Search Results for: health insurance

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.

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.

When clients come to us for custom research projects, sometimes it's because it's a big firm that's looking to make acquisitions or it's a company that's looking for some kind of competitive intelligence. They're looking at who else is offering things like them and how they can position themselves against those other competitors in the market.

Episode Summary: If one wants to start a general search engine, they're going to have to compete with Google. If one wants to start a general eCommerce platform, they'll have to compete with Amazon. But the same dynamics play out on a smaller scale. There are going to be some established players, some big tech giant, be it IBM or someone else, who already has a product.

This article is part 4 of a 7-part series called “AI Zeitgeist,” where we’ll be mapping out the details of AI adoption over the next 10 years and explore the critical changes in the AI ecosystem that business leaders need to understand.

The Patient Protection and Affordable Care Act (ACA) has significantly changed the landscape for how healthcare providers can be reimbursed by insurers. They are now reimbursed based on the guidelines set by Value-based Purchasing (VBP) models. This type of payment model reimburses the healthcare provider based on the quality of their work with the insured patient.

The following statements are all true, but not in the way you might think:

AI is hard for most companies to adopt.
Machine learning talent is hard to find and hard to hire.
AI gives some companies new ways to compete in the market.

Episode Summary: Recently, we were called upon by the World Bank to do a good deal of research on the potential of applying artificial intelligence to health data in the developing world. Diagnostics was a very big focus of the information that we presented. It appears as though diagnostics is an area of great promise with regards to AI, and that's what we're focusing on in this episode the podcast.

Here at Emerj we’re dedicated to cutting through the AI hype that’s permeating the current zeitgeist in the business world. Although we’re skeptical about many of the claims that AI vendors make on their websites about what they’re AI software can do, it seems unlikely that the AI hype is going to disappoint venture capitalists and governments enough to usher in a third AI winter.

There are several companies claiming to offer AI solutions to banks and financial institutions. We found that these solutions are intended to help banking and finance companies with at least one of the following business problems: