Increased AI Capital Expenditure Will Come at the Expense of Reduced Buybacks

Overview

This report explores the growth trend of capital expenditure by S&P 500 companies in the AI sector and its impact on stock buybacks. Goldman Sachs expects that AI-related capital expenditure will increase significantly over the next few years, while stock buybacks will decrease accordingly. Additionally, the report analyzes the potential impact of M&A activity, dividend growth, and policy uncertainty on corporate cash usage.

Core views

Goldman Sachs expects that AI-driven capital expenditure growth will become one of the main directions for S&P 500 companies' cash usage, while stock buybacks will be constrained. Specifically: 1. **Capital Expenditure and R&D**: In 2026, capital expenditure by AI super-large enterprises is expected to grow by 83%, reaching $75.5 billion, accounting for 100% of their operating cash flow. Meanwhile, these companies’ buyback activities have sharply declined, falling by 64% year-on-year. 2. **Stock Buybacks**: Although overall buyback amounts have slightly increased (+3%), buybacks by AI super-large enterprises have nearly stalled, accounting for only 15% of total cash expenditure—far below the average level from 2017-2022 (27%). 3. **M&A Activity**: M&A deals remain robust, with strategic buyers announcing nearly $700 billion in M&A plans, up 140% year-on-year. Cash payments account for nearly 70% of M&A transactions. 4. **Policy Uncertainty**: The economic policy uncertainty index is at a historic high, potentially having a negative impact on companies' cash expenditure decisions. 5. **Dividend Growth**: Despite uncertainties, dividends by S&P 500 companies are expected to maintain steady growth, with growth rates of 6% and 5% in 2026 and 2027, respectively.

Analysis framework

Goldman Sachs analyzed S&P 500 companies' financial data, industry trends, and policy environment to assess the impact of growing AI capital expenditure on corporate cash usage structures. Specific methods include: 1. **Data Analysis**: Using Compustat and FactSet data to track historical changes in corporate capital expenditure, R&D, buybacks, and dividends. 2. **Model Forecasting**: Based on macroeconomic models, forecasting future trends in corporate cash usage, including growth in AI-related capital expenditure and changes in buyback activities. 3. **Policy Uncertainty Assessment**: Measuring the impact of policy uncertainty on corporate behavior through the Economic Policy Uncertainty Index. 4. **Industry Comparison**: Comparing performance across different industries in terms of capital expenditure, buybacks, and M&A activity, highlighting the particularities of AI super-large enterprises.

Methodology notes

• Industry/Industrial Analysis FrameworkSupply-demand framework

  The growth in AI capital expenditure is mainly driven by demand on the supply side—that is, companies need more hardware and infrastructure to support AI development.

  By analyzing the growth in capital expenditure in the AI sector, Goldman Sachs reveals how companies' demand for hardware and infrastructure affects cash usage structures.

• Valuation Method

  The impact of policy uncertainty on corporate value

  The report uses the Economic Policy Uncertainty Index to evaluate the impact of policy uncertainty on S&P 500 companies' cash usage decisions.

• Cycle and Economic Sentiment FrameworkInventory cycle (Kitchin)

  The growth in AI capital expenditure may be influenced by inventory cycles, especially investments in semiconductors and other hardware sectors.

  Goldman Sachs combines inventory cycle theory to explain why AI-related capital expenditure accelerates in the short term.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• META.US

  Benefiting from the growth in AI capital expenditure, META, as one of the AI super-large enterprises, will increase capital expenditure and reduce buybacks.

  Strengths

  Strong R&D capabilities and a leading market share.

  Weaknesses

  Higher policy uncertainty may affect its capital expenditure decisions.

  Comparison

  Compared to other AI super-large enterprises, META stands out in terms of capital expenditure growth.

  Risks

  Policy changes and technological competition may pose challenges to its long-term development.

Key data

• Growth in Capital Expenditure by AI Super-Large Enterprises+83%In 2026, capital expenditure by AI super-large enterprises is expected to grow by 83%.
• Decline in Buybacks by AI Super-Large Enterprises-64%In the first quarter of 2026, buyback activity by AI super-large enterprises fell by 64% year-on-year.
• Growth in S&P 500 Companies' Cash Usage+21%In 2026, cash usage by S&P 500 companies is expected to grow by 21%.
• M&A Deal Volume$700 billionFrom 2026 to date, strategic buyers have announced nearly $700 billion in M&A plans.

Impact & implications

The growth in AI capital expenditure indicates companies' high regard for future technological development, while also reflecting their cautious approach to cash usage in the current market environment. Although policy uncertainty may put pressure on some companies' spending decisions, overall, AI-related investment will remain an important theme in the coming years. Moreover, the active M&A activity shows companies' drive to achieve growth through external expansion.

Risks

• Policy uncertainty may affect companies' capital expenditure decisions.
• Global economic slowdown could lead to slower growth in AI investment.
• Rising interest rates may increase companies' financing costs.

What to watch

• The growth trend of AI-related capital expenditure.
• Changes in the policy uncertainty index.
• The sustainability and scale of M&A activity.