One of the more appealing elements in the AI investment thesis is how AI has the potential to positively alter a variety of industries. Healthcare, which is an innovative space in its own right, is ripe for disruption and the benefits afforded by AI.
Increasing digitization of healthcare has implications for some AI-related companies residing in the Invesco QQQ Trust (QQQ) and the Invesco NASDAQ 100 ETF (QQQM). The AI exposure of those ETFs could be more compelling as the healthcare sector becomes a bigger AI adopter.
That’s a point to keep in mind for multiple reasons. First, market observers are increasingly noting that AI is evolving from the enabler phase to the adopter phase. Specifically, healthcare is an adopter. Second, many large-cap healthcare companies have the capital needed to make AI investments. Third, the sector is one in dire need of cost-reducing, efficiency-enhancing avenues and AI can help on those fronts.
Plenty of AI Applications in Healthcare Sector
There are encouraging possibilities for AI enablers held by QQQ and QQQM pertaining to the healthcare sector. AI has multiple avenues to be additive within the sector. For example, take the case of the industry’s significant data demands.
“Despite comprising over one-third of the world’s total volume, data in healthcare has historically been siloed and poorly organized, with over 80% unstructured,” noted Stephanie Aliaga, global market strategist at J.P. Morgan Asset Management. “However, over the past 15 years, tens of billions of dollars have been spent to digitize the industry (i.e. via electronic health records), allowing AI models to harness the over 500 petabytes of health-related data that exist today.”
QQQ/QQQM tech holdings with AI exposure can help healthcare companies increase innovation and streamline the drug development process. These two factors in particular enhance the allure of the long-term AI/healthcare relationship. Bringing new products to market is the lifeblood of the biotech and pharmaceuticals industries. After all, patent protection has a limited shelf life.
“Drug development is a lengthy and costly process. It can take up to 18 years from pre-clinical research to commercialization and costs an average of $2.3 billion per drug—of which 80%, on average, is spent on R&D. By boosting productivity, generative AI could cut costs while improving drug success rates,” added Aliaga. “McKinsey estimates a potential increase of $60-110 billion in annual economic value for pharma and medical product industries.”
Bottom line: there are good reasons for healthcare to embrace AI and those factors could be beneficial to QQQ and QQQM investors.
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