Artificial intelligence (AI) has the potential to upend every sector in a way that we’ve not seen in our lifetime. Healthcare, a $9 trillion global industry1, is no exception.
While there is much speculation about likely use cases and the potential impact of AI, we believe innovations will have a positive impact on costs and quality of care delivery. This is especially true when you consider the significant opportunity to reduce or eliminate upwards of $1 trillion of fraud, waste, and abuse in the US healthcare system alone2.
We believe the impact of AI in healthcare will be far reaching, specifically as it relates to the following:
While we are still in the early innings of AI’s potential to impact the healthcare sector, we believe use cases will be far reaching. We are cautiously optimistic about the use of health data to inform AI models, given privacy and regulatory restrictions. We believe that AI will meaningfully impact the cost and quality of care delivered and will ultimately lead to more efficient and effective drug discoveries. While it will happen in phases over time, we are in a once-in-a-lifetime paradigm shift and are excited to monitor the impact on healthcare and the investible opportunities that advances in AI and ML will create.
1. Source: World Health Organization
2. Source: Jama Network Waste in the US Health Care System: Estimated Costs and Potential for Savings, October 7, 2019
3. Source: Jama Network Administrative Simplification and the Potential for Saving a Quarter-Trillion Dollars in Health Care, October 20, 2021
4. Source: National Bureau of Economic Research The Potential Impact of Artificial Intelligence on Healthcare Spending, Page 4, January 2023, revised October 2023
5. Sources: Forbes, Congress.gov
6. Source: whitehouse.gov. Executive Order.
7. Source: National Library of Medicine Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018, March 3, 2020
8. Source: McKinsey & Company Fast to first-in-human: Getting new medicines to patients more quickly, February 10, 2023
9. Source: National Library of Medicine Why 90% of clinical drug development fails and how to improve it?, February 11, 2022
10. Source: For illustrative purposes only as a select example of a company in the Adams Street portfolio related to use of AI in healthcare. This company is not intended to be representative of the holdings of the broader Adams Street portfolio or any particular Adams Street-managed investment vehicle.
11. Source: Freenome
12. Source: PLOS Digital Health Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models, February 9, 2023.
13. Source: Atropos Health How Well Do Large Language Models Support Clinician Information Needs?, March 31, 2023
14. Source: WhatIs.com What are AI hallucinations?, June 2023
15. Source: Atropos Health How Well Do Large Language Models Support Clinician Information Needs?, March 31, 2023
16. Source: Nature Supervised deep learning with vision transformer predicts delirium using limited lead EEG, May 16, 2023
17. Source: Amazon Web Services What is an API (Application Programming Interface)?
18. Source: Amazon Web Services AWS HealthScribe
19. Source: Journal of Medical Internet Research Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study August 22, 2023
20. Source: Bain & Company Beyond Hype: Getting the Most Out of Generative AI in Healthcare Today August 7, 2023
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