Topic: Capital Markets-Company & Equity Research
Report type: AWS Cloud and AI Investment Economics (AWS 云计算与 AI 投资经济性分析)

Please prepare an in-depth fundamental research report centered on the theme of "the economics and fundamental impact of AWS AI infrastructure investment," and systematically address the following questions:

1. Based on key takeaways from AWS re:Invent, summarize AWS’s latest strategic developments in AI infrastructure, including in-house chips (e.g., the Trainium series), computing platforms, and the AI technology stack. Explain how these developments differ from the traditional cloud computing model.
2. From the perspectives of capital expenditure and unit economics, analyze the impact of large-scale AI investments on cost structure, depreciation dynamics, EBITDA/EBIT margins, and free cash flow. Explain the mechanism of "short-term profitability pressure versus medium- to long-term profit release," and identify key forward-looking operating indicators from the perspective of operational data.
3. Considering the growth of AI workloads, changes in customer mix, and the competitive landscape, evaluate the impact of AI-related businesses on medium-term revenue growth and return on invested capital (ROIC). Discuss the potential re-rating logic for AWS and Amazon’s overall valuation.
4. Identify key risks and uncertainties (e.g., compute supply constraints, power and infrastructure limitations, AI pricing pressure, and intensifying competition), and assess the sensitivity of Amazon’s medium- to long-term fundamentals to these factors.

Requirements: The analysis should focus on underlying mechanisms, maintain logical consistency with clearly stated assumptions, and demonstrate an integrated understanding of technological evolution, financial structure, and capital market dynamics.

## Evaluation Criteria for *AWS AI Infrastructure Investment Economics and Fundamental Impact*

This framework evaluates deep research reports on AWS AI infrastructure investment. It emphasizes **tech–financial–valuation linkage**, **verifiable unit economics**, **short-term pressure vs. medium-term release**, and **risk scenarios with monitoring indicators**. The framework includes **5 primary dimensions and 14 secondary dimensions, totaling 100 points**.

---

### 1. Technical Strategy and Information Extraction (25 points)

#### (1) Key takeaways from re:Invent 2025 (8 points)
- **7–8**: Accurately extracts relevant disclosures (chips, platforms, supply, pricing, ecosystem), distinguishes facts vs. management views, provides sources, and clarifies uncertainty.
- **4–6**: Covers main points but weak linkage to business implications.
- **0–3**: Generic or inaccurate summary, insufficient for analysis.

#### (2) Depth of AI infrastructure architecture understanding (10 points)
- **9–10**: Explains chip strategy (e.g., Trainium), workload differences, bottlenecks (network, memory, power), and linkage to upper-layer services, with quantifiable variables.
- **6–8**: Covers components but lacks constraint/mechanism analysis.
- **0–5**: Superficial or concept-heavy without substance.

#### (3) Identification of paradigm shift vs. traditional cloud (7 points)
- **6–7**: Clearly identifies shifts (capex front-loading, utilization-driven economics, pricing changes, ecosystem lock-in) and links to financial impact.
- **3–5**: Partial qualitative insight without financial linkage.
- **0–2**: Fails to recognize key differences.

---

### 2. Capex and Unit Economics Analysis (30 points)

#### (1) Capex breakdown and accounting rigor (10 points)
- **9–10**: Breaks down AI investments (DC, servers, networking, power, facilities) with clear capitalization scope and linkage to delivery capacity.
- **6–8**: Reasonable breakdown but lacks granularity or accounting clarity.
- **0–5**: Generic capex discussion.

#### (2) Depreciation and P&L transmission (10 points)
- **9–10**: Clearly explains D&A impact (EBIT vs EBITDA), timing of asset ramp and utilization, and short-term margin pressure vs. medium-term release.
- **6–8**: Understands direction but lacks dynamic modeling.
- **0–5**: Misuses EBITDA/EBIT or lacks mechanism.

#### (3) Unit economics model and testability (10 points)
- **9–10**: Builds reproducible model (TCO, utilization, pricing, power, depreciation) with sensitivity analysis.
- **6–8**: Includes key variables but incomplete framework.
- **0–5**: Lacks verifiable economic model.

---

### 3. Growth, Competition, ROIC, and Valuation (25 points)

#### (1) AI workload growth and revenue modeling (10 points)
- **9–10**: Quantifies growth drivers (training vs inference, customer mix, pricing, backlog) with measurable indicators.
- **5–8**: Describes drivers but lacks quantification.
- **0–4**: Generic growth narrative.

#### (2) Competitive dynamics and pricing pressure (7 points)
- **6–7**: Analyzes competition across supply, chips, ecosystem, pricing, and lock-in, linking to growth, margins, and efficiency.
- **4–5**: Basic comparison without financial linkage.
- **0–3**: Weak or incorrect analysis.

#### (3) ROIC and valuation re-rating framework (8 points)
- **7–8**: Links ROIC to AI investment and builds valuation logic (growth, margins, capital efficiency), identifying triggers.
- **4–6**: Mentions ROIC/valuation but lacks decomposition.
- **0–3**: Weak or inconsistent framework.

---

### 4. Methodology, Assumptions, and Data Quality (10 points)

#### (1) Assumptions clarity and consistency (4 points)
- **4**: Key assumptions clearly stated, consistent, and linked to sensitivity.
- **2–3**: Partial or weakly justified assumptions.
- **0–1**: Missing or inconsistent assumptions.

#### (2) Data quality and reproducibility (4 points)
- **4**: Reliable sources, clear definitions, and reproducible calculations.
- **2–3**: Reasonable data but incomplete transparency.
- **0–1**: Unverifiable or unsupported data.

#### (3) Structure and model transparency (2 points)
- **2**: Clear structure, charts/models support logic.
- **1**: Acceptable but scattered.
- **0**: Poor structure.

---

### 5. Risk and Scenario Analysis (10 points)

#### (1) Risk identification and transmission (6 points)
- **5–6**: Covers key risks (supply, power, capex overruns, pricing, competition, regulation) with clear impact paths.
- **3–4**: Lists risks without mechanism.
- **0–2**: Weak or irrelevant risks.

#### (2) Scenario analysis and monitoring indicators (4 points)
- **4**: Provides at least two scenarios with quantified impact on margins/FCF/ROIC and clear tracking indicators.
- **2–3**: Scenarios present but not quantified.
- **0–1**: No scenario analysis.