The Difference Between OCR and AI
Manual data entry is time consuming, and solutions have been implemented to help us with these processes. One of them being OCR, and another one being AI. You may wonder which one you should use. This is the difference between OCR and AI.
What is OCR?
Optical character recognition is a technology that recognizes text in documents and images. OCR is used to collect data for business documents. Even though the setup process can be annoying and time consuming, the reliability of text recognition is enough. OCR can also recognize handwriting and can be used for pattern recognition.
To accomplish tasks, it is necessary to set up rules for each template and field. OCR needs rules and templates to ensure that the technology actually captures the necessary data.
When it comes to invoices, for example, each field needs its own rules. Error streams may also occur, such as a lack of flexibility in terms of variability in the document. OCR technology cannot be fully automated, so more or less of these rules must apply, and it will have a significant impact on the accuracy of the output, as well as on the cost and time of processing.
What is AI?
Artificial Intelligence is a branch of computer science that deals with the simulation of intelligent behavior by computers. It has the ability for machines to mimic intelligent human behaviour.
To extract data from an invoice, a set of rules and templates would have to be set up for a field that varies from provider to provider. AI can work on other business documents, but it does not require the same rules or templates to work from day one.
As AI is still a relatively new, there are still hurdles to adoption. It seems to take some time for AI to be fully accepted and implemented in companies.
Which One to Use?
Ultimately, it depends on the work you need to do and what the final goal is.
Using Both OCR and AI?
What about using both? Get the best of both worlds with Zapbot. Zapbot is an intelligent document extraction software that combines OCR and A.I. Machine Learning to extract information from various types of documents (eg invoices, bills, ID cards, etc.). It can read information from digital documents or use OCR to convert scanned images from documents into digital data, and in turn identify the type of data. This will help to automate information extraction and document processing in various sectors such as banks, insurance, human resources, finance, procurement shipments, and more!
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