The global AI investment boom has reached historic proportions, with capital spending now approaching the scale of the technology expansion seen during the 1990s.
According to BofA Global Research, artificial intelligence-related investment has increased by the equivalent of approximately 1.2 percentage points of US gross domestic product (GDP) since the first quarter of 2020.
That expansion has already surpassed the comparable investment pace of the 1970s oil boom and the shale energy boom of the 2010s.
Only the 1990s technology investment cycle, which reached approximately 1.5 percentage points of GDP over a similar period, remains ahead of today’s AI infrastructure expansion.
AI Investment Boom Approaches 1990s Technology Surge
The comparison from Bank of America highlights how artificial intelligence has become one of the most significant drivers of capital investment in recent US economic history.
Unlike purely speculative market rallies, the current expansion involves substantial spending on physical infrastructure, including data centers, computing equipment and electricity systems.
Major technology companies are investing heavily to secure the processing capacity required for developing and operating increasingly advanced AI models.
As a result, the AI investment boom is influencing construction activity, manufacturing demand and broader economic growth.
However, the historical comparison measures the scale of investment relative to GDP rather than stock market valuations or investment returns.
Data Center Construction Becomes a Major US Growth Driver
The economic impact of AI infrastructure spending extends well beyond the technology industry.
Research from the Federal Reserve estimates that investment in data center facilities and equipment contributed approximately 0.20 percentage points to US GDP growth in 2025.
For 2026, the estimated contribution increases to around 0.40 percentage points, highlighting the expanding role of digital infrastructure in the economy.
Meanwhile, data centers now represent nearly 46% of private office construction spending, compared with less than 5% approximately a decade earlier.
This dramatic shift demonstrates how artificial intelligence is reshaping commercial construction investment.
Demand for data center facilities has also increased the need for electrical equipment, cooling systems, industrial machinery and specialized construction materials.
Consequently, the AI boom is creating significant opportunities for businesses operating outside the traditional technology sector.
AI Data Centers Could Support 304,000 US Manufacturing Jobs
The expansion of AI infrastructure is also supporting employment across American manufacturing supply chains.
Researchers at Stanford University’s Institute for Economic Policy Research (SIEPR) estimate that the current pace of data center development could sustain approximately 304,000 US manufacturing jobs.
These positions are associated with the production of essential equipment and materials used to construct and operate data centers.
The benefits extend to semiconductor components, power distribution systems, cooling equipment and other industrial products.
Importantly, the employment estimate includes manufacturing activity throughout the supply chain rather than only workers employed directly at data center construction sites.
The findings suggest that AI infrastructure spending could become an increasingly important source of industrial demand across the United States.
Global Data Center Spending Could Reach $2.1 Trillion by 2028
Bank of America expects worldwide data center investment to reach approximately $1 trillion in 2026.
Furthermore, the investment bank projects spending will more than double to $2.1 trillion by 2028 as demand for AI computing infrastructure continues to accelerate.
Its longer-term projections imply a compound annual growth rate of approximately 37% between 2025 and 2030.
Such spending could provide substantial opportunities for semiconductor manufacturers, electricity infrastructure providers, construction companies and other industrial suppliers.
However, the scale of these investments also raises questions about financing requirements, infrastructure limitations and the potential returns generated by AI services.
Amazon, Google, Microsoft and Meta Lead Massive AI Spending Plans
The world’s largest cloud computing companies remain central to the artificial intelligence investment surge.
Goldman Sachs estimates that combined 2026 capital expenditures among five major technology companies could reach approximately $800 billion.
That represents an increase of roughly 52% compared with its December 2025 estimate of $527 billion.
The latest company spending plans illustrate the extraordinary scale of the expansion.
Amazon expects capital expenditures of approximately $200 billion to $220 billion in 2026.
Alphabet, Google’s parent company, is targeting between $195 billion and $205 billion, while Microsoft anticipates spending approximately $175 billion to $190 billion.
Meta Platforms expects investment of around $130 billion to $145 billion, and Oracle projects capital expenditures between $50 billion and $70 billion.
Together, these companies are making substantial financial commitments to expanding cloud infrastructure, data center capacity and AI computing systems.
Although these budgets support artificial intelligence development, they may also include investments in other corporate infrastructure and operations.
Morgan Stanley Expects AI Spending Growth to Slow by 2028
Despite the extraordinary pace of investment, Morgan Stanley expects growth in AI infrastructure spending to moderate over the coming years.
The investment bank forecasts that capital expenditure growth among major cloud providers could approach 100% year over year in 2026.
However, that growth rate is projected to slow to approximately 60% in 2027 and 14% in 2028.
Importantly, slower growth does not necessarily indicate that companies will reduce their overall spending.
Instead, the forecasts suggest that investment could continue increasing from an already elevated base, although at a less aggressive pace.
Morgan Stanley equity strategist Nicholas Lentini believes companies benefiting from AI infrastructure demand could continue receiving upward revisions to their revenue and earnings forecasts.
This outlook reflects expectations that substantial investment in computing capacity will continue supporting businesses across the AI supply chain.
Wall Street Has Repeatedly Underestimated AI Capital Spending
Morgan Stanley also highlighted the difficulty analysts have faced when forecasting the expansion of AI investment.
In both 2024 and 2025, actual capital expenditure growth exceeded 50%, even though initial forecasts suggested increases of approximately 20%.
These substantial differences demonstrate how quickly major technology companies have accelerated their investment plans.
Demand for advanced computing resources, competitive pressure and expectations for future AI adoption have contributed to repeated upward revisions.
As a result, investment forecasts may continue changing as technology companies reassess their infrastructure requirements.
AI Investment Outlook Remains Strong Despite Slower Growth Forecasts
The latest research suggests that artificial intelligence has developed into one of the largest capital investment cycles in modern economic history.
Spending on data centers, semiconductor equipment and supporting infrastructure is now influencing US economic growth, manufacturing employment and global corporate investment strategies.
Although Morgan Stanley expects the pace of expenditure growth to moderate through 2028, overall investment levels could remain historically elevated.
For investors, an important distinction is whether slowing spending growth reflects a maturing expansion or weakening demand for AI infrastructure.
The long-term outlook will depend on how effectively technology companies convert their enormous capital investments into revenue, productivity improvements and sustainable profitability.
For now, the AI investment boom continues to approach the scale of the 1990s technology expansion, underscoring the growing economic significance of artificial intelligence.
