Survey blueprint: collapsing 42 categories into a fielding instrument
The wiki keeps 42 fine-grained categories (good for a buyer’s map). A CTO usage/evaluation survey can’t ask 42 questions — respondents fatigue and overlap confuses them. This page is the real instrument: ~16 questions, each mapping to one or more wiki categories, with the answer shortlist and design notes. Reuse the standard scale on every question:
Scale (multi-select per option): Interested · Considering/evaluating · Pilot/implementing · In production · Would recommend · Would not recommend.
Design rule: ask about what a fund buys as one decision. Where the wiki splits for precision (DSPM vs DLP; the five agent rows), the survey merges or gates with a screener.
Screener (route the respondent)
- S1. Do staff use public/enterprise AI tools today? (yes → everyone gets the core)
- S2. Do you do RAG over internal data? (gates the retrieval/data questions)
- S3. Do you build/run agents that take actions? (gates the agent-security questions)
- S4. Are you under SR 11-7 / formal model risk or heavy allocator DD? (gates governance depth)
Core questions (everyone)
| # | Question (category) | Maps to wiki | Shortlist (answer options) |
|---|---|---|---|
| Q1 | Enterprise AI assistant | enterprise-ai-assistant | ChatGPT Enterprise, Claude Enterprise, M365 Copilot, Gemini Enterprise, Amazon Q, Glean, Perplexity, Other |
| Q2 | AI gateway | ai-gateway | Portkey (Palo Alto), LiteLLM, Kong, TrueFoundry, Cloudflare, F5, OpenRouter, Other |
| Q3 | AI access governance / shadow-AI + prompt DLP | ai-access-governance + dlp | WitnessAI, Harmonic, Aurascape, Cyberhaven, Nightfall, Prompt Security (SentinelOne), Zscaler/Netskope-native, Other |
| Q4 | AI runtime security (firewall) | ai-runtime-security | Prisma AIRS (Palo Alto), HiddenLayer, WitnessAI, Pillar, Cisco AI Defense, Lakera (Check Point), Lasso, Other |
| Q5 | LLM observability & eval | llm-observability | Langfuse (ClickHouse), LangSmith, Arize, Braintrust, Datadog, Helicone, Fiddler, Other |
| Q6 | AI governance / model risk | ai-governance-platform (+comms-surveillance sub-q) | Credo AI, Holistic AI, ModelOp, IBM watsonx.governance, OneTrust, Vanta, Monitaur, Other |
| Q7 | AI-aware network security / SASE | network-security-sase | Palo Alto, Zscaler, Netskope, Cloudflare, Cisco, Cato, Forcepoint, Other |
Data & retrieval (gated by S2 = RAG)
| # | Question | Maps to | Shortlist |
|---|---|---|---|
| Q8 | DSPM + DLP + data-access governance (one question, note overlap) | dspm + dlp + data-access-governance | Microsoft Purview, Varonis, Cyera, BigID, Securiti (Veeam), Sentra, Concentric, Immuta, Other |
| Q9 | Entitlement-aware RAG | entitlement-aware-rag | Glean, Microsoft Graph/Copilot, Knostic, Gemini Enterprise, Amazon Q, Other |
Agent stack (gated by S3 = agents)
| # | Question | Maps to | Shortlist |
|---|---|---|---|
| Q10 | AI-SPM / agent security (merges 2 wiki rows) | ai-spm + agent-runtime-security | Zenity, Noma, Prisma AIRS, Cranium, Lasso, Operant, Straiker, Other |
| Q11 | Agent authorization & tool/MCP access (merges 3 wiki rows) | authorization-engine + mcp-gateway + tool-identity-integration | Cerbos, OPA/Styra, Permit.io, Oso, Kong MCP, Solo.io agentgateway, Arcade, Composio, Other |
| Q12 | Non-human / agent identity | non-human-identity | CyberArk (Palo Alto), Astrix (Cisco, pending), Aembit, Oasis, Token, Natoma (Snowflake), Entro, Clutch, Other |
Foundation & governance (gated / as relevant)
| # | Question | Maps to | Shortlist |
|---|---|---|---|
| Q13 | Identity & IGA | identity-access + identity-governance | Entra, Okta, Ping, SailPoint, Saviynt, Veza, ConductorOne, Other |
| Q14 | AI SOC / security automation | ai-soc-analysts | Prophet, Dropzone, 7AI, Radiant, Simbian, CrowdStrike Charlotte, Palo Alto AgentiX, Torq, Other |
| Q15 | Comms surveillance (AI-prompt capture) | comms-surveillance | Behavox, SteelEye, NICE Actimize, Theta Lake, Shield, Relativity Trace, Other |
| Q16 | Enterprise browser / extension | enterprise-browser + browser-security-extension | Island, Prisma Access Browser, Menlo, Seraphic, Chrome Enterprise, Edge for Business, LayerX, Other |
Categories intentionally NOT given their own question
Folded into the above or out of scope for a usage survey:
- Foundation incumbents (EDR, SIEM, secrets, SSPM, supply-chain, vendor-risk, GRC, anti-deepfake) — mostly “already owned”; ask only if the survey’s scope includes the general security estate.
- AI red-teaming (ai-red-teaming) — fold into Q4/Q5 unless surveying AI builders; it’s a low-fit, developer-tool category for most funds.
- Retrieval infra (content-sources, vector-retrieval) — plumbing, not a governance choice.
- Process rows (trust zones, risk tiers, promotion gates, HITL, AUP) — better as maturity questions (“do you have a written AUP? risk-tiering? trust-zone design?”) than vendor questions.
Cross-cutting design notes
- Label acquired options with their parent — many answer options are now product lines, not companies (see ai-security-m-and-a-map). A bare “Lakera” or “Portkey” dates the survey.
- Expect double-counting where one vendor answers several questions (Palo Alto, Microsoft, Cyberhaven, WitnessAI, Lasso, Glean) — reconcile in analysis, not by forcing single-select.
- Overlap traps to pre-empt: DSPM↔DLP↔access-governance (Q8); runtime↔red-team (Q4/Q5); the five agent rows (Q10/Q11/Q12); assistant↔entitlement-RAG (Q1/Q9).
History
- [2026-06-28] Created in Phase 4 per taxonomy-gaps Q4 — the fielding instrument behind the 42-category wiki.