74% of enterprises now run AI workloads on hybrid cloudLIVE DATA

The AI benchmark
data your board
is going to ask for.

Practitioner-sourced data on how Fortune 1000 companies deploy, spend on, and evaluate AI. From the CTOs, CIOs, and Heads of AI who actually make the decisions — not analysts, not vendors.

A quarterly study. Four proprietary indices. A tear sheet of your AI vital stats. The peer comparison data that doesn’t exist anywhere else.

Fortune 1000

Participant Companies

12

Industries Represented

VP / Head of AI

Avg. Respondent Title

Quarterly

Data Refresh Cycle

The Problem—

Everyone has an opinion on AI. Nobody has the data.

Gartner studies vendors. McKinsey sells frameworks. G2 solicits reviews from the vendors themselves. We built a practitioner-only panel — Fortune 1000 technology leaders who contribute their data quarterly. Vendors don’t participate in the study. They buy access to the results.

No Peer Benchmarks

You're making million-dollar AI decisions with no visibility into what your peers are spending, deploying, or getting in return.

Every Other Benchmark Is Vendor-Funded

Gartner, Forrester, and IDC earn the majority of their revenue from the vendors they evaluate. G2 charges vendors for premium profiles. The people being rated are paying for the ratings.

Board Deck Gap

Your CFO wants comparable data before approving next quarter's AI budget. You don't have it. Neither does anyone else.

Membership—

What members receive.

A tear sheet of your company’s AI vital stats

Your spend, vendor stack, adoption maturity, and technology roadmap — all in one place. The data your board and executive team actually asks for, ready to present.

A peer comparison benchmark against Fortune 1000 companies

See exactly how your AI investments compare to anonymized peers in your industry and company size. Where you over-invest, where you under-invest, and where you’re ahead.

Four proprietary indices updated every quarter

Heat Index (where new budget is going), Adoption Index (what’s already deployed), Vulnerability Index (which vendors are at risk), and Spend Index (where dollars actually flow).

A private community of practitioners — no vendors, no pitches

A verified network of CTOs, CIOs, and Heads of AI at Fortune 1000 companies. Private digital community for async discussion, plus invite-only research dinners in major markets. No vendors. No sales pitches.

The Research—

What the Enterprise Pulse covers.

Foundation Models

Provider selection, multi-model strategy, and spend allocation across OpenAI, Anthropic, Google, and open-source alternatives.

AI Infrastructure & Compute

Cloud AI platforms, GPU provisioning, inference vs. training spend, and vendor consolidation patterns.

Data & ML Pipelines

Data foundations, orchestration tooling, RAG deployments, vector search, and production ML infrastructure.

AI Governance & Risk

Policy frameworks, model evaluation practices, compliance requirements, shadow AI management, and responsible deployment.

Emerging Technologies

Agentic AI, open-source agents, small language models, AI for cybersecurity, and early-stage deployment patterns.

Vendor Evaluation & Spend

Satisfaction ratings, switching intent, competitive displacement, and budget allocation by category.

How It Works—

30 minutes. Quarterly. That's the ask.

01

Apply

Apply to the Arcana Research community. Open to enterprise technology leaders at Fortune 1000 companies who are actively deploying AI. We verify every participant.

02

Participate

Complete the Arcana AI Enterprise Pulse — a quarterly study (~30 minutes) covering your AI spend, vendor evaluations, deployment status, and strategic priorities.

03

Benchmark

Receive a tear sheet of your AI vital stats, a peer comparison benchmark, full access to four proprietary indices, and community membership.

The Indices—

Four lenses on enterprise AI. All practitioner-sourced.

Our proprietary indices are built from quarterly study data collected from enterprise AI leaders at Fortune 1000 companies. No vendor funding. No analyst opinion. Just deployment data.

Methodology: Structured quarterly study administered to a verified panel of enterprise technology leaders at companies with $1B+ revenue. All responses are anonymized. Indices are computed from deployment status, spend allocation, satisfaction ratings, and adoption intent. No vendor input. No analyst opinion.

AI SWE82
LLM Orch.78
RAG71
AI Analytics65
Agents44
AI Security58
AI SWE Tools75
Fine-tuning52
MLOps60
Data Pipelines55
Evaluation48
Governance42
LOW
HIGH
Q1 2026 · Arcana Research

Heat Index

Where new budgets are going

A 0–100 score for emerging AI technologies based on near-term adoption plans, pilot activity, and new investment momentum. Tracks where the next dollar goes — not what’s already deployed.

AI Software Engineering
+12.4%
LLM Orchestration
+9.1%
Retrieval-Augmented Gen.
+6.8%
Open Source Agents
+15.2%
AI-Assisted Analytics
+3.2%

Early data from our founding cohort. Full index available to members.

Adoption Index

What’s already deployed

Which AI technologies are in production at Fortune 1000 companies today. Sourced from practitioner ratings across six core categories — shows what your peers have actually shipped, not what they’re planning.

Foundation Models
+4.1%
Data Infrastructure
+2.3%
AI Software Engineering
+8.7%
Compute Infrastructure
+1.9%
AI for Cybersecurity
+6.4%

Early data from our founding cohort. Full index available to members.

Vulnerability Index

Who’s at risk

Which AI vendors are at risk of losing enterprise customers — and to whom. Based on satisfaction scores, switching intent, and competitive displacement patterns from our practitioner panel.

Legacy NLP Platforms
-8.2%
First-Gen Chatbots
-11.5%
On-Prem ML Suites
-5.7%
Single-Cloud AI Stacks
-3.3%
Manual Annotation Tools
-14.1%

Early data from our founding cohort. Full index available to members.

Spend Index

Where budgets go

Where enterprise AI budgets actually flow — by category, company size, and industry. Tracks quarter-over-quarter allocation shifts across infrastructure, platform, and application layers.

Cloud AI Infrastructure
+4.2%
AI Dev Platforms
+2.8%
Vertical AI Applications
+5.1%
AI Security & Governance
+7.3%
AI Consulting & Services
-1.9%

Early data from our founding cohort. Full index available to members.

Try It—

Preview your benchmark.

Answer three questions and see a preview of how your organization compares to peers. The full report is available after joining the study.

Preview Your Benchmark—

Your Role

Company Size (employees)

Industry

The Community—

Practitioners only. No vendors. No analysts.

Our research community is exclusively enterprise technology leaders at Fortune 1000 companies who deploy AI at scale. The people making the decisions, managing the budgets, and evaluating the vendors. Membership is by application. We verify every participant.

Head of AIChief Technology OfficerChief Information OfficerVP EngineeringChief Data OfficerSVP ProductDirector of MLVP AI Strategy

Company Size

$1B+ revenue · 2,000+ employees

Fortune 1000 and upper mid-market

AI Maturity

Active deployment

Past experimentation, in production or pilot

Decision Authority

Budget influence

Involved in AI vendor and spend decisions

Get Started—

The data your board deck is missing.

Apply to the Arcana AI Enterprise Pulse

Contribute 30 minutes per quarter. Receive a tear sheet of your AI vital stats, a peer comparison benchmark, and access to four proprietary indices. Walk into your next board meeting with the data.

For AI vendors interested in Pulse data access, contact ken@arcanaresearch.com