Nearly $2.5 trillion of AI-related infrastructure investment will flow through the global economy by 2028; >80% of that spending is still ahead of the market as of early 2026.
Predictor: Morgan Stanley
Prediction text
Nearly $2.5 trillion of AI-related infrastructure investment will flow through the global economy by 2028; >80% of that spending is still ahead of the market as of early 2026. | Quarterly hyperscaler capex disclosures
Key catalyst: Quarterly hyperscaler capex disclosures
Watch events: Hyperscaler capex guidance; sovereign AI infrastructure commitments; CHIPS Act / EU Chips Act disbursements.
Resolution evidence
2025 hyperscaler capex totals $300B+ across MSFT/GOOG/META/AMZN; Stargate $500B + xAI $200B + sovereign GCC deals validate trajectory.
Predictor: Morgan Stanley
Calibration plot (stated vs observed)
Evidence about this node from Morgan Stanley is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).
Reference class: ai_capability_milestone_2y
AI reaches specific named capability (intern-level / world-class programmer / etc) within 2y of stated target
Tetlock-style outside view: at TRF=1 (just predicted), outside view dominates (w_in=0.3). At TRF=0 (deadline), inside view dominates (w_in=1.0). The blend regularizes overconfident inside views toward the historical base rate.
Probability over time
Milestone chain
- 2026-02-26overdueQ1 window check-in (25%)
- 2026-04-23overdueQ2 window check-in (50%)
- 2026-06-18pendingQ3 window check-in (75%)
No downstream cascades — this prediction is a leaf in the dependency graph.
What if this resolves?
Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"
Evidence chain
Raw metadata
{
"trf": 0.6127227050582519,
"kappa": 0.5833,
"base_rate": null,
"predictor": "Morgan Stanley",
"total_llr": 1.6094379124341,
"bayesian_v2": true,
"prior_logit": 0.1881087531101633,
"bayes_factor": "2.6:1 favoring",
"blend_reason": "no reference_class linked",
"inside_prior": 0.5468890061717089,
"kappa_source": "predictor_table",
"blend_applied": false,
"contributions": [
{
"llr": 1.6094379124341,
"kappa": 0.5833,
"label": "Multiple sources converge on $700B+ for 2026; Manifold cross-check market resolved at 83% for >$300B (vs prior 55%) - pr",
"adjusted_llr": 0.9387851343228107
}
],
"evidence_kind": "intake_event_update",
"inside_source": "history_v2",
"inside_weight": 1,
"outside_weight": 0,
"posterior_prob": 0.7552652216034469,
"evidence_origin": "daily_intake",
"llm_suggestions": [
{
"polarity": "corroborates",
"status_change": "accelerated",
"evidence_strength": "strong",
"delta_prob_suggestion": 0.07
}
],
"posterior_logit": 1.126893887432974,
"predictor_brier": 0.01,
"evidence_doc_ids": [],
"inside_posterior": 0.7552652216034469,
"blended_posterior": 0.7552652216034469,
"reference_class_id": null,
"total_adjusted_llr": 0.9387851343228107,
"predictor_n_resolved": 1
}Raw metadata
{
"trf": 0.6650500679109432,
"kappa": 0.5833,
"base_rate": null,
"predictor": "Morgan Stanley",
"total_llr": -0.8109302162163288,
"grace_days": 7,
"bayesian_v2": true,
"prior_logit": 0.48761894841185965,
"bayes_factor": "1.6:1 against",
"blend_reason": "no reference_class linked",
"inside_prior": 0.6195453572459543,
"kappa_source": "predictor_table",
"n_milestones": 2,
"blend_applied": false,
"contributions": [
{
"llr": -0.4054651081081644,
"kind": "quartile_checkpoint",
"kappa": 0.5833,
"label": "Q1 window check-in (25%)",
"weight": 0.05,
"strength": "weak",
"confidence": null,
"source_url": null,
"adjusted_llr": -0.2365077975594923,
"expected_date": "2026-02-26",
"measurement_criterion": null
},
{
"llr": -0.4054651081081644,
"kind": "quartile_checkpoint",
"kappa": 0.5833,
"label": "Q2 window check-in (50%)",
"weight": 0.05,
"strength": "weak",
"confidence": null,
"source_url": null,
"adjusted_llr": -0.2365077975594923,
"expected_date": "2026-04-23",
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}
],
"evidence_kind": "metadata_milestone_miss_sweep",
"inside_source": "history_v2",
"inside_weight": 0.5344649524623397,
"outside_weight": 0.4655350475376603,
"posterior_prob": 0.5036507734437512,
"posterior_logit": 0.014603353292875043,
"predictor_brier": 0.01,
"inside_posterior": 0.5036507734437512,
"blended_posterior": 0.5036507734437512,
"reference_class_id": null,
"total_adjusted_llr": -0.4730155951189846,
"predictor_n_resolved": 1
}Network propagation neighbors
Top incoming (parents)
Edges that influence THIS node's belief
| Kind | Node | Their prob | P(c|s=T) | P(c|s=F) | Δ implied |
|---|---|---|---|---|---|
| killer | TK05 Rate Regime Persistence (10y > 5% through 2028) | 30.0% | 0.050 | 0.720 | -0.153 |
| killer | TK04 Macro Recession 2026-27 (Structural Deleveraging) | 25.0% | 0.050 | 0.720 | -0.119 |
| killer | TK14 Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates) | 20.0% | 0.050 | 0.720 | -0.086 |
| killer | TK07 Labor Political Backlash (UBI Mandate / AI Tax) | 18.0% | 0.050 | 0.720 | -0.072 |
| killer | TK10 $100T Sovereign Debt Crisis | 12.0% | 0.050 | 0.720 | -0.032 |
Top outgoing (children)
Predictions THIS node influences
No outgoing edges.
Ticker exposure
Beneficiaries (9)
Adverse (2)
Prerequisites (8)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| correlate | S_HUMANOID_ENTERPRISE_2028 | Humanoid R2: 100K+ enterprise by Nov 2028 | humanoid_deployment | — |
| correlate | S_GRID_50GW_2027 | 50GW dedicated AI/data center grid by Dec 2027 | energy_grid_expansion | — |
| correlate | S_NO_RECESSION_5Y | No NBER recession through 2031 | macro_recession | — |
| killer | TK05 | Rate Regime Persistence (10y > 5% through 2028) | — | — |
| killer | TK04 | Macro Recession 2026-27 (Structural Deleveraging) | — | — |
| killer | TK14 | Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates) | — | — |
| killer | TK07 | Labor Political Backlash (UBI Mandate / AI Tax) | — | — |
| killer | TK10 | $100T Sovereign Debt Crisis | — | — |
Dependents (0)
| Type | Pred | Title | Domain | Lag |
|---|---|---|---|---|
| No dependents | ||||
Expected milestones (1)
| Expected by | Description | Status |
|---|---|---|
| 2026-12-31 | [Capital Markets 2026-12] 2-month price performance vs semi index [CMQ_020] Hyperscaler capex guidance; sovereign AI infrastructure commitments; CHIPS Act / EU Chips Act disbur | pending |
Linked documents (10)
Raw metadata
{
"nia": false,
"qty": "~$2.5T",
"mode": "FORECAST",
"role": "Cited-Firm",
"context": "Morgan Stanley macro thesis: AI is no longer thematic tech disruption but a primary macro variable influencing global GDP, credit markets, and industrial expansion.",
"to_year": 2028,
"cited_by": "Synthesis report",
"conv_cues": "specific quantitative target; major bank",
"direction": "NUMERIC_TARGET",
"from_year": 2026,
"timeframe": "by 2028",
"conv_level": "HIGH",
"milestones": [
{
"kind": "quartile_checkpoint",
"label": "Q1 window check-in (25%)",
"status": "overdue",
"weight": 0.05,
"ordinal": -3,
"source_id": null,
"expected_date": "2026-02-26",
"observed_date": null,
"miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
"miss_emitted_by": "metadata_milestone_sweep"
},
{
"kind": "quartile_checkpoint",
"label": "Q2 window check-in (50%)",
"status": "overdue",
"weight": 0.05,
"ordinal": -2,
"source_id": null,
"expected_date": "2026-04-23",
"observed_date": null,
"miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
"miss_emitted_by": "metadata_milestone_sweep"
},
{
"kind": "quartile_checkpoint",
"label": "Q3 window check-in (75%)",
"status": "pending",
"weight": 0.05,
"ordinal": -1,
"source_id": null,
"expected_date": "2026-06-18",
"observed_date": null
},
{
"kind": "event",
"label": "Nearly $2.5 trillion of AI-related infrastructure investment will flow through the global economy by 2028; >80% of that spending is still ah",
"status": "pending",
"weight": 1,
"ordinal": 0,
"source_id": "CMQ_020",
"expected_date": "2026-08-14",
"observed_date": null
}
],
"repeat_eps": 1,
"sub_domain": "Economy",
"affiliation": "Morgan Stanley Research",
"attribution": "THIRD_PARTY_CITATION",
"granularity": "YEAR",
"source_refs": "12, 13",
"target_date": "2028-06-15T00:00:00",
"display_date": "2026-08-14",
"episode_date": "2026-04-21T00:00:00",
"key_catalyst": "Quarterly hyperscaler capex disclosures",
"parse_method": "Report midpoint",
"domain_bucket": "Markets",
"episode_title": "The Global Architecture of Machine Intelligence: Exhaustive Synthesis of AI Compute, Memory & Quantum Predictions (2023-2026)",
"fault_line_id": "F002, F003, F007",
"flag_repeated": false,
"in_5yr_window": true,
"source_report": "AI_Chip__Compute__Memory__Quantum_Predictions.md (2026-04-21)",
"appears_in_eps": "CMQ-RPT",
"futurist_phase": "Phase 2 (2027-2028)",
"is_macro_claim": false,
"total_mentions": 1,
"priority_weight": 5,
"ps_cluster_tags": [
"C5"
],
"report_evidence": "Canonical macro-capex anchor for AI infrastructure thesis — cited across sell-side community.",
"active_end_month": "2026-12",
"recent_statement": "MS April 2026 AI Market Trends report reaffirms $2.5T thesis.",
"watch_events_raw": "Hyperscaler capex guidance; sovereign AI infrastructure commitments; CHIPS Act / EU Chips Act disbursements.",
"months_from_today": 26,
"probability_layer": "Higher (in-flight)",
"active_start_month": "2026-01",
"flag_nia_bracketed": false,
"track_record_grade": "A-",
"track_record_notes": "Morgan Stanley AI research (led by Joseph Moore team) has been most-accurate among major-bank sell-side on compute capex.",
"contradicting_notes": "Macroeconomic capacity constraints (power, permitting, skilled labor) may delay realization; $2.5T assumes current pace holds.",
"flag_near_term_2027": false,
"flag_high_conviction": true,
"milestones_phase2_at": "2026-05-01T18:14:03.523234+00:00",
"milestones_derived_at": "2026-05-02T03:08:50.598727+00:00",
"reference_class_match": {
"decision": "keyword_filtered",
"computed_at": "2026-04-30T01:49:13.796883+00:00",
"best_id_unfiltered": "regulatory_freeze_window",
"best_similar