From Automation to Intelligence: RPA + AI Power

As organizations navigate the next wave of digital transformation, the convergence of Robotic Process Automation (RPA) with Artificial Intelligence (AI) is reshaping what’s possible in enterprise operations. At Microsoft Build 2025, the introduction of agents — autonomous, goal-driven AI entities — marks a pivotal moment in this evolution. What began as a solution to eliminate repetitive, rule-based tasks is now evolving into something far more transformative.

This evolution isn’t just about doing things faster; it’s about enabling smarter, adaptive processes that scale across business units. With RPA well-established in many enterprises, the integration of AI technologies like machine learning (ML), natural language processing (NLP), and computer vision is unlocking new frontiers in automation.

In this blog, we will capture some insights that were shared at a webinar hosted by Fortude recently. The webinar explored the importance of RPA and showcased real-world scenarios to highlight its success. It also outlined the benefits of automation technologies and shared practical tips on how businesses can kickstart their RPA journey with Fortude’s automation services.

What is RPA or process automation?

Robotic Process Automation is a technology that automates highly repetitive or rule-based work normally done by people. This covers invoice processing, customer inquiries, report generation as well as other tasks that can be manual and time-consuming. RPA relies on computer software robots, also known as ‘bots’, to perform human-like operations at an extremely high speed with very few errors. According to Gartner, the top advantages of using RPA tools are increased employee productivity, reduced costs, improved business continuity, and decreased IT resource requirements.

Why add AI?

AI augments RPA by introducing cognitive capabilities. Instead of following strict rules, bots can now “think”—interpreting context, learning from data, and adapting to new scenarios. Technology is utilized to ‘add smartness’ like decision-making, learning, and understanding capabilities to make processes more efficient. This combination transforms automation from a back-office utility to a core enabler of business intelligence and scale.

According to a survey conducted by Gartner, organizations are evolving their use of Artificial Intelligence as part of their automation strategies with 80% of executives thinking automation can be applied to any business decision. The combination of RPA with AI, such as Machine Learning and Natural Language Processing, has created a new buzzword – ‘Intelligent Automation’.

Here’s how key AI technologies enrich traditional RPA:

• Machine Learning (ML): Learning from data, it helps bots identify patterns, predict outcomes, and continuously improve processes over time — ideal for dynamic decision-making.
• Natural Language Processing (NLP): Enables bots to understand human language input from emails, chat conversations, or documents, and generate human language, enabling more natural and intuitive interactions.
• Artificial Intelligence (AI): Allows bots to process unstructured data and make adaptive decisions through pre-trained models or ML algorithms.
• Optical Character Recognition (OCR): Digitizes printed or handwritten content, allowing automation to access and process data that would otherwise require human intervention.

Here are some key areas where the combined power of RPA and AI is making a real difference:

1. AI-powered document processing
   
   Manual document handling is time-consuming and error-prone. By integrating OCR and AI models, companies can automate the extraction and interpretation of data from unstructured documents such as invoices, purchase orders, contracts, and more. Because AI takes on the manual entry load, this process becomes possible.

   Fortude supported an Australian supermarket chain that handled claims from 34 outlets, each submitting documents in different formats. With built-in AI capabilities, the solution intelligently processed even unfamiliar documents by mimicking human decision-making.

2. Conversational AI and chatbotsCustomer service and internal helpdesks can be revolutionized with NLP-driven bots that understand and respond to human queries. These bots can process requests, escalate issues, or trigger workflows autonomously. Conversational AI also helps enhance user satisfaction by offering 24/7 support and consistent responses.

   At Fortude, we’ve developed our own AI-powered companion called Charlie — a smart chatbot designed to simplify your day-to-day operations. Whether it’s responding to Infor M3-related queries, assisting with customer support, enhancing sales efficiency, or enabling HR self-service, Charlie filters through multiple knowledge bases to deliver accurate, enterprise-specific answers.

3. Computer vision for UI automation
   
   Computer vision enables bots to interpret visual cues on screen (like buttons or icons), making UI automation more resilient — especially in dynamic environments where traditional selectors may fail. This is especially useful in legacy system interfaces that don’t offer APIs but are crucial to daily operations.
4. AI-driven decision making
   
   By integrating ML models, RPA can power decision making — for example, assessing loan eligibility, prioritizing support tickets, or recommending actions in real-time. The bots can execute and adapt decision logic as models evolve, reducing manual intervention and accelerating decision-making.
5. Intelligent email processing
   
   Using NLP and ML, bots can scan, categorize, and extract key data — handling everything from HR requests to customer support with minimal human involvement. This significantly reduces turnaround time and enables quicker resolution of business-critical tasks.