Artificial intelligence (AI) already impacts our lives, in smart-home devices, virtual assistants, and search results, among other things. But AI will eventually play a bigger role in even more applications, including healthcare.
Accenture forecasts that AI adoption in healthcare is set to grow rapidly as consumers use the technology to keep track of diseases and manage their health. In fact, one in five consumers in the U.S. has already used AI to receive healthcare services, according to Accenture's survey.
The consulting company forecasts that AI in healthcare could become a $6.6 billion industry by 2021, a massive jump from $600 million in 2014. Not surprisingly, tech giants like Microsoft (NASDAQ:MSFT) and NVIDIA (NASDAQ:NVDA) are already scrambling for a piece of the pie. Let's see how these two companies are going after AI in healthcare and what this could mean for them in the long run.
Microsoft moved into the AI-enabled healthcare market by setting up a new division at its Cambridge research facility last September. The company is looking to develop predictive tools and personal health information systems to alert patients about their conditions in a timely way, so they can receive the required medication.
The company is using its cloud computing platform and AI expertise as part of its Healthcare NExT initiative, and it has already struck a few notable partnerships, like a strategic research partnership with the University of Pittsburgh Medical Center (UPMC).
UPMC is a healthcare delivery network that comprises more than three million members, 25 hospitals, and 3,600 physicians. It will use Microsoft's tools to generate new patient insights and develop conversational tools for patient-doctor interaction, among other features.
Microsoft is also moving toward the commercialization of its AI-enabled healthcare services, recently announcing that its Microsoft Genomics service is now generally available on the Azure cloud platform for use by healthcare providers. Genomic medicine is an emerging medical discipline that uses an individual's genetic history to cure life-threatening diseases.
It could take years to study a patient's genetic history and devise medication based on that, but Microsoft is using high-performance computing to speed up the process of genomic sequencing and research. The company has already brought St. Jude Children's Research Hospital on board to use its genomics service, and the hospital's medical professionals can now use genomics data to treat diseases such as childhood cancer.
In all, Microsoft is targeting a genomics medicine space that could be worth $24 billion in 2022. The general availability of Microsoft's genomics research platform puts it in a strong position to tap this market.
NVIDIA is one of the pioneers in AI with its expertise in graphics processing units (GPUs), which are necessary to carry out complex statistical calculations for training AI models. In fact, AI researchers around the world had recognized the importance of NVIDIA's graphics cards for carrying out complex calculations as early as 2011, giving the graphics specialist a head start in AI.
The chipmaker has used its GPU expertise in the field of healthcare as well. Late last year, GE Healthcare announced that it will equip 500,000 of its imaging devices across the globe with NVIDIA's AI tech, which will help GE Healthcare's CT scan system to process medical images twice as fast.
This technology -- approved by the Food and Drug Administration -- can improve clinical outcomes thanks to its speed and efficiency, but more importantly, medical professionals will now be able to detect liver and kidney lesions with more accuracy, too.
And NVIDIA and GE Healthcare are ready to push the envelope further. According to GE's estimates, an average hospital generates 50 million gigabytes of data every year, but only 3% of it is analyzed or acted upon. The computing power of NVIDIA's GPUs can help GE create more actionable data that can be used in healthcare applications, like the creation of treatment plans.
This is probably why NVIDIA has decided to train 100,000 developers in healthcare AI. For instance, an NVIDIA GPU-powered supercomputer can enhance the training of AI models for diagnosing breast cancer. As this technology's effectiveness grows, NVIDIA's GPU sales will benefit.
Despite these promising moves from both companies, investors need to remember that AI in healthcare is still in its early stages. Given the scale of the healthcare industry in the U.S. and abroad, these early efforts are still important to establishing a foothold in a space that is poised to take off in just a few years.