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AI Cost Efficiencies Could Spur Long-Term Adoption

BY | ETF Database
07/10/2025 | 101 VIEWS
Nvidia (NVDA) recently ascending to a market capitalization of $4 trillion is the latest confirmation that the AI trade, following some curveballs earlier this year, has come roaring back. It could have even more momentum in the second half of 2025.That’s been a clear boost for ETFs like the Invesco QQQ Trust (QQQ B+) and the Invesco NASDAQ 100 ETF (QQQM B). Those funds, which feature the same, artificial-intelligence-heavy rosters, are higher by almost 5% over the past month. That proves the AI trade has been reborn. Interestingly, some of the headwinds that weighed on QQQ/QQQM AI-focused components earlier this year could be morphing into longer-ranging positives. Take the case of China’s DeepSeek. There’s considerable speculation about that company’s claims that it was able to make significant AI strides using cheap, antiquated semiconductors. But DeepSeek has prompted U.S.-based technology companies to pay closer attention to AI costs. That could bode well for long-term adoption. That’s because investors, particularly those engaged with the hyperscalers residing in QQQ and QQQM, are demanding that high-priced AI expenditures bear fruit.Declining AI Costs Could Boost QQQThere are myriad examples of disruptive technologies evolving and realizing cost efficiencies that enhanced adoption. There’s evidence that scenario is at play today in the AI realm. “Prices today for querying models are roughly one 100th on average of what they were a few years ago. As we know from economics, as prices fall, consumption tends to rise,” noted Derek Glenn, portfolio manager at BNP Paribas. “Our belief is that AI will be everywhere. It will be embedded in many systems, applications and technologies. It will touch every part of our economy. And more efficient models unlock this opportunity.” Glynn points to declining costs for processing queries and strides made in model intelligence as two of the three trends ushering in a new era of AI adoption — one that could have significant implications for assets such as QQQ and QQQM. “Fundamentally, the combination of those two reinforces this third dynamic, which is a broadening in the number and type of use cases for AI. It’s important to keep in mind this is a general-purpose technology: it’s going to impact all aspects of the economy, and it can also improve many areas of our personal lives,” added the portfolio manager. He acknowledges that the cadence of AI spending by hyperscalers is hard to project. But it’s clear those expenditures are likely to be consistent and increase, albeit modestly, over the next several years. That could be enough to drive upside for QQQ and QQQM. “Big picture, there’s still an AI arms race unfolding between these megacap technology companies. AI is a very large and still emerging opportunity and it’s likely there’s greater risk to them missing it than in overinvesting. So, we think they’re going to pursue this type of spend to secure their future,” concluded Glynn. For more news, information, and analysis, visit the ETF Education Content Hub.

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