In the past, automation meant handling repetitive, rule-based tasks with software robots. While that still holds true, things have evolved. Today, the real value lies in combining Robotic Process Automation (RPA) with Artificial Intelligence (AI) to handle more complex and dynamic work. This combination is often referred to as “intelligent automation”, a practical solution that helps businesses operate faster, with greater accuracy and more adaptability.
When RPA and AI are brought together, the result is much more than just automated processes. It’s about smarter workflows that think, learn, and improve over time.
Why Combine RPA with AI?
RPA is excellent for automating structured, repetitive tasks, think data entry, invoice processing, or report generation. However, it has limitations. It can’t understand context, make predictions, or process unstructured data on its own.
That’s where AI steps in. AI adds capabilities like:
- Machine Learning (ML): Allows systems to learn from data and make better decisions over time.
- Natural Language Processing (NLP): Enables systems to read, interpret, and respond to human language.
- Computer Vision: Helps machines interpret visual information, such as scanned documents or images.
Together, these tools can automate tasks that were previously too complex for traditional RPA.
How Businesses Benefit from Intelligent Automation
Blending RPA and AI leads to smarter automation with broader applications. Here’s how it helps:
- Smarter Decision-Making: AI enables bots to make decisions based on patterns and predictions, rather than just fixed rules.
- Improved Customer Service: Chatbots can understand and respond to queries using NLP, handling customer issues round-the-clock.
- Data-Driven Insights: ML models can analyze data and uncover insights, while RPA can automatically trigger actions based on those insights.
- Handling Unstructured Data: AI can process emails, PDFs, images, and voice commands turning messy data into actionable input for bots.
Practical Examples
- Invoice Processing: AI reads and extracts data from invoices, even if the formats vary. RPA then inputs that data into accounting systems without errors.
- Email Management: AI categorizes and prioritizes incoming emails. RPA routes them to the right departments or responds automatically.
- Employee Onboarding: AI can verify documents and recognize patterns in applications, while RPA ensures new hires get system access, ID cards, and welcome emails without delays.
Challenges to Keep in Mind
While intelligent automation offers clear benefits, it’s important to approach it strategically:
- Not all tasks need AI. Use AI where it adds value, such as understanding, decision-making, or prediction.
- Start small. Test combinations in specific workflows before expanding.
- Make sure your systems can support AI models and integrate smoothly with RPA tools.
Finally, it’s very important to keep in mind that at least for the time being, AI can’t replace humans. It’s perfectly fine to use these technologies to become more productive and efficient, but it’s crucial that a human confirms what has been developed to make sure the result is accurate, correct and ready to be shared publicly.
Moving Forward
As automation technologies mature, businesses have a real opportunity to make their workflows smarter, not just faster. By blending the reliability of RPA with the adaptability of AI, companies can improve how they operate in a way that feels intelligent, not robotic. In the next article, we’ll break down hyperautomation. We’ll show how it connects to what’s described in this article and how it can streamline the entire automation strategy of a business.