Rising long-term bond yields may signal investor expectations of an AI-driven productivity increase rather than only inflation concerns and growing government debt, according to Jacob Manoukian, U.S. head of investment strategy at JPMorgan Private Bank. Speaking at the Reuters Global Markets Forum on Thursday, Manoukian suggested that the bond market might be detecting an improved productivity cycle from current AI investment. This represents a significant shift in market sentiment, as bond yields typically reflect long-term economic expectations and productivity growth prospects.
According to the San Francisco Fed's latest data, productivity-utilization-adjusted total factor productivity grew by just 0.07% over the four quarters ending in the first quarter of 2026. This figure is not far from zero and well below the post-Golden Age era levels, indicating that despite the promising AI innovation wave, tangible productivity benefits have yet to emerge. As reported by Kansas City Fed researchers, the recent productivity pickup visible in official data is 'not yet broad-based,' with gains concentrated among a small set of industries.
San Francisco Fed researchers Aakash Kalyani and Huiyu Li analyzed nearly 500,000 corporate earnings call transcripts spanning 5,198 public firms to measure AI and productivity discussions. They found that firms with positive AI sentiment on their calls have 'substantially higher investment growth' than other public companies, with this correlation between AI-positive language and actual capital spending being real. However, the National Bureau of Economic Research surveyed corporate executives across the US, UK, Germany, and Australia, finding that more than 80% of firms report no measurable impact from AI on either employment or productivity over the past three years, even though roughly 70% of firms are actively using AI technology.
Despite widespread AI adoption, only about a third of organizations have scaled AI across multiple business units, according to a 2025 McKinsey study. The report reveals that almost two-thirds of organizations are still in experimental or pilot phases, with 64% seeing AI as a support for innovation while broad, sustainably demonstrable impact on results remains significantly less common. This implementation gap explains why employees frequently report noticeable time savings in research, writing, programming, and customer communications, but corporate-level revenue growth, profit improvement, and productivity indicators often fall short of expectations. The key challenge lies in process design, data access, responsibilities, quality control, and the ability to reorganize workflows rather than simply acquiring AI models.
The AI investment expansion is driving increased borrowing among hyperscalers as they increase spending on data centers and infrastructure. AI-related debt issuance has exceeded $220 billion this year, double last year's total, while U.S. corporate bond issuance has reached $1.68 trillion, up nearly 27% from the same period in 2025. Treasury yields have increased, with some investors suggesting that growing corporate debt supply could reduce demand for U.S. government bonds, reflecting the broader economic impact of AI-driven investment cycles.
