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AT&T traces its history to 1875 when Bell Telephone was founded soon after Alexander Graham Bell patented his invention of the telephone. Today, AT&T is the world’s largest telecom and the largest mobile telephone service provider in the US. 

While overt AI "flops" are less common than they were three years ago, the pattern of failure for AI projects is still much the same.

This article is based on a presentation at the 2017 AI Applications Summit conference in Boston, entitled “Artificial Intelligence in the Hospital Setting” (slide deck embedded below) delivered by Emerj CEO Daniel Faggella - updated with recent insights and interviews from Emerj's podcast and AI Opportunity Landscape data.

McKesson is a large pharmaceutical distributor that delivers health information technology, medical tools and supplies, and care management tools and software to healthcare providers in the United States. The company has been working to incorporate artificial intelligence solutions internally since 2012, but in more recent years they have adopted a few important automation tools. 

The finance sector has proven itself an early adopter of AI in comparison to other industries. As such, the applications of artificial intelligence and machine learning in finance are myriad. Traders, wealth managers, insurers, and bankers are likely well aware of this in some form.

Facial recognition software is making its way into the mainstream, with consumer applications such as the ability to unlock one’s smartphone with their face. The banking sector has been at the forefront of enterprise adoption of AI since machine learning became the hot topic of the business world in the early years of the decade; as such, it makes sense that facial recognition technology would start to make its way into banking.

There are few companies claiming to offer artificial intelligence solutions to orthopedics companies. We found that these solutions are intended to help orthopedics companies with at least one of the following business problems:

Government interest in AI has picked up in recent years, and many government officials are starting to ask the same questions business executives were asking two or three years ago. Governments and large NGOs are starting to invest in AI, spending budget and time on pilot programs for various AI applications and discussions with people in the field on the future implications of the technology.

According to the International Health, Racquet & Sportsclub Association, the global fitness industry earned revenues estimated at $83.1 billion in 2016, up from $81 billion in 2015, and growing by 2.6%. If it continues at this rate, it should reach $87.5 billion in 2018. As of now, numerous AI vendors claim to assist gyms with signing up new gym customers, developing nutrition and fitness programs, and maintaining good customer relationships. Some offer chatbots that they claim can help gym members maintain personalized fitness regimens.

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.