Since the dawn of financial markets, there have been speculative bubbles. They span everything from Dutch tulip mania to the bursting of the internet bubble. In some corners, there are concerns that the momentum accrued this year by AI investments is heading that way.
While it’s often said that market history doesn’t always repeat, but it often rhymes, it’s worth noting that many of the important tech and AI-adjacent names residing in the Invesco QQQ Trust (QQQ) and the Invesco NASDAQ 100 ETF (QQQM) are far more financially healthy than the names that dominate the Nasdasq-100 Index (NDX) in the 1990s.
Additionally, generative AI — most readily accessible form — is in its infancy. It may be too early to be calling for bubbles for stocks and exchange traded funds such as QQQ and QQQM. Still, AI is a disruptive technology with a long runway of applications and growth potential.
AI Evolution Could Dispel Bubble Talk
Investing can be an emotional pursuit. With some bubbles still fresh on the minds of market participants, there’s some concern about the state of AI. However, there the technology’s evolution could be supportive of assets such as QQQ and QQQM while possibly mitigating bubble bursting.
“Gen AI is rapidly evolving into more multi-modal formats. From text-based prompts and output initially, the technology is now being used to generate images, video and audio input,” according to BNP Paribas research. “If these capabilities continue to expand, we could imagine a world where we have access to specialised virtual assistants via a smartphone or an augmented reality device.”
There is more to the potential durability of QQQ and QQQM as avenues to AI exposure. This technology is likely to experience high levels of corporate adoption. That could serve to take some of the volatility out of relying solely on consumers to embrace it. In fact, the long-term corporate case for wider AI acceptance is likely strong than it is at the consumer level.
“Gen AI can unlock new avenues of growth, and companies could do more with less. Developers can write more code per hour; customer service helpdesks can be AI-assisted and handle more questions without the intervention of a human. This drives cost efficiency,” concluded BNP Paribas. “There are also companies with proprietary data that can find ways to weave this technology into their existing offering to develop new products or improve existing ones to better retain customers.”
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