From rules to reasoning: understanding the difference between RPA and AI agents
Automation. For many SMEs, it’s the starting point of working more efficiently. But once the first processes are automated, a bigger question arises: what’s next? Should you automate more? Or automate smarter?
In this blog, we explain the difference between traditional RPA (Robotic Process Automation) and AI agents. Not to overwhelm you with buzzwords, but to help you see what’s possible today and how your organisation can benefit from both.
What is RPA?
RPA is a technology designed to automate repetitive, rule-based tasks. Think of:
- transferring data between systems
- sending standardised emails
- filing documents based on fixed criteria
RPA always follows a predefined set of instructions. It’s predictable and reliable, but also limited. As soon as something deviates from the expected pattern, the system breaks down. RPA only works with structured input such as spreadsheets or forms and has no capacity to learn or adapt.
What is an AI agent?
An AI agent goes a step further. It is a system that:
- makes decisions based on context, input, situation, goals and available tools
- works with unstructured data like language, emails and images
- learns and adjusts based on feedback, new data or failed attempts
It doesn’t just follow rules. It attempts to achieve a goal with the tools it has been given and adjusts its approach if the initial one is unsuccessful. That ability to adapt only becomes truly powerful when the system is given memory, so it can retain what worked or failed before and apply that learning in future situations.
Why this distinction matters
Many organisations are already using RPA to streamline their workflows. And that’s a significant first step. But if you want to unlock more strategic value, you’ll need to move beyond repetitive logic.
AI agents are built for situations that require nuance, interpretation, or flexibility. They can prioritise, reason, assess intent, and handle messy or incomplete data. Most importantly, they improve as they go, provided you feed them the correct data and context.
How to get started?
You probably track your physical and mental health with a Garmin, Apple Watch, or Whoop, right? But what’s tracking the health of your AI journey? That’s where the AI Maturity Scan comes in.
Our AI Maturity Scan and Adoption Framework gives you a clear view of where you are today, which processes are AI-ready, and what steps to take next.
Think of it as a wearable for your organisation. It provides insight into how far you’ve come, how quickly you’re progressing, and where your AI strategy is actually making a meaningful impact.
With our AI Adoption Framework and targeted workshops for each phase, we guide you from first steps to measurable results, all at your pace, based on real needs.
Curious how fit your AI really is?
Start measuring today with CROPLAND.
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