From Siri and Alexa to chatbots or robot traders, artificial intelligence has fundamentally changed many aspects of how we work and data capture is no exception.
Close your eyes and imagine depositing your invoices in a scanner, leaving and letting your computer archive / sort them so that you have only the “exceptions” to process before paying the bills. Do you think this is a dream still far from being realized? Not so sure.
Did you know ? Really intelligent capture software does not require templates, keywords, exact definitions, classifications or indexes to do a good job. Indeed, it can extract the right information and give meaning to a multitude of documents alone, whatever their size, format, language or symbols used.
Three ways in which artificial intelligence modifies data capture
With intelligent capture software, the AI-based “engine” can learn – like a new employee – to perform data entry. It can quickly extract contextual information and learn to interpret the patterns and characteristics of different types of documents. In addition, it can validate the data and provides additional protection, which employees can not achieve without tedious manual searches.
Intelligent data capture has changed the game for three main tasks: classification, extraction and validation.– Classification
With the classification, also called “sorting of documents”, the software learns to recognize different types of documents (when the user “teaches” some variations and examples). The automatic learning engine reduces the number of rules to be applied, which gives a high level of confidence in the classification of documents with a minimum of manual effort.– Extraction
Artificial intelligence has worked wonders for extracting data in semi-structured and unstructured documents. For example, consider identifying the invoice number, which typically involves creating complex templates, keywords, and links around specific domains and labels. A new employee can view a document and immediately locate invoice numbers, regardless of the form’s form. Now, software can do it too without the need for programming.– The validation
AI-driven research extends research with different tools. Thus, it can use different sources of information (such as an example, quantity, price, description, or amount) to link an article to the system database.
Working in tandem: intelligent capture and automation of robotic processes
The market for RPA (Robotic Process Automation) is booming. So far, it is delivering on its promise to automate complex, rule-based processes. Forrester expects a global market – with only a fraction of document capture – worth $ 2.9 billion in 2021, compared with just $ 250 million in 2016 (10 times more growth in five years).
In other words, the system itself becomes smarter.
In addition to the obvious advantages of automation, the use of intelligent data capture software also eliminates conjectures on the configuration side. It is important to note that the goal of AI-based data capture is not to replace humans, but to drive as much automation as possible with machines that can intelligently perform tasks. In the end, employees are freed from mundane tasks and can take on valuable tasks that require a human spirit to do things right.
In a world where information and documents are constantly changing, any company that wants to be successful must learn and adapt – ideally with technology that does the same thing.