Healthcare Industry

In response to the coronavirus, Healthcare companies are increasing the amount they invest in artificial intelligence.

In a survey that polled 500 healthcare industry executives across the life science, hospital, health plan, and employer organization sectors, 56% of them say their respective organizations are expanding their use of AI in response to the pandemic.

83% of organizations already have an AI strategy in place, and 15% are in the ‘planning’ phase. These executives are expecting to see a return on their Machine Learning investment in less than 4 years. Also, 57% of organizations are in ‘late-stage AI deployment’ and those companies expect to a return in as little as two years.

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This makes sense as this recent survey backs up one done by Deloitte late last year. In that survey, they asked 120 healthcare executives similar questions. At the time, about 75% of health care providers that were surveyed had expected to increase their AI funding in 2020.

Healthcare organizations had reported that their main concern regarding AI is the cost. This doesn’t really make sense. That’s like worrying about the cost of a fuel potion than gives your car unlimited miles per gallon. People.. it’s ok to spend money if that money spent saves more money than it costs.

Also, AI is a totally free technology, lol. You don’t have to pay anything to use it. I suppose if you don’t know how to use computers, then you might have to pay someone to do it for you, but that is a separate issue.

If these healthcare executives don’t want to pay for other people’s AI tools, then maybe they can spend 1% more on their research and development department. They could train their staff on a free AI tool, like Google Tensor Flow.

Why The Healthcare Industry Wants AI

The Healthcare Industry is planning on using machine learning to automate the administrative processes and to detect fraud. They also want to use it to reduce waste and eliminate abuse. Life sciences organizations are depending on AI to enable personalized communications and to help identify patients for clinical trials.

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