AI Sector Overviews Articles and Reports

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. 

The idea of using artificial intelligence (AI) in the military scares many people in the US, especially when it comes to the Army. The US Army typically operates on the ground, and so it may be uncomfortably closer to home for some people.

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.

The Chinese military, or People's Liberation Army, is focusing heavily on artificial intelligence. However, China's race to develop "smarter," cheaper AI technology for the military is not linear, but instead a many-pronged strategy that involved the central government, domestic companies, and international trade. Gregory Allen of the Center for a New American Security published a report on China's AI strategy, in which he said:
Chinese military leaders increasingly refer to intelligent or “intelligentized” military technology as their confident expectation for the future basis of warfare. Use of the term “intelligentized” is meant to signify a new stage of military technology beyond the current stage based on information technology.
He also reported that “total Chinese national and local government spending on AI to implement these plans is not publicly disclosed, but it is clearly in the tens of billions of dollars.”

The healthcare industry holds perhaps the most responsibility of any industry when it comes to ensuring data privacy. A breach in electronic medical records (EMRs) could tarnish a healthcare company's reputation, put undue stress on patients, and render the company in violation of regulations.

Credit card companies could make use of AI applications across multiple business areas. AI-based fraud detection is among the most widely discussed AI applications in the financial sector, and it seems to work for credit cards similarly to how it works for banks. Additionally, credit card companies and financial institutions could use AI software to improve customer service and develop customer-targeted marketing campaigns.

Government contracts are notoriously hard to acquire. It takes many months of painstaking work to get through the gamut of regulations that weigh about 8.5 lb when printed out. Startups and small companies, including those developing artificial intelligence, often do not have the resources to compete for a share of this market. The US Air Force is changing that by streamlining the process in what it calls Pitch Days, the first of which was on March 6 and 7, 2019 in New York.

Generic pharmaceuticals require less research and development than their brand name counterparts. As a result, AI applications for research and development don’t seem to be the most prominent solutions for generic drug companies. That said, despite the lack of precedence, there may be many areas in which AI could help generic drug companies.