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Edge AI Governance & Monitoring Readiness Survey Template

Benchmark edge AI governance, monitoring, and operations. Uncover risks, compliance gaps, and MLOps needs across deployments. Quick, actionable survey template.

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Sample Survey Items

Q1
Dropdown
What scope best describes your responses?
  • Organization-wide
  • Multiple sites/teams
  • Single site/team
  • Unsure
Q2
Dropdown
What is our current stage with edge AI models?
  • Not using edge AI models
  • Exploring/PoC
  • Pilot in limited locations
  • Production in multiple sites
  • Retiring or suspending edge AI
Q3
Dropdown
If not yet in broad production, when do you expect a pilot or expansion?
  • < 3 months
  • 3-6 months
  • 6-12 months
  • 12+ months
  • No plans
Q4
Multiple Choice
Which edge AI use cases are most relevant over the next 12 months?
  • Quality inspection (vision)
  • Predictive maintenance
  • Safety monitoring
  • On-device personalization
  • Text classification (NLP)
  • Voice/audio processing
  • Object detection/classification (vision)
  • Edge demand forecasting
  • Fraud detection at POS/kiosks
  • Undecided / not defined
  • Other
Q5
Multiple Choice
Which model types are currently in scope for edge deployment?
  • Computer vision
  • Time-series forecasting
  • Anomaly detection
  • Natural language processing (NLP)
  • Speech/voice
  • Recommendation
  • Control/optimization
  • Other
Q6
Multiple Choice
Which edge environments are most relevant for us?
  • IoT sensors/devices
  • Industrial equipment/robots
  • On-prem servers/gateways
  • Mobile devices/tablets
  • Vehicles/fleets
  • Retail POS/kiosks
  • Medical/clinical devices
  • Other
Q7
Dropdown
How formalized are our policies for the edge model lifecycle?
  • Written, organization-wide policies
  • Written, team-specific policies
  • Informal guidelines only
  • None in place
Q8
Matrix
For each stage, indicate the level of control required for edge models.
RowsNot in placeInformalDefinedRequired sign-off
Data collection for edge datasets••••
Model training/build••••
Pre-deployment approval••••
Change management for updates••••
Incident response/playbooks••••
Q9
Dropdown
Do we maintain a model registry/inventory that includes edge deployments?
  • Yes — unified across cloud and edge
  • Yes — but partial coverage
  • No — planned within 6 months
  • No
Q10
Matrix
If yes, what does the registry track for edge models?
RowsTracked for allTracked for someNot tracked
Model/version lineage•••
Deployment target (device/site)•••
Owner/accountable team•••
Risk tier/classification•••
Approval/sign-off status•••
Release/change history•••
Q11
Opinion Scale
In the last 6 months, how well defined and enforced were data governance controls for edge datasets?
Range: 1 – 10
Min: Not definedMid: Partially definedMax: Well defined and enforced
Q12
Multiple Choice
Which signals have we monitored on edge deployments in the last 30 days?
  • Data drift
  • Concept drift
  • Data quality checks
  • Latency/throughput
  • Accuracy/precision/recall
  • Hardware resource usage
  • Privacy/security events
  • Safety constraint violations
  • Human-in-the-loop feedback
Q13
Rating
How mature are our SLOs/SLAs for edge model performance today?
Scale: 11 (star)
Min: No SLOsMax: Defined SLOs with alerting
Q14
Multiple Choice
What tooling is used to observe and alert on edge models?
  • Built-in device logs/metrics
  • Centralized monitoring (e.g., Prometheus/Grafana)
  • MLOps platform
  • Custom scripts/agents
  • Commercial APM/observability
  • Data observability tool
  • Not sure
  • Other
Q15
Numeric
Average time to detect a production edge incident in the last 90 days (minutes).
Accepts a numeric value
Whole numbers only
Q16
Numeric
How many edge deployments were rolled back in the last 90 days?
Accepts a numeric value
Whole numbers only
Q17
Ranking
Rank the following risk areas for edge AI from highest to lowest priority.
Drag to order (top = most important)
  1. Data privacy
  2. Security
  3. Safety
  4. Fairness/bias
  5. Reliability/availability
  6. Regulatory compliance
Q18
Dropdown
How often are formal risk assessments run before edge deployments?
  • Every release
  • Major changes only
  • Ad hoc
  • Never
  • Planned within 6 months
Q19
Dropdown
Do any edge models process sensitive personal data today?
  • Yes, regularly
  • Sometimes
  • Unsure
  • No
Q20
Multiple Choice
Attention check: To confirm you are reading the questions, please select "I am paying attention" only.
  • I am paying attention
  • I am not paying attention
Q21
Long Text
What are the top two or three gaps blocking edge AI governance and monitoring today?
Max 600 chars
Q22
Constant Sum
Allocate 100 points to the areas that most need investment for edge AI readiness.
Total must equal 100
  • Policies & governance
  • Monitoring & alerting
  • Model registry & inventory
  • Data governance for edge datasets
  • Risk & compliance processes
  • Tooling & automation
  • People, training & change management
  • Deployment/rollback processes
Min per option: 0Whole numbers only
Q23
Long Text
Anything else we should consider for edge AI governance or monitoring?
Max 600 chars
Q24
Dropdown
What is your primary role?
  • Executive/VP
  • Director/Manager
  • Data science/ML
  • Software/IT/DevOps
  • Product/Operations
  • Security/Compliance/Risk
  • Quality/Manufacturing
  • Other
Q25
Dropdown
Which function do you primarily sit in?
  • Engineering/IT
  • Data/AI
  • Product
  • Operations
  • Manufacturing/Supply chain
  • Security/Risk/Compliance
  • Finance
  • HR
  • Other
Q26
Dropdown
How many years of experience do you have in data/AI or analytics?
  • 0-1
  • 2-4
  • 5-9
  • 10+
Q27
Dropdown
Which region best describes your primary location?
  • North America
  • Europe
  • APAC
  • Latin America
  • Middle East & Africa
  • Multiple regions
Q28
Dropdown
What is your current level of involvement with edge AI models?
  • Not involved
  • Aware/consulted
  • Contributor
  • Owner/accountable
Q29
Chat Message
Welcome! This short survey takes about 7–10 minutes. Please answer based on your team’s current practices. Your responses are confidential and will be aggregated.
Q30
Long Text
Any final comments or clarifications?
Max 600 chars
Q31
AI Interview
AI Interview: 2 Follow-up Questions on edge AI readiness
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Q32
Chat Message
Thank you for completing the survey! Your input will help prioritize our edge AI governance and monitoring improvements.

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