AI Articles and Analysis about Process automation

Customer data is essential for insurance firms to stay competitive in the coming decade. Insurance companies at present have backlogs of data on past and existing customers in the form of policy agreements, applications, and claims forms. They’ve also collected millions of images showing car damage, property damage, and personal injuries.

There are many possibilities for automation in the healthcare industry outside of AI. Robotic process automation (RPA) technology can serve healthcare companies with various use cases involving data transfer and clinical documentation. Moving important information from the business’ frontend to their deeper business processes is among the most common use cases for RPA in healthcare, and many other solutions emerge from this idea. A similar phrase and field to RPA is called White Collar automation and readers can find a full interview on white collar automation in healthcare today here. 

AI software for corporate banks is not too different from those for retail banks, although their data requirements and intentions for the software will differ. AI vendors currently selling to banks typically have clients covering all types of banking, but few specify any of their solutions to be for corporate banking specifically. Instead, they market themselves across the entire industry and give corporate banking details where appropriate.

There's an entire artificial intelligence ecosystem for enterprise search. Most of this is in a purely digital world. Most vendors help with a layer of AI-enabled search that understands terms or phrases and is able to return the results or answers to questions that someone types in. But the problem is compounded when it comes to searching the physical world.

Large banks deal with millions of documents every day across their corporate offices and numerous branches. Although one might assume that these documents are digital, in many cases, even the largest banks store old physical documents in file cabinets and boxes off the bank’s premises, and even those that are kept on-site might be relegated to storage units amongst hundreds of thousands of other documents.

AI applications for automating processes in clinical trials are among the most prominent AI applications for the pharmaceutical industry. AI vendors are currently offering software that allows pharmaceutical companies to leverage their scientists' notes for data science projects regarding their future trials. Additionally, there are some applications which help companies segment their customers into easily navigable groups when finding patients for clinical trials.

Optical character recognition (OCR) is a subset of machine vision technology that focuses on recognizing written letters and characters and reproducing them digitally for later use. This opens up many possibilities for the banking industry, including some security solutions, and notably, document digitization.

Machine vision has numerous use cases within the healthcare industry, including clinical solutions such as medical imaging and medical diagnostics. There are also possibilities in white collar automation such as medical transcription, which was one of the main interview topics in our white collar automation interview with the Executive Chairman of CognitiveScale.