Goldman Sachs, a global investment bank based in New York City, United States, has projected that worldwide spending on non-hardware artificial intelligence (AI) could exceed $1 trillion, signalling a major shift in how the AI economy is evolving beyond chips and infrastructure into software, services, and large-scale corporate transformation across industries.
“The AI economy is shifting from building systems to embedding intelligence across entire organisations.”
The forecast highlights a turning point in the AI boom: the transition from building artificial intelligence systems to embedding them deeply into business operations, workforce structures, and broader economic systems.
According to the investment bank’s analysis, early AI investment was dominated by physical infrastructure such as semiconductors, data centres, and cloud computing capacity. However, the next phase is expected to be driven far more by “intangible” spending, such as software deployment, enterprise integration, data restructuring, cybersecurity upgrades, and organisational redesign.
This includes major costs tied to retraining employees, redesigning workflows, and implementing AI systems across entire industries. Goldman Sachs estimates that labour-related AI transformation alone is already running into the hundreds of billions of dollars globally, accounting for productivity shifts, consulting services, and enterprise restructuring efforts.
“The largest costs of AI are no longer hardware but human and organisational change.”
The bank argues that this shift represents a structural economic transformation rather than a temporary technology cycle. Unlike previous technological waves that were primarily hardware-driven, AI adoption requires companies to fundamentally rethink how they operate, making the transition both more expensive and more complex than earlier digital revolutions.
A key insight in the report is the expectation of a “productivity J-curve,” where short-term economic gains may appear limited or even temporarily negative as companies absorb high implementation costs. Over time, however, productivity improvements are expected to accelerate as AI systems become more deeply integrated into decision-making, automation, and customer-facing services.
The forecast also suggests that the benefits of AI will not be evenly distributed across the global economy. Companies that successfully adopt and scale AI technologies are likely to gain a significant competitive advantage, while those that lag behind risk losing market share despite facing similar investment pressures and disruption.
“AI will widen the gap between firms that adapt quickly and those that fail to integrate.”
For global markets, the implication is a gradual shift in leadership from hardware manufacturers that powered the early AI surge toward software companies, cloud platforms, and enterprise solution providers that enable AI deployment at scale and extract value from it.
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Ultimately, Goldman Sachs’ projection underscores a broader message: the AI revolution is entering a second phase, less visible than the semiconductor boom but potentially far more transformative. The highest costs ahead may not come from building AI systems, but from rebuilding the global economy around them.
Senior Reporter/Editor
Bio: Ugochukwu is a freelance journalist and Editor at AIbase.ng, with a strong professional focus on investigative reporting. He holds a degree in Mass Communication and brings extensive experience in news gathering, reporting, and editorial writing. With over a decade of active engagement across diverse news outlets, he contributes in-depth analytical, practical, and expository articles exploring artificial intelligence and its real-world impact. His seasoned newsroom experience and well-established information networks provide AIbase.ng with credible, timely, and high-quality coverage of emerging AI developments.