R0042/2026-04-01/Q001 — Self-Audit¶
ROBIS 4-Domain Audit¶
Domain 1: Eligibility Criteria¶
Rating: Low risk
| Criterion | Assessment |
|---|---|
| Criteria defined before searching | Yes — targeted major consultancy surveys (McKinsey, Gartner, Deloitte, KPMG, Forrester) as specified in the query |
| Criteria consistent throughout | Yes — applied same relevance threshold to all sources regardless of findings |
| Scope appropriate | Yes — covered 2024-2026 timeframe as appropriate for current enterprise AI landscape |
Notes: The query itself specified the target sources, which constrained the eligibility criteria appropriately.
Domain 2: Search Comprehensiveness¶
Rating: Some concerns
| Criterion | Assessment |
|---|---|
| Multiple search strategies used | Yes — three distinct searches targeting industry surveys, enterprise motivations, and sovereign AI |
| Searches designed to test each hypothesis | Partially — searches were designed to find evidence rather than test specific hypotheses, appropriate for open-ended query mode |
| All results dispositioned | Yes — 30 results returned, all dispositioned (10 selected, 20 rejected) |
| Source diversity achieved | Partially — achieved consultancy diversity (Deloitte, KPMG, Menlo Ventures) but could not access McKinsey content (timeout) or Forrester (paywalled) |
Notes: The inability to access McKinsey's full report and Forrester's paywalled content creates a gap. Three of the five named consultancies in the query could not be fully accessed.
Domain 3: Evaluation Consistency¶
Rating: Low risk
| Criterion | Assessment |
|---|---|
| All sources scored using same framework | Yes — GRADE reliability/relevance + bias domains applied to all 5 sources |
| Evidence typed consistently | Yes — Statistical and Analytical types used consistently |
| ACH matrix applied | Yes — all evidence mapped to all 3 hypotheses |
| Diagnosticity analysis performed | Yes — most and least diagnostic evidence identified |
Notes: Vendor sources (Allganize, Deepset) received appropriately higher COI ratings.
Domain 4: Synthesis Fairness¶
Rating: Low risk
| Criterion | Assessment |
|---|---|
| All hypotheses given fair hearing | Yes — H1 (consensus exists) was tested seriously despite being ultimately eliminated |
| Contradictory evidence surfaced | Yes — Menlo Ventures buy-vs-build data included as counterpoint to private AI narrative |
| Confidence calibrated to evidence | Yes — Medium confidence reflects the gap in direct deployment-location survey data |
| Gaps acknowledged | Yes — missing McKinsey, Forrester, and absence of dedicated private AI motivation surveys documented |
Notes: The three-tier motivation structure attempts to represent the evidence as-is rather than impose a false consensus.
Domain 5: Source-Back Verification¶
Rating: Low risk
| Source | Claim in Assessment | Source Actually Says | Match? |
|---|---|---|---|
| SRC01 | 42% report strategic readiness | "42% of companies report strategic readiness for AI adoption" | Yes |
| SRC02 | 55% of enterprises avoid AI due to security | "55% of enterprises avoid at least some AI use cases due to data security concerns" (citing Deloitte) | Yes |
| SRC03 | AI spending $114M to $130M | "Average enterprise AI spending climbed from $114M (Q1) to $130M (Q3)" | Yes |
| SRC05 | 76% buy vs build | "76% purchased rather than built internally" | Yes |
Discrepancies found: 0
Corrections applied: None needed
Unresolved flags: None
Notes: All key statistics verified against source material. The Deloitte 55% figure cited by Allganize is attributed correctly as a Deloitte finding reported by Allganize.
Overall Assessment¶
Overall risk of bias: Low risk
The research process was conducted consistently across all sources. The main limitation is search comprehensiveness — two of the five named consultancies could not be fully accessed. This is documented as a gap rather than hidden. The inclusion of counter-evidence (Menlo Ventures buy-vs-build data) demonstrates synthesis fairness.
Researcher Bias Check¶
- Infrastructure bias: The researcher's infrastructure mindset could predispose toward over-emphasizing private deployment advantages. Mitigated by including the Menlo Ventures finding that 76% of enterprises are moving toward buying rather than building.
- Confirmation bias risk: The researcher is investigating sycophancy as a private AI motivation (Q002, Q003), which could create an anchoring effect where Q001 results are unconsciously shaped to support subsequent queries. Mitigated by documenting that behavioral customization appears only in the sovereign AI literature, not in mainstream consultancy surveys.