Artificial Intelligence?  Machine Learning?  Intelligent Automation?  

Here is a jargon-free guide to these important technologies. ​


A process is a sequence of actions that gets something done.

We've been doing processes in one form or another since we first climbed down from the trees. An early process was fire-making. This involved the collection of various materials followed by a sequence of actions which got the fire lit. Today, our processes have multiplied in number and complexity. But they haven’t changed their form. They are still ‘a sequence of actions that gets something done’.



This is simple. Your car probably has an automatic gear shift. Older cars have manual shifts and you change gears ‘by hand’. Automation is therefore, doing something without using your hands. And further, without the need to use any sort of human ability like voice, sight gesture etc. 

Robotic Process Automation 

PROCESS AUTOMATION is a computer programme that analyses the processes on one or more of your systems and provides a means to automate them. It can work 24/7 with minimal supervision. 

Automation at work

Humans have been automating for as long as we’ve been working. Pottery wheels and windmills got us going and we’ve been flat-out at it ever since. But no matter what point of history you look at, the form is the same. Put simply, ‘the fewer hands that touch a process the smoother it becomes’. Today we are using digital technologies to continue to take us further towards the the most efficient, cost-saving way to do things. 

Process Discovery 

The workplace is a warm habitat for processes. They are everywhere. When it comes to automation, where do you start? One option is to form a team to map your processes and highlight blockages. Which department should be mapped? Who should do the task? Another option is to install a process discovery bot and let it review your processes, note linkages and blockages, and put it all in a report with recommendations. In the end it’s you who has to decide but process discovery is a no-brainer. 


Applications, or Apps, are the software tools you use.  They include things like Microsoft Word, Google Sheets, Outlook, Adobe – but also your systems like SAP, Oracle, Dynamics, Sage, or you own inhouse systems. Note that applications refer to the software, not the devices the software runs on.

Error Rates

This is a measure of how often errors occur within a process.  Let’s say on average you run a particular process 100 times per month and on five of those runs something goes wrong.  You have an error rate of 5%. 


These refer to the applications and the different sections within those applications that are viewed and/or worked on during a process.  For example, if you are entering an invoice into your finance system, you may have one screen where you input the supplier information and value and a different screen where you issue the payment.

High-level Steps

These are the main parts of a process.  For example, an invoice process may have invoice arriving (step 1), invoice is opened and read (step 2), validated (step 3), entered in the system (step 4) and sent for approval (step 5).

Scanned Documents

These are typically PDF documents, either emailed or generated by the business to support a process (for example, an invoice). They usually contain data and other information relevant to a specific job, customer, or supplier.

OCR (Optical Character Recognition)

This technology reads and records characters (text and numbers) from an image.  Modern data capture apps add a layer of artificial intelligence to this to make it easier to work with.

IDP/IDC – Intelligent Document Processing/Capture

This technology reads and records characters (text and numbers) from an image.  Modern data capture apps add a layer of artificial intelligence to this to make it easier to work with.

Free Text

This is unstructured, unrestricted text (not confined to forms or fields) – such as that found in the body of an email or within a report.

Remote Desktop/Server/Screen Reading

This is a technology used to access applications and computers remotely from a device such as a desktop, laptop or phone.

Artificial intelligence

Artificial Intelligence is a specific field of computer engineering that focuses on creating systems capable of gathering data and making decisions and/or solving problems. An example of basic AI is a computer that can take 1000 photos of cats for input, determine what makes them similar, and then find photos of cats on the internet. The computer has learned, as best as it can, what a photo of a cat looks like and uses this new intelligence to find things that are similar.


Autonomy means that an AI programme doesn’t need help from people. Driverless cars illustrate the term “autonomous” in varying degrees. Level four autonomy represents a vehicle that doesn’t need a steering wheel or pedals: it doesn’t need a human inside of it to operate at full capacity. If we ever have a vehicle that can operate without a driver, and also doesn’t need to connect to any grid, server, GPS, or other external source in order to function it’ll have reached level five autonomy.

Anything beyond that would be called sentient, and despite the leaps that have been made recently in the field of AI, the singularity (an event representing an AI that becomes self-aware) is purely theoretical at this point.


These are rules, formulas or commands that tell a computer what to do - repeatedly. A simple algorithm is the one we use at traffic lights: green for go, red for stop, etc. We apply this algorithm repeatedly when we’re driving in the city. Algorithms for process automation are far more complex. They handle more variables. At the traffic lights we deal with three variables: red, orange and green. In computer algorithms we can have hundreds of variables. This makes algorithms incredibly useful when combined with today’s digital processing power. It makes machine learning possible, which in turn makes our bots better at what they do.

Machine learning

The meat and potatoes of AI is machine learning — in fact it’s typically acceptable to substitute the terms artificial intelligence and machine learning for one another. They aren’t quite the same, however, but connected.

Machine learning is the process by which an AI uses algorithms to perform artificial intelligence functions. It’s the result of applying rules to create outcomes through an AI.