Data Syllabus —
What to Bring Before You Start
This is a prep guide for the Arcana AI Enterprise Pulse™. Pull the data points below before you begin so the study moves in ~30 minutes with no guessing from memory.
How to Staff It
This study is best answered by Sourcing & Procurement + AI / Technology Leadership in collaboration. Procurement brings spend, contracts, and vendor data. AI leadership brings roadmap, deployment, and impact data. Two people on different devices can complete in ~30 min wall clock; one person alone takes ~45–60 min.
Before Starting — Demographics (5 min)
| Data Point | Specificity / Source |
|---|
| Organization type & industry | Category (Technology, Finance, Healthcare, etc.) |
| Respondent title & seniority | C-level, EVP/SVP/VP, Director |
| Employee headcount | Band (2K – 100K+) — from HR system / 10-K |
| Annual revenue | Band ($500M – $50B+) — from annual report / 10-K |
Section 1 — Total AI Spend
Pulled by Procurement, confirmed by AI Leadership
Pull these numbers before you start — don't estimate from memory. Tight brackets only (e.g. $100–125M, not $50–250M).
| Data Point | Specificity | Where to Find It |
|---|
| Total AI vendor spend, 2025 | Tight bracket (e.g. $100–125M) | IT budget + cloud billing + procurement tracker |
| Total IT vendor spend, 2025 | Tight bracket (e.g. $1.0–1.2B) | IT budget summary |
| AI as % of total IT spend | Whole number (e.g. 10%) | Calculated from the two above |
| Token / API inference share | % of AI spend | OpenAI / Anthropic / Bedrock billing |
| Primary funding source | Net-new / reallocated / mixed | Budget planning deck |
| 2026 AI spend projection dual-role | Direction + magnitude (↑ 20–40%) | 2026 IT budget draft |
Cheat Sheet — What to Have Open
Procurement Spend & Contracts
- Vendor contract list (active + pending)
- Cloud billing dashboard (AWS / Azure / GCP)
- IT budget spreadsheet with AI line items
- Procurement tracker with renewal dates
- ELA / master agreement list
AI Leadership Roadmap & Impact
- Technology roadmap (current + 12-month)
- AI initiative tracker or scorecard
- Deployment status by LOB
- Pilot-to-production conversion data
- LOB-level impact notes
Section 2 — Core AI Vendor Categories (6)
For each of the 6 categories, answer the same data points
Tight spend brackets only (e.g. $28–32M, not $25–50M). Procurement handles spend + contract data; AI leadership handles performance + switching intent.
Adoption status (Production / Pilot / Plan)
Primary vendor
Secondary / eval vendors
Tight annual spend bracket
Multi-year deal & ELA expiry
Spend trend for 2026 (↑↓ %)
Switching intent
Satisfaction (1–5)
Execution rating (1–5)
Value for money (1–5)
Displacing any incumbent?
Access channel — Foundation Models only
Foundation Models get one extra question: how the spend splits across Direct API / AWS Bedrock / Azure OpenAI.
01
Foundation Models
OpenAI, Anthropic, Google, Meta, Mistral, Cohere
02
AI Compute & Infra
AWS, GCP, Azure, CoreWeave, Lambda Labs
03
Data Foundation
Snowflake, Databricks, BigQuery, Pinecone, dbt
04
Consulting & SIs
Accenture, Deloitte, IBM, McKinsey, TCS, Wipro
05
AI Dev & Engineering
Cursor, GitHub Copilot, Claude Code, Windsurf
06
AI Governance & Risk
OneTrust, Credo AI, Prompt Security, Protect AI
Section 3 — Emerging Tech Roadmap (10 technologies)
AI Leadership answers — ~30 seconds per tech
For each: adoption status (In Production / Pilot / Near-Term / Long-Term / Not in Plan) and vendors in use or under consideration.
AI Search / RAG
AI Monitoring & Observability
Process Automation
Fine-Tuning & Customization
Knowledge Management
Agent Orchestration
AI Security Platforms
Physical AI & Digital Twins
Domain LLMs
Cybersecurity AI
Section 4 — AI Yield Index
Where you sit on the 0–100 maturity scale
Score across 4 zones: Experimental (0–25) → Developing (25–50) → Realizing (50–75) → Leading (75–100). Most AI leaders can answer from memory or a quick dashboard scan.
Breadth
# of LOBs with AI in production (out of total)
Depth
Pilot-to-production rate (# in prod / total pilots)
Measurement
Formal ROI / KPI framework — Formal / Informal / None
Governance
Board AI charter + AI CoE — Established / In-discussion / None
Underlying survey inputs — assessed across 10 functions
Software Dev & IT
Customer Service
Sales
Marketing
Risk & Compliance
Finance / FP&A
Supply Chain
HR
Legal
R&D
Section 5 — Strategic Signals (Looking Ahead)
Open-ended judgment calls — think these through before you start
These are not data lookups. They are calls a CTO / VP Strategy should make before opening the survey.
Most Exciting AI Vendor
The vendor you're betting on for 2026 — momentum, capability, or enterprise fit
Most Vulnerable Legacy Vendor
Legacy SaaS / SW vendor whose core workflows are being replicated by AI-native tools — feeds the Arcana Vulnerability Index
#1 Strategic Priority
Top AI focus for next 12 months (Scaling pilots, Data readiness, Consolidation, etc.)
Biggest Obstacle
Primary blocker cited across teams (Governance, Talent, Data quality, ROI proof)
Ready? Start the study.
Confidential & de-identified · arcana-research.com/study/arcana
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