SKN | Bank of America Warns AI Investment Returns Could Face Pressure as Competition Intensifies

Key Takeaways:

• AI infrastructure spending expectations have surged, with projected hyperscaler capital expenditure reaching approximately $1 trillion over the next 12 months, according to Bank of America.
• Falling AI service prices and stronger competition could challenge profitability, even as usage and adoption continue to expand.
• The central risk is capital efficiency: rising investment must translate into sustainable revenue and returns rather than excess capacity and weaker pricing power.

Bank of America has warned that the artificial intelligence investment cycle could face mounting pressure as capital spending accelerates, competition intensifies and prices for AI services decline. In a client note, investment strategist Sebastian Raedler drew comparisons with previous periods of large-scale infrastructure investment, when ambitious spending initially supported expansion but eventually exposed businesses to excess capacity and declining financial returns. For sophisticated investors, the analysis shifts attention from the scale of AI adoption to the sustainability of the returns generated by the capital being deployed.

AI Infrastructure Spending Reaches Historic Scale

According to Bank of America, consensus expectations for hyperscaler capital expenditure over the next 12 months have increased from $330 billion in early 2025 to approximately $1 trillion. The latest estimate represents around 3% of US gross domestic product, exceeding the relative scale of two historical investment cycles highlighted by the bank.

By comparison, railroad investment during the 1870s was estimated at 2.2% of US GDP, while spending associated with the technology expansion of the 1990s represented approximately 1.1%. These comparisons underscore the exceptional scale of current AI infrastructure commitments. However, investment magnitude alone does not establish whether future revenues will justify the expenditure.

Raedler’s analysis emphasizes a recurring pattern: strong initial returns can attract additional capital, intensifying competition and eventually weakening profitability. The implication is that continued technological progress does not necessarily guarantee attractive financial outcomes for every company financing the expansion.

Falling AI Prices Challenge Profitability

Competition in AI models is emerging as a potential source of pressure. Bank of America highlighted the growing presence of Chinese developers offering open-weight models, which is contributing to a more competitive market for AI capabilities.

The bank also reported that average AI token prices have declined by approximately 50% since the summer, even as the volume of tokens processed by AI systems continues to increase. Lower prices may encourage broader adoption, but they also reduce revenue generated per unit of usage. Whether higher volumes can compensate for this decline is therefore an important consideration for the economics of AI services.

The comparison with cloud computing during the 2010s is instructive. According to the bank, barriers to entry helped limit competition in that market and supported profitability. The AI model market may face a different competitive structure, making sustained pricing power less certain.

Why Capital Efficiency Matters to Investors

Bank of America’s analysis raises a broader question about the relationship between corporate AI spending and commercial demand. If lower prices stimulate sufficient additional usage, providers may offset some pressure on revenue per token. If demand growth proves insufficient, however, companies could face weaker monetization despite substantial infrastructure commitments.

The available analysis does not establish whether increased usage will fully offset declining prices. Investors should therefore distinguish between evidence of technological adoption and evidence of durable profitability. As the AI investment cycle develops, capital discipline, pricing trends and the ability to convert infrastructure spending into sustainable cash flows will remain important indicators of financial resilience. For a confidential discussion regarding your cross-border banking structure and global wealth management arrangements, contact our senior advisory team.