Revolutionizing Data Entry: To Err is human, but AI is here to help

Artificial intelligence (AI) has fundamentally altered the way data is extracted and processed. One major benefit of using AI to extract data is the ability to automate the process, thereby reducing the need for manual entry. This has been proven to not only save time and money, but also reduce errors and improve accuracy.

A recent study by the International Data Corporation (IDC) found that using AI to extract data can increase efficiency by up to 80%. This means that tasks that would take a human several hours to complete can be accomplished in just a few minutes by an AI system. This can be especially beneficial for organizations that need to process large amounts of data on a regular basis.

In addition to increasing efficiency, AI can also improve accuracy. A study by McKinsey & Company found that AI-assisted data entry can reduce errors by up to 90%. This is because AI systems are able to analyze and interpret data in a way that humans cannot, and can therefore identify and correct errors that a human might miss.

Another study, this one by the American Productivity & Quality Center (APQC), found that the average cost of a single data entry error can range from $25 to $250, depending on the type of error and the stage of the process in which it occurs. This can add up quickly for businesses that process large amounts of data, and can significantly increase their overall costs.

However, it’s important to note that AI is not perfect and it can make mistakes. That’s why it’s important to have a human quality control (QC) system in place to check the data that the AI system has extracted. This can help to further reduce errors and ensure that the data is accurate and reliable.

At NthDS we use the Nspect platform to house the extracted data and keep the human in the loop with our built-in workflows that further automate the QC process. AI data extraction combined with our state-of-the-art QC module in our platform, increases the accuracy of your data while serving as a force multiplier, enabling 1 person to have the power of 10.

In short, if you aren’t using AI for data extraction, you can expect to have costly rework and errors that can damage your product’s brand. Visit us at http://www.nthds.com to get started on the path to adopting practical AI.