# Sovereign AI — Inflation & gaps ## Six patterns in the gap between announced and disbursed How each announcement inflates: the six-pattern decomposition of the gap between what a program announced and what it will disburse, attributed per program with per-pattern provenance and the editorial framework stated on the page. Cite PrintScreenshot For each sovereign-AI program with an attributed gap, the share of its announced-versus-disbursement gap attributed to each of six inflation patterns, with the confidence tier of every attribution. Program Phasedin 21 · leads 14 Aspirationalin 16 · leads 7 Financing-stalledin 9 · leads 0 Otherin 7 · leads 5 Chip-conditionalin 2 · leads 1 Vaporwarein 1 · leads 1 Gap led by phased rollout **— 14 programs** Norway 100% · analyst-inferred Italy 90% · primary-source-anchored 10% · analyst-inferred Singapore 85% · primary-source-anchored 15% · analyst-inferred Canada 80% · primary-source-anchored 20% · analyst-inferred Germany 80% · primary-source-anchored 20% · analyst-inferred EuroHPC (EU-wide) 75% · primary-source-anchored 25% · analyst-inferred Taiwan 75% · primary-source-anchored 25% · analyst-inferred Australia 70% · analyst-inferred 30% · analyst-inferred India 70% · primary-source-anchored 30% · analyst-inferred Spain 70% · primary-source-anchored 30% · analyst-inferred United Kingdom 70% · primary-source-anchored 30% · analyst-inferred United States 70% · primary-source-anchored 30% · analyst-inferred Japan 60% · primary-source-anchored 25% · analyst-inferred 15% · analyst-inferred Mexico 60% · analyst-inferred 40% · analyst-inferred Gap led by aspirational **— 7 programs** France 20% · primary-source-anchored 75% · primary-source-anchored 5% · analyst-inferred United Arab Emirates 20% · primary-source-anchored 70% · primary-source-anchored 10% · primary-source-anchored Vietnam 30% · analyst-inferred 70% · analyst-inferred South Korea 25% · primary-source-anchored 65% · analyst-inferred 10% · analyst-inferred Brazil 60% · analyst-inferred 40% · analyst-inferred Saudi Arabia 25% · primary-source-anchored 60% · primary-source-anchored 15% · analyst-inferred Malaysia 50% · analyst-inferred 50% · analyst-inferred Gap led by other **— 5 programs** Africa (regional) 100% · Scrutica-editorial attribution NATO + AUKUS 100% · Scrutica-editorial attribution Poland 100% · Scrutica-editorial attribution Sweden 100% · Scrutica-editorial attribution Ukraine 100% · analyst-inferred Gap led by chip-allocation-conditional **— 1 program** China 30% · analyst-inferred 20% · Scrutica-editorial attribution 50% · primary-source-anchored Gap led by vaporware **— 1 program** Indonesia 50% · primary-source-anchored 50% · primary-source-anchored _Plate III._ Bar length is the share of a program’s announced-versus-disbursement gap attributed to the pattern. Each row sums to its own gap, so rows compare by shape; the dollar amounts behind them differ. Ink weight carries the confidence: solid = anchored in the announcement’s own text or a primary source (22 of 56 attributions), wash = analyst-inferred from public evidence (29), hollow = Scrutica’s editorial attribution (5). The six-pattern taxonomy (v2026-05-20) is itself an editorial framework; definitions, per-program provenance, and every source link are in the working decomposition below. Six further programs have no gap attribution in the manifest, and two are not yet assessed — 36 programs tracked in all. The Programs view isolates the government-only portion of each headline and reads the reality ratio off it. This view asks what produced the gap: which of six named patterns the shortfall decomposes into (private capital relabeled as public, foreign direct investment folded in, credit lines, timeline aspiration, and so on). Each attribution has its own source and a confidence tier, and the framework is written out on the page. ### Working detail: per-program decomposition with sources Cross-program decomposition ## Inflation decomposition scorecard A 6-pattern taxonomy applied to each program’s announced-vs-deployed gap. Each program’s gap decomposes into one or more named patterns whose percentages sum to 100% of the program’s gap. The taxonomy itself is a Scrutica editorial framework; per-row attributions have a source URL, an accessed-at date, and a confidence rating. The financing-type breakdown on the per-country cards (government / private / FDI / credit) is a separate decomposition; this scorecard shows the gap-shape patterns that breakdown does not capture. Programs 34 36 sovereign vehicles tracked With announced-vs-deployed gap 28 6 executing without material gap Primary-source attributions 28 of 62 total · confidence tier 1 Editorial attributions 5 Scrutica-editorial (tier 3) where sources are thin [How this is derived↗](/methodology#sovereign-inflation-decomposition "How this is derived: sovereign-AI inflation decomposition. Announced-vs-deployed gap read through a six-pattern editorial taxonomy with per-attribution confidence.") Portfolio frequency ### Which patterns dominate across the 28 programs with a gap Aspirational 16/ 28 7 dominant · avg 41% when present Phased rollout 21/ 28 14 dominant · avg 60% when present Financing-stalled 9/ 28 0 dominant · avg 26% when present Chip-allocation-conditional 2/ 28 1 dominant · avg 30% when present Vaporware 1/ 28 1 dominant · avg 50% when present Other 7/ 28 5 dominant · avg 79% when present Per-program decomposition ### Pattern allocation per program (% of announced-vs-deployed gap) Each row sums to 100% across the patterns present for that program. Hover or focus a cell to read the per-attribution provenance and notes. Programs without a material gap (committed ≈ disbursed ≈ announced) are excluded from the matrix and counted in the header above. AEUAE 70% — view full provenance20% — view full provenance10% — view full provenance CNChina 50% — view full provenance~30% — view full provenance~20% — view full provenance FRFrance 75% — view full provenance20% — view full provenance~5% — view full provenance JPJapan 60% — view full provenance~25% — view full provenance~15% — view full provenance KRSouth Korea ~65% — view full provenance25% — view full provenance~10% — view full provenance SASaudi Arabia 60% — view full provenance25% — view full provenance~15% — view full provenance AUAustralia ~70% — view full provenance~30% — view full provenance BRBrazil ~60% — view full provenance~40% — view full provenance CACanada 80% — view full provenance~20% — view full provenance DEGermany 80% — view full provenance~20% — view full provenance ESSpain 70% — view full provenance~30% — view full provenance EUEU-Wide 75% — view full provenance~25% — view full provenance GBUnited Kingdom 70% — view full provenance~30% — view full provenance IDIndonesia 50% — view full provenance50% — view full provenance INIndia 70% — view full provenance~30% — view full provenance ITItaly 90% — view full provenance~10% — view full provenance MXMexico ~60% — view full provenance~40% — view full provenance MYMalaysia ~50% — view full provenance~50% — view full provenance SGSingapore 85% — view full provenance~15% — view full provenance TWTaiwan 75% — view full provenance~25% — view full provenance USUnited States 70% — view full provenance~30% — view full provenance VNVietnam ~70% — view full provenance~30% — view full provenance AF\*Africa (Regional) ~100% — view full provenance NATONATO/AUKUS ~100% — view full provenance NONorway ~100% — view full provenance PLPoland ~100% — view full provenance SESweden ~100% — view full provenance UAUkraine ~100% — view full provenance AspirationalPhased rolloutFinancing-stalledChip-allocation-conditionalVaporwareOther Portfolio reading ### Dominant patterns across regional clusters Phased rollout dominates 14 programs: Australia · Canada · Germany · Spain · EU-Wide · United Kingdom · +8 more Aspirational dominates 7 programs: UAE · Brazil · France · South Korea · Malaysia · Saudi Arabia · +1 more Other dominates 5 programs: Africa (Regional) · NATO/AUKUS · Poland · Sweden · Ukraine Vaporware dominates 1 program: Indonesia **Regional reading.** Gulf programs (UAE, KSA) skew Aspirational and Chip-allocation-conditional: headline 5 GW / 600K-GPU framing with an operationally smaller Phase 1. The post-Oct-2023 BIS-authorization gate now splits the two: the UAE moved to Country Group A:5 on July 10, 2026 (91 FR 43034), making AI-chip exports license-free to supplement-no.-8 approved entities, while KSA still runs on bespoke case-by-case licenses. South & Southeast Asia (India, Indonesia, Vietnam, Malaysia) skew Phased (where execution is real) versus Financing-stalled or Vaporware (where capital and counterparties aren’t yet identified). Western Europe (France, Germany, UK, EuroHPC) skews Phased with smaller Aspirational residuals; the €109B France headline is the outlier that drags the regional average toward aspirational. East Asia (China, Japan, Korea) skews Chip- allocation-conditional (China specifically) and Phased (Japan, Korea). Framework and methodology ## Inflation-decomposition taxonomy (v2026-05-20) The 6-pattern taxonomy is a Scrutica editorial framework, not an industry standard. Categories are not mutually exclusive. Per-pattern percentages partition the announced-versus-deployed gap (so attributions for a single program sum to 100% of the gap, with the gap itself implicit in committed/disbursed substrate). Where a program has no gap (disbursed ≈ announced), the row shows pct=0 across patterns and a no\_gap flag. Where the literature is silent, the program is marked unclassified with an explicit reason. Aspirational Public announcement of a future-target capacity with no operational deployment yet, OR the announced number includes a capacity target whose construction has not commenced. Phase 1 may be commissioned, but the headline-shaping bulk is forward-target. Example: UAE Stargate $500B (5 GW campus aspiration; only Phase 1 200MW under construction) Phased rollout Multi-phase plan where Phase 1 (or earlier) is operational and on schedule; Phase N is forward-target but not aspirational because the multi-year build cadence is itself the disbursement plan. Distinguished from Aspirational by the presence of a substantiated multi-phase budget schedule. Example: IndiaAI Mission (38K GPUs operational, 100K target end-2026, on track per IndiaAI CEO disclosure) Financing-stalled Announcement carries deployment intent but financing closure has not arrived — SWF allocation pending, sovereign-debt instrument not yet placed, parliamentary appropriation deferred, chip-supplier contract un-priced. Distinguished from Aspirational by the presence of operational intent rather than future-capacity branding. Example: Indonesia Sovereign AI Fund planned 2027-2029, not established Chip-allocation-conditional Announcement contingent on BIS / chip-supplier approval (export license, NVIDIA allocation slot, foundry-capacity commitment). Distinguished from financing-stalled by the constraint being a supplier or regulatory authorization rather than capital. Example: Saudi HUMAIN ramp beyond the bespoke Nov 2025 35K-GB300 license remains authorization-gated. The UAE's parallel gate converted on July 10, 2026 to license-free approved-entity treatment under Country Group A:5 (91 FR 43034), leaving an entity-list + April 6, 2027 renewal condition rather than per-license approval Vaporware Announcement with no substantive substrate — no facility, no operator, no allocation. Distinguished from financing-stalled by the absence of identifiable counterparties. Example: Various smaller-state announcements where the program-name does not resolve to a procurement vehicle Other Catch-all for cases that don't fit (joint-venture-pending, regulatory-blocked, dual-currency-conversion ambiguity, sovereign-political-instability hold). Notes inline. Example: Program where deployment intent is real, financing exists, but a downstream condition unrelated to the five named patterns is the binding constraint ### Confidence rating per attribution - **Confidence 1**: announcement-text-explicit or primary-source-anchored. The attribution reads directly off a government disclosure, primary procurement record, or substrate-verified data-quality flag. - **Confidence 2**: analyst-inferred from public evidence. The attribution requires a step of inference from one or more public sources; a reader could disagree on the inference but the substrate has the underlying signal. - **Confidence 3**: Scrutica-editorial attribution where the source record is sparse. Used only when the program’s financial record is too thin to support a confident pattern call but the gap-shape is still analytically informative; marked explicitly so a reader doesn’t mistake it for a primary-source-anchored claim. ### Related research Cross-program sovereign-AI inflation framing exists at CNAS (Sovereign AI Index, periodically updated, with “announced versus disbursed” pairs), Brookings (sovereign-AI capacity assessments), CSIS (sovereign technology programs), and IDC (sovereign AI tracker, with “announced versus operational” pairs). Scrutica’s 6-pattern taxonomy is a Scrutica editorial choice, labelled as such; a reader who would prefer a different taxonomy can read the per-row notes and re-classify inline. Source citations per attribution accompany every row in the scorecard above.