The healthcare industry has been investing in artificial intelligence (AI)for years because of its revolutionary contributions to technology. A study shows that 75% of large businesses with a turnover of more than $10 billion committed over $50 million to AI in 2019 alone.
When the pandemic began having an impact on doctors and healthcare workers, AI’s role became more apparent for its ability to provide precise data while increasing efficiency. It is important to the growth of the industry, but it isn’t entirely risk-free. Let’s explore both sides of this coin to have a sense of the role AI plays in the healthcare industry.
Benjamin Gordon Cambridge Capital: AI and the healthcare sector
The benefits of AI
Studies suggest that about 250,000 deaths happen each year in the US alone as a result of medical error. Medical error is one of the leading causes of total deaths in some countries after cancer and heart ailments.
When using AI products, these errors are very often avoidable. Some technology can use machine learning to understand whether a drug is suitable for a patient’s profile or not. This process is similar to fraud detection conducted by financial agencies. AI enables physicians to spot mistakes and risks, which can be easy to miss otherwise.
According to Benjamin Gordon Cambridge Capital, the American healthcare industry wastes billions of dollars each year. One study shows that this waste makes up nearly 25% of medical costs. Why does this happen?
The blame is generally placed on inefficient systems. Research shows that staff scheduling tends to be challenging for healthcare companies. With AI, staff management can greatly improve while saving about 90% of the time that goes into this labor.
- Scientific discovery
A collaborative environment allows development to happen more quickly. And, in the field of science, efficiency is one of the most basic needs. Since scientific development involves data transfers and collaboration, AI makes this job easy by fetching information from across the globe faster. It can study patterns as well, which is a practice that may cause even physicians to falter.
The Risks of AI
As Benjamin Gordon Cambridge Capital points out, any kind of development comes with associated positives and negatives. AI is no different. The success of AI depends on the quality of data it receives. The data has to be exact because the exactness of the data is essential to ensure the results are free from any bias.
The system design has to be strong to avoid errors or miscalculations. Regular audits and tests are critical to detect system biases. System biases can cause unreliable data in the absence of checks and balances.
Another challenge with AI is ethics. Collecting a large amount of information on diseases is helpful, but ethical practices must be maintained to avoid misuse of data and privacy breaches. Problems like data leaks need careful and exact attention to be prevented.
Even so, AI is revolutionizing the healthcare industry by saving time, effort, and money, all while making it more resourceful.