Search Results for: health insurance

Chatbots are one of the most talked-about uses of natural language processing (NLP) software in business. Some of the most common application areas for chatbots include customer service, healthcare, and financial advisory.

Much of the artificial intelligence and automation discussion going on in the enterprise recently involves something that, in most cases, actually isn’t artificial intelligence at all: robotic process automation, or RPA.

Banks are in one of the best positions for leveraging AI in the coming years because the largest banks have massive volumes of historical data on customers and transactions that can be fed into machine learning algorithms. We recently completed our Emerj AI in Banking Vendor Scorecard and Capability Map in which we explored which AI capabilities banks were taking advantage of the most and which they might be able to leverage in the future.

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.