for behavior prediction, fraud detection, credit recommendations, or accurate document classification. - OCR (Optical Character Recognition)
Converts scanned documents, PDFs, and images into searchable, usable text. Essential for companies still dealing with paper-based processes: contracts, invoices, receipts. - NLP (Natural Language Processing)
Allows RPA to read, understand, and classify messages, emails, chats, and feedback, turning human language into structured data. We’ve implemented such solutions for automating email triage and contract analysis. - Generative models
The newest (and most powerful) layer of the equation. Using models like GPT and others, RPA can now summarize reports, write automated responses, fill fields with natural language, and even make decisions based on multiple unstructured data sources.
Where to apply intelligent automation in practice
The benefits are visible across multiple areas. Here are some real-world applications we’ve delivered or that leading innovative companies are already adopting:
- Finance: Bots that read invoices via OCR, perform bank reconciliation with machine learning, and prepare explanatory reports with generative AI.
- Legal: Automated contract reading, clause extraction, and risk analysis with NLP and ML.
- Customer Service: Ticket triage based on content, prioritization by sentiment, and initial automated responses via AI.
- HR: Resume analysis, profile classification, and personalized email responses for each candidate—fully automated.
- Logistics: Bots that track deliveries, interpret real-time status updates, and send alerts with route rescheduling suggestions.
RPA + AI ≠ magic. It’s solution engineering.
There is no intelligent automation without well-planned architecture, API integration, and clear process modeling. At Verzel, we treat each project as decision engineering, focusing on agile delivery, data security, and maximum scalability.
We work with technologies like AWS Textract, Azure Cognitive Services, OpenAI, HuggingFace, and low-code RPA tools to ensure the robot not only “does” but thinks, decides, and learns.
The future of RPA has already begun
Automation is no longer just an efficiency tool, it’s now cognitive infrastructure for companies that want to scale intelligently.
RPA with AI takes you from simple execution into the realm of analysis, adaptation, and automated decision-making.
If your company needs to handle large volumes of information, make rapid decisions, and maintain quality at scale, intelligent RPA is your new foundation.
At Verzel, we’re building this future today. And you? Let’s design an automation architecture that understands, learns, and decides with you.
Sources:
Mckinsey: “The next generation of automation: intelligent automation”
Deloitte: “Intelligent Automation: A new era of automation in business”