Investments rising exponentially as AI solutions take aim at healthcare
Over the last two years, the healthcare industry has become a major proving ground for artificial intelligence (AI) capabilities, with both startups and venture capital (VC) investors recognizing the enormous potential that AI solutions can offer for improving patient care, expanding the reach of services, and reducing healthcare costs. The latest edition of KPMG Private Enterprise's* Venture Pulse Report highlights the increasing excitement around the applicability of AI in healthcare.
Artificial intelligence (AI) and machine learning (ML) are often conflated; in essence, artificial intelligence can be understood as the overall field of computer science while machine learning is a subset. Investment within AI and ML applications in healthcare have exploded as of late, mainly as the enormous potential for accurate automation of tasks as routine as, say, radiology readings is fairly obvious. The key challenge is the degree of accuracy, as in the field of healthcare the rewards are enormous if one can automate analytics and disintermediate the complex chain of value, but given that human health and lives are at risk, predictions must be absolutely airtight.
Since 2015, VC investment in AI for healthcare has soared, reaching almost $1.3 billion across 103 deals in 2017. Investments continued to increase in Q1'18, with $320 million invested across 18 deals: well on pace to at least match 2017's totals. Given the inefficiencies and high costs associated with healthcare in most regions of the world, it is very likely that funding for AI will only continue to grow.
The use of AI and machine learning in healthcare is not a new endeavor. FDA-approved algorithms have been used since as early as 1998 to detect cancers in medical images. The difference today is that new technologies are making such efforts much easier. Use of the cloud and the rapid digitalization of information has improved access to data and the speed of computation. VC investors have seen the concept of AI become mainstream and are investing accordingly.
VC investors are excited about AI solutions because they can help meet a variety of needs for different stakeholders -- from increasing patients' access to care and improving outcomes, to allowing doctors to be more efficient and improving quality control for health system regulators.
VC investors are also interested in the potential of AI to help impact broader health system inefficiencies. For example, life sciences companies could potentially use AI tools to `fail fast', better identify population subsets where new drugs will do well and find secondary uses for old failed drugs. Such improvements could speedup drug approvals and reduce development costs. AI can also be used to improve supply chain management, disease prevention and support patient monitoring and care of chronic illnesses.
Many corporates are just starting to put their toe in the water with respect to making investments in AI, using funding as a means to wrap their heads around how to leverage technologies effectively. Recent acquisitions in the space are likely to spur more corporate and private equity investments in the space.
On the not-for-profit side, the ability to make better, data-driven decisions is seen as a major benefit. However, most organizations recognize they will need to change their business models in order to get the most value from AI innovation. The challenge is that regulations are still somewhat behind so corporates do not want to get too far ahead of themselves. In the interim, not-for-profits in the space are still looking at making VC investments, building for-profit arms, and monetizing their data.
“For AI in healthtech to achieve its full potential, there needs to be a much broader understanding of the value of AI across healthcare workflows and the ability of AI to supplement existing processes. While this will take time due to some fundamental inertia of healthcare, the application of AI in healthtech will lead to an entirely new paradigm for providing tech-driven healthcare” by Bharat R. Rao, Ph.D. National Leader, Data & Analytics for Healthcare & Life Sciences, KPMG in the U.S.
Access to data is one of the critical enablers of the successful use of AI in healthcare. The advent of technologies like wearables that can provide constant streams of data and the development of analytics tools to manage and analyze available data quickly will continue to underpin the successful use of AI. Similar to other areas where AI is seen as a backbone for transformation - such as autonomous driving - without access to the right data at scale, AI may not be able to live up to its potential.
Over the next few quarters, investments in AI for healthcare will likely focus primarily on improving back-end efficiencies, such as the use of RPA to support care, or the use of AI to process claims. In the short term, it is unlikely that AI investments will focus on direct patient diagnosis, but rather on ways of using AI to provide routine second opinions or to detect errors.
While the majority of VC investments related to AI in healthcare have occurred in the U.S., there is likely to be increasing investment in other regions as investment in the space continues to heat up. While AI has the potential to reduce costs and improve quality in developed countries, it also has the potential to help address issues in developing regions with infrastructure deficiencies or scarce resources. China, in particular, is expected to see major investments in the near-term.
Jonathan Lavender is the Global Chairman for KPMG Private Enterprise. Read the latest KPMG Venture Pulse Report.
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