NVIDIA (NVDA.US) maintains its dominant position in the global financial sector with a market capitalization of $4.5 trillion, wielding influence that far exceeds the combined market value of 2,000 companies in the Russell 2000 index. The company is deeply held by 667 ETFs, making it one of the most widely held individual stocks in global investment portfolios. Behind this market structure lies the powerful attraction of artificial intelligence technology to industrial capital—as revealed by Morgan Stanley's latest research, the economic value creation brought by AI technology may far exceed implementation costs.

According to Morgan Stanley's calculations, the annual net economic benefits generated by AI applications alone could reach approximately $920 billion, equivalent to 28% of S&P 500 constituent companies' pre-tax earnings in 2026 (after deducting implementation costs), corresponding to a market value increase of $13-16 trillion. However, the institution's analysts emphasize that achieving this target will require several years, and the actual degree of corporate benefits remains uncertain, with risk factors that cannot be ignored.

Morgan Stanley strategists Stephen Byrd and others noted in their report that this overall value will be realized through "entirely new sources of growth, productivity, and innovation," with implementation costs accounting for approximately 5% of customer benefits already deducted. The research breaks down AI value creation into two categories: agentic AI (software systems executing virtual tasks) is expected to contribute $490 billion annually, accounting for 15% of 2026 pre-tax revenue; embedded AI (physical systems such as humanoid robots) corresponds to $430 billion, representing 13%.

Byrd emphasized that agentic AI has a broader scope of impact, while embedded AI, though covering a narrower range of occupations, is more likely to achieve automated replacement in applicable fields, with deployment costs estimated at $5 per hour.

Additionally, value creation at the industry level shows significant differentiation: consumer staples, distribution retail, real estate management, transportation, and other sectors show potential savings exceeding 100% of expected 2026 pre-tax earnings; multiple industries have potential savings exceeding 50%, while the AI impact on technology hardware, semiconductors, and other fields is relatively lower.

Morgan Stanley has accordingly created an AI value creation heat map, identifying medical equipment, transportation, consumer services, software, capital goods, automotive, and staple distribution retail as the most promising sectors. Notably, the research considers the industrial sector as an "underestimated structural beneficiary," providing support for its overweight stance.

Based on preliminary assessments, AI-driven efficiency improvements are expected to contribute 30 basis points and 50 basis points to S&P 500 net profit margins in 2026 and 2027, respectively. Morgan Stanley analysts noted that "current baseline forecasts for AI-driven margin expansion have room for upward revision." This conclusion highlights artificial intelligence's strategic position in reshaping the global industrial landscape.

It's worth noting that this technological transformation's impact on the job market may be better than expected—while some positions face replacement risks, AI is more likely to alleviate labor shortages. The report uses computer proliferation as an example: in the 1990s, this technology reduced traditional positions like secretaries and accountants but simultaneously created numerous programmer and computer scientist positions.

Microsoft, based on 200,000 anonymous conversation data points between users and the public generative AI system Bing Copilot, found through quantitative analysis that AI has the most significant impact on knowledge-intensive jobs, while work primarily involving physical labor experiences lower impact. This conclusion aligns with corporate investment trends—Wells Fargo economists observed that companies are currently prioritizing investments in software development, information processing equipment, and manufacturing facility construction in high-tech fields, with related spending exceeding the combined total of transportation and industrial equipment.

"This may just be the beginning of a high-tech production boom," economists Shannon Greene and Tim Quinlan noted. Although high-tech industries currently account for only 3% of U.S. manufacturing output, capacity expansion trends are emerging as new factory types shift toward high-end manufacturing.

From equipment investment to employment structure adjustments, artificial intelligence is reshaping the global economic landscape through multiple pathways.

Notably, among ETFs focusing on NVIDIA, several high-concentration funds stand out. The top five funds by holding percentage are: ProShares Ultra Semiconductors (USD.US) leads with 27.6%, followed by GraniteShares 2x Long NVDA Daily ETF (NVDL.US) with 26.38%, Strive US Semiconductor ETF (SHOC.US) with 24.47%, Global X PureCap MSCI Information Technology ETF (GXPT.US) holding 23.09%, and VanEck Semiconductor ETF (SMH.US) ranking fifth with 22.19%. These data confirm the market's strong recognition of NVIDIA's core position in the semiconductor and AI sectors.