AI in Healthcare: The Next Frontier
Why Artificial Intelligence Is Reshaping Diagnostics, Imaging, and Clinical Decision-Making: The Key Market Dynamics and Tech Drivers Investors Can’t Ignore.
Artificial intelligence (AI) applied to healthcare is revolutionizing the industry, enabling doctors and researchers to make more accurate diagnoses and develop more effective treatments.
According to Global Market Insights, in 2022 Artificial Intelligence (AI) in the Healthcare Market size exceeded $5 B and is going to grow around 29% CAGR through (2023-2033) reaching something like + $70 B in 2032, driven by the increasing demand for innovative solutions to complex health challenges.
Let's try to get a broader vision of this emerging trend.
For newcomers, in the healthcare context, solutions are generally designed to:
improve patient outcomes,
reduce healthcare costs,
increase access to care for patients worldwide.
For better clarity, today we will not talk about therapies and in particular new drug discovery market, which will take a considerable share of this market expecting to reach + 22 B in 2032. We will discuss it in the future.
So, today we will focus on 3 main points:
Context: what are the main important healthcare challenges in the middle-long term run?
Tech Potential: what is AI, and what is not AI?
Sweet Spots: which gaps can AI fill that other technologies are struggling to tackle? In other words: what are the potential benefits and limitations?
Quick Facts:
If you’re hurry, here’s a 1 min recap of what you should get from this content:
AI adoption in healthcare is driven by the aging population and the shortage of healthcare workers. COVID-19 has accelerated this trend, with strong market interest shown in the US.
AI can automate clinical decision-making and diagnosis, making healthcare processes more efficient and less expensive. It can also improve accuracy in diagnoses, therapeutic recommendations, and interpretation of medical images.
An interesting sweet spot is AI in diagnostic imaging with a +1B dollar market expected already by 2024.
However, issues such as data quality, privacy, ethics, and regulation may hinder its adoption.
1. Why talk about AI + Healthcare today?
Trying to answer this question comprehensively would probably require 300 pages of reports. But this is a briefing. So, we'll navigate smoothly through literature and market analysis reports to pick up a digestible vision of the most pressing healthcare gaps ready for AI solutions.
Demographic & Workforce Dynamics
The world’s older population continues to grow at an unprecedented rate and the resulting incidence of various age-related diseases will generate sustainability issues in the provision of healthcare worldwide. In numbers, according to WHO:
by 2050, the world’s population of people aged 60 years and older will double reaching 2.1 billion.
The number of persons aged 80 years or older is expected to triple between 2020 and 2050 to reach 426 million.
Early diagnosis and management of chronic diseases in a context of limited human resources (according to WHO a projected shortfall of 10 million health workers by 2030) and difficult management of the growing burden on their respective health systems is leading governments in various countries to increasingly invest in the adoption of new technologies.
Moreover, research results on personalized care are opening unique scenarios in increasing the value of care. However, it is another challenge to meet the sustainability needs of healthcare budgets.
Finally, in the context of increased demand for healthcare professionals, large-scale training and updating of personnel in both well-equipped and remote contexts is still a challenge.