Artificial Intelligence has always been the industry buzzword. The AI market is expected to grow approximately 126.6% by 2025. As it steps into the USD 3 trillion healthcare market with research and development investments exceeding USD 30 billion a year, according to McKinsey and PwC, the way industry diagnoses and treats illness is about to change.
Artificial intelligence is an umbrella term that refers to machines having the ability to respond to situations in a manner that resembles human intelligence. The current use of AI in healthcare mainly involves making data-driven forecasts, speeding up daily routines and detecting models and patterns as well as deviations from them. But AI has immense capability to release enhancements in the sphere of cost, quality and access. Frost & Sullivan estimates the AI health market to grow tenfold with the revenues touching USD 6.6 billion in 2021, at a CAGR of 40%, which is a significant increase from the market size of USD 633.8 million in 2014.
One of the first areas of healthcare where AI is highly likely to have useful applications is diagnostics. The next most likely area of application is care management. Personalized medicine is a third area of application, it is much further down the road. Nevertheless, AI has shown great potential with the applications namely robot assisted surgery, virtual nursing assistants, fraud detection, administrative workflow assistance, preliminary diagnosis, etc. These applications have incredible prospects and hold the key to creating USD 150 billion in annual savings for the US healthcare economy by 2026, as per Accenture analysis. Frost & Sullivan reports that AI has the potential to improve outcomes by 30- 40% and reduce the cost of treatment by as much as 50%.
The real risks and barriers of AI should also be addressed to form a well-rounded view on its usability in the domain of healthcare. One of the biggest roadblock for AI in healthcare will be overcoming inertia to revamp current processes that no longer work, and implement services with emerging technologies. There are many barriers that AI has to overcome, the availability of large quantities of high-quality data that can be used to train algorithms being one of them. In many organizations, the data isn’t in a single place or in a useable format, or it contains biases that can lead to bad decisions. These AI and machine learning systems must be able to continually and quickly ingest large amounts of healthcare data, but without the right infrastructure and process, they can’t. In order for companies to take advantage of AI and machine learning, a data strategy should be put in place to foster success. Other risks noted are safety and accuracy, risk in new/exceptional health cases and risk for patients & doctors.
Thereby, to take full advantage focus should be placed on security, workforce, institutional readiness and care reach. Startups and tech giants have hopped on the AI bandwagon, giving it the unicorn status. Even top pharmaceutical companies like Pfizer, Novartis, Sanofi, GlaxoSmithKlein, Amgen, and Merck have all announced partnerships in recent months with AI startups aiming to discover new drug candidates for a range of diseases from oncology and cardiology.
Google is the most active investor/acquirer of AI companies among big tech companies, with 92 healthcare investments since 2012 and internal projects such as DeepMind, Quantum AI, etc. Other tech giants, namely, Amazon, IBM, Facebook, General Electric, Apple, Oracle and Microsoft among others have demonstrated investments, acquisitions and have certain internal projects that are paving the way for developments of AI.
CB Insights reports that healthcare AI startups have raised USD 4.3 billion across 576 deals since 2013, thereby gearing towards improving patient outcomes, aligning the interests of various stakeholders, and reducing healthcare costs.
Among different parts of the world, investments from the China in the AI market has seen a notable rise since 2015, surpassing UK to become the second most active country for healthcare AI deals. Fosun Pharmaceutical taking a minority stake in US-based Butterfly Network and Tencent Holdings investing in Atomwise are testaments to the fact that Chinese tech giants are bringing products from other countries to China through partnerships. In its AI plan, Chinese government aimed at becoming the global leader in AI research by 2030.
In conclusion, even with plenty of issues to overcome, healthcare remains as a high interest industry for AI investments. AI has the opportunity to have a vast and progressive impact for doctors and patients in healthcare. The trick to achieving a positive AI outcome will be to develop trustworthy, accurate algorithms that can be extensively implemented to tackle major shortcomings in the current state of affairs.
Vanshita Agrawal, Research Analyst at A2Z Insights
