Investing.com — Goldman Sachs economists said Tuesday that investments in artificial intelligence agents and related infrastructure could surpass $1 trillion globally in the coming years, with U.S. companies already spending $150 billion annually on labor costs tied to the AI transition.
The bank’s Global Economics Analyst report said AI adoption will require substantial investment beyond hardware, including data infrastructure, software development, and organizational restructuring. Company statements and revenue growth at data-intelligence and cloud-service providers indicate these investments are accelerating.
Goldman estimates that executive time allocations suggest $40 billion per year in organizational capital investment. The bank projects workforce reorganization could cost $800 billion to $900 billion over the full AI adoption cycle, based on labor restructuring costs incurred so far.
Historical relationships between information and communications technology hardware and complementary investments in data, software, and organizational capital support the $1 trillion estimate for non-hardware investments, according to the report.
These non-hardware investments in AI represent intangible capital, which has grown to roughly equal traditional capital expenditure in G10 economies, based on EU KLEMS data. Much of the growth in intangible investment over the past 20 years reflects increased spending on organizational capital and software management.
Goldman said increased intangible investment typically produces a productivity curve where resources are initially directed toward internal investments needed for technology adoption, much of which is not measured in gross domestic product. The recent acceleration in U.S. productivity growth may therefore be understated, the bank said.
Companies that invest more effectively in intangible capital have historically captured larger revenue shares, achieved higher productivity, and generated better returns on investment, partly through reduced labor costs, Goldman said.
The bank’s equity analysts previously concluded that companies focused on data structure and AI deployment will be key to unlocking AI’s economic value, while increased market concentration and lower labor costs could drive higher valuations for companies that invest more effectively in AI agents.
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