Four ways artificial intelligence could change healthcare

In our opinion, there are four ways artificial intelligence could change healthcare, and this article outlines each one. Here, we turn to healthcare, where we believe innovation can be a strong force for change. For example, healthcare systems hold large amounts of data that analysts can use to generate insight. In addition, pharmaceutical companies keep looking for ways to shorten lengthy drug development timelines. In theory, AI could help match the right treatments, in adequate quantities, to the right patients. However, these potential benefits depend on data quality, privacy safeguards, and regulatory approval.

Four ways artificial intelligence could change healthcare

The list below reflects our view of where early applications may appear.

• Research and development. First, AI could help improve the success rates of medications in clinical trials. However, any such gains may take years to appear, and results may vary widely.
• Clinical trials. Next, AI tools applied to logistics could speed up the trial process and improve efficiency. For instance, they could help companies find faster-enrolling sites and flag underperforming ones. Of course, these tools rely on accurate site data, and poor inputs can lead to poor choices.
• Commercial development. In addition, AI could help companies identify physicians and specialists suited to support a new product launch. Meanwhile, it could point companies toward the events most likely to build awareness of a new medication. In practice, marketing rules and approval requirements still limit how companies promote any product.
• Complementing the human experience. Finally, every patient wants an accurate diagnosis, and this is where AI could make a meaningful difference. For example, AI tools may help a physician assess a patient’s uncommon symptoms. By using AI to support diagnostic accuracy, providers may reach better conclusions and potentially improve outcomes. Above all, we see AI as a support for clinical judgment, and it can produce errors or reflect bias.

Evaluation and regulation may set the pace

In our view, these applications could be AI’s first steps into the sector. However, progress may take time. Researchers and regulators will likely keep evaluating whether these tools deliver better results and economic benefits. We believe these capabilities are here to stay. Nevertheless, adoption may be uneven, and some applications may not meet early expectations.

For instance, UnitedHealth Group has stated that AI could help reduce the time needed to turn data into information. According to the company, this may lead to a better understanding of the factors that affect a person’s health. In our opinion, strategic use of this technology may support better healthcare decisions and lower costs for companies. However, implementation costs, data privacy concerns, and integration challenges may offset some of these gains. Therefore, these four ways artificial intelligence could change healthcare remain possibilities rather than certainties.

How to read these possibilities

For investors, the key question is not whether AI sounds promising but whether it produces measurable results. First, it may help to look for evidence that a tool improves a specific task, such as trial enrollment or diagnostic support. Next, investors may want to consider who pays for the technology and who captures the savings. In other words, a tool that helps patients may not always help a company’s earnings. In addition, healthcare tends to move slowly because patient safety comes first. As a result, companies may test new tools in limited settings before wider use. Meanwhile, competition may reduce any early advantage.

Most importantly, we think a balanced view weighs potential gains against the risks noted above. Of course, the pace of change may differ across research, trials, marketing, and clinical care. Fortunately, investors do not need to predict every outcome to follow the trend. Instead, they can track progress over time and adjust their expectations as evidence builds.

This article is educational and is not investment advice or a recommendation regarding any security or company named.