AI Sector Overviews Articles and Reports

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.

AI applications in healthcare are becoming more common for white-collar automation and diagnostics. However, medical robotics is an area that may be marginally underdeveloped. This is likely because of regulations concerning automated surgery.

Since the early 2010s, major banks have used anomaly detection - an AI technique for identifying deviations from a norm - for automating fraud, cybersecurity, and anti-money laundering processes.

The Department of Homeland Security (DHS) routinely handles large amounts of data. Its mandate is to “keep America safe,” and that encompasses many fronts. This includes anything to do with potential threats to the nation, ranging from border security to cybersecurity, so “big data” would be an understatement. Using machine learning and artificial intelligence technology for Homeland Security was inevitable.

The facilitation of research and development (R&D) is perhaps the most common use case for AI applications in the pharmaceutical industry. There are numerous solutions for extracting and organizing research data from clinical trial notes and other medical documents. Additionally, there is software that can purportedly analyze data from images of drug compounds at the molecular level.

Large volumes of data, managed properly, are a boon for many industries, including the military. It would not be possible to mount effective military operations without knowing the when, where, and what in deploying resources. Military big data, therefore, helps defense leaders make better decisions, provided it is not “dark data.”

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.