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Broadly, artificial intelligence involves a machine doing something that only a human would be able to do. That said, computer scientists disagree on if certain computing capabilities from several years ago still constitute AI. Nowadays, many of these capabilities might just be called software.

According to Deloitte and the Economist, global annual health spending should reach $8.734 trillion dollars by 2020, and, as mentioned in our previous report on AI for Healthcare in Asia, InkWood Research estimated the size of the artificial intelligence market in the healthcare industry at around $1.21 billion in 2016. As of now, numerous AI vendors claim to help healthcare professionals diagnose patients using machine vision. Other AI vendors claim to offer solutions for increasing adherence to drug therapy programs.

When searching Indeed at the time of writing this article, over 770 remote machine learning job listings were posted. A search on LinkedIn yielded over 1,200 results.

When it comes to planning an AI initiative, a business will need to determine the method by which to acquire the data necessary to meet their objectives. Data is essential when it comes to succeeding with AI. An effective AI strategy is built on top of data that is specific to the business problem a company is trying to solve.

InkWood Research estimated the size of the artificial intelligence market in the healthcare industry at around $1.21 billion in 2016. We surveyed more than 50 executives from healthcare companies previously and laid out the state of AI applications in the healthcare space. It seems AI-based healthcare innovations have made their way into Asia, led by developments in China, India, Japan, and South Korea. Numerous companies claim to assist healthcare professionals in Asia with aspects of their roles, including assisting in diagnostics, remote caregiving, and improving a patient's ability to manage their health using data from wearable devices.

NASDAQ estimates more than $5 trillion is traded every day in what it describes as “the most actively traded market in the word:” foreign exchange, or forex. Business leaders might expect AI to make its way into the forex world the way it has into finance and banking broadly. Most companies claim to assist foreign exchange traders by predicting when to trade or hold onto currencies. As it turns out, however, Most of the AI vendors in the forex space are in fact only claiming to use AI. There is strong evidence to suggest that their claims are illegitimate.

Episode Summary: In this episode of the AI in Industry podcast, we interview Nikhil Malhotra, Creator and Head of Maker's Lab at Tech Mahindra, about how artificial intelligence changed the nature of IT services and business services in general. Malhotra talks about what businesses should consider to make themselves relevant for the future. In addition, he discusses the philosophy shift that has to happen for people to be appreciative of the process of problem-solving, and to see profit and growth from AI. We hope business leaders in the IT services industry will take from this interview the low-hanging fruit applications in the IT services industry.

Artificial intelligence and machine learning have fueled technological innovations in marketing, eCommerce, and several other industries. Many people experience the benefits of AI and ML systems without even knowing it every time they search on Google or click on a song in Spotify.

Modern AI and machine learning software require large sets of data in order to train its algorithms to make judgments, make predictions, and take actions. Data is a critical part of bringing artificial intelligence to life in different industry sectors. The applications we’ve highlighted below involve organizing historical and real-time data from existing businesses in the retail sector from which data scientists can build machine learning models.

It should come as no surprise that AI has found its way into radiology in a similar fashion to most other medical fields. Many AI vendors selling into the radiology field are just beginning to gain regulatory approval. We researched the use of AI in radiology to better understand where AI comes into play in the industry and to answer the following questions: