6 repetitive tasks that are improved with AI

Workers spend almost half of their day performing repetitive tasks on the computer. Automation is the key to ending this problem, since it is estimated that 45% of the repetitive tasks of large companies will be automated.

In this sense, companies like Keepler Data Tech solve the most tedious tasks through automation based on artificial intelligence, in 6 different scenarios.

“At Keepler we have developed a solution that uses artificial intelligence to analyze what is known as unstructured data, which has enormous hidden value in many organizations and a high workload in its treatment,” says Daniel Alonso, Head of ML Solutions and Innovation from Keepler Data Tech.

Task automation

These are the 6 scenarios in which the company solves tedious tasks with automation:

• Back Office. Data capture, followed by mail management, digital document cataloging, IT and software reporting, or tedious invoice management, are the most hated tasks. It is possible to extract entities from documents or invoices and reduce manual inspection time. In addition, it allows its integration into the corporate ERP, thus reducing the possibility of errors and allowing the automation of this process. Also, thanks to AI (Artificial Intelligence), it is possible to summarize documents and obtain new information, comparing it with previous versions, with a much higher cost efficiency than with a manual process.
• Customer Support. Artificial intelligence in customer service is responsible for listening and interpreting messages to offer the most appropriate response to customer needs. It is increasingly common to find bots that engage in conversations with customers, offering faster and more accurate responses, in addition to the advantage of their 24/7 availability. They are able to detect when agent intervention is necessary and request their participation. In this way, agents are relieved of repetitive assistance and allow the solution of the simplest or most common processes to be automated, dedicating more time and human labor to procedures that require greater complexity. It is also possible to automate the management generated by this service, for example, automatically classifying incoming electronic messages and even automatically discarding spam, avoiding unnecessary noise.

Automation: 6 repetitive tasks that can be improved with AI

• Damage and quality check. New technologies have revolutionized quality control, inspections and anomaly detection. Machine learning algorithms provide very advanced solutions. They are capable of identifying damage or malfunctioning of machinery or structures, through image inputs, sound recordings, data patterns. In addition, they review the finished products, look for faults and ensure quality standards.
• Image recognition. Image recognition has been around for a long time, but its use has spread in recent years. This technology is very useful in numerous applications in industrial environments, for example, allowing more effective supervision of work environments and safety equipment, the identification of risk situations, the detection of anomalies in products… Thanks to this, it is possible to saves time, by using the analysis of video and photo images, to perform automatic searches in millions of records in a matter of seconds or analyzing it and having a response in real time.
• Transcription of information. The identification of specific information such as ID, dates, telephone numbers or addresses is feasible. The same technology facilitates obtaining reports from sales teams and uploading them to the CRM. The use of artificial intelligence is capable of transcribing an entire conversation in complete words, filling in the gaps left by the phonetic transcription, allowing the audio to be converted into text.
• Detection of insights and topics. Artificial intelligence is capable of extracting relevant information from opinions or reviews, and even the feelings that users have expressed on the network. In this way, it is possible to identify the margins for improvement and also the topics that are of interest when generating content.