AI Sector Overviews Articles and Reports
Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:
Life sciences companies are likely to begin experimenting further with AI in their workflows in the coming years, but they face challenges in AI adoption due to strict regulations. Machine learning has a "black box" problem, meaning that it's in many cases impossible to know how a machine learning algorithm comes to its conclusions.
Artificial intelligence is changing the way healthcare networks do business and physicians perform their routine activities from medical transcription to robot-assisted surgery. Although the more mature use-cases for AI in healthcare are those built on algorithms that have applications in various other industries (namely white-collar automation), we believe that in the coming three to five years, AI solutions for healthcare will become increasingly specialized to individual use-cases.
The International Energy Agency’s latest annual gas market report, Gas 2018, estimated that global gas demand could reach more than 4,100 billion cubic meters (bcm) in 2023. This is an increase from 3,740 bcm in 2017. Greater gas demands mean more oil rigs, and the machines on these rigs break down.
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.”