Edge AI Governance & Monitoring Maturity Assessment

Welcome to the Edge AI Governance & Monitoring Maturity Assessment. This survey takes approximately 14 minutes and asks about your organization's current edge AI practices, governance, monitoring, and risk posture. There are no right or wrong answers—we are interested in your honest assessment of current practices. Your participation is entirely voluntary, and you may stop at any time. All responses are confidential and will be reported only in aggregate to inform governance and operations priorities. Please click 'Next' to begin.

What is your current level of involvement with edge AI models in your organization?

• Owner/accountable
• Contributor
• Aware/consulted
• Not involved

What scope best describes the practices you will be reporting on in this survey?

• Organization-wide
• Multiple sites or teams
• Single site or team
• Unsure

What is your organization's current stage with edge AI models?

• Not using edge AI models
• Exploring / proof of concept
• Pilot in limited locations
• Production in multiple sites
• Retiring or suspending edge AI

If your organization is not yet in broad production with edge AI, when do you expect to begin or expand a pilot?

• Less than 3 months
• 3–6 months
• 6–12 months
• 12+ months
• No plans
• Not applicable — already in production

Which of the following edge AI use cases are most relevant to your organization over the next 12 months? (Select all that apply)

• 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

Which model types are currently in scope for edge deployment in your organization? (Select all that apply)

• Computer vision
• Time-series forecasting
• Anomaly detection
• Natural language processing (NLP)
• Speech/voice
• Recommendation
• Control/optimization
• Other

Which edge environments are most relevant to your organization? (Select all that apply)

• IoT sensors/devices
• Industrial equipment/robots
• On-premises servers/gateways
• Mobile devices/tablets
• Vehicles/fleets
• Retail POS/kiosks
• Medical/clinical devices
• Other

How formalized are your organization's policies for the edge model lifecycle?

• Written, organization-wide policies
• Written, team-specific policies
• Informal guidelines only
• None in place

How would you rate the level of governance control your organization applies during model development and training for edge deployments?

How would you rate the level of governance control your organization applies during model deployment and release for edge environments?

How would you rate the level of governance control your organization applies during ongoing monitoring and maintenance of edge models?

Does your organization maintain a model registry or inventory that includes edge deployments?

• Yes — unified across cloud and edge
• Yes — but partial coverage
• No — planned within 6 months
• No

If your organization maintains a model registry, which of the following does it track for edge models? (Select all that apply)

• Model version and lineage
• Training data provenance
• Performance metrics
• Deployment location/device
• Hardware/resource requirements
• Owner/team accountability
• Compliance or approval status
• Not applicable — no registry
• Other

In the last 6 months, how well defined and enforced were data governance controls for edge datasets in your organization?

Which of the following signals has your organization monitored on edge deployments in the last 30 days? (Select all that apply)

• 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
• None of the above

How mature are your organization's service-level objectives (SLOs) or service-level agreements (SLAs) for edge model performance?

What tooling does your organization use to observe and alert on edge models? (Select all that apply)

• Built-in device logs/metrics
• Centralized monitoring (e.g., Prometheus, Grafana)
• MLOps platform
• Custom scripts/agents
• Commercial APM/observability tool
• Data observability tool
• Not sure
• Other

What is the approximate average time to detect a production edge AI incident in the last 90 days?

• Less than 5 minutes
• 5–15 minutes
• 16–60 minutes
• 1–4 hours
• 4–24 hours
• More than 24 hours
• Don't know / not tracked

Approximately how many edge AI deployments were rolled back in your organization in the last 90 days?

• 0
• 1–2
• 3–5
• 6–10
• More than 10
• Don't know / not tracked

Rank the following risk areas for edge AI from highest to lowest priority for your organization.

1. Data privacy
2. Security
3. Safety
4. Fairness/bias
5. Reliability/availability
6. Regulatory compliance

How often does your organization conduct formal risk assessments before edge AI deployments?

• Every release
• Major changes only
• Ad hoc
• Never
• Planned within 6 months

Do any of your organization's edge AI models currently process sensitive personal data?

• Yes, regularly
• Sometimes
• Unsure
• No

What are the top two or three gaps currently blocking edge AI governance and monitoring in your organization?

We'd like to explore your thoughts on edge AI governance and readiness in more depth. An AI moderator will ask you up to 2 follow-up questions based on your earlier responses.

Rank the following areas by how urgently they need investment to improve your organization's edge AI readiness.

1. Policies & governance
2. Monitoring & alerting
3. Model registry & inventory
4. Data governance for edge datasets
5. Risk & compliance processes
6. Tooling & automation
7. People, training & change management
8. Deployment/rollback processes

Based on your responses in this survey, is there anything else you believe should be considered for edge AI governance or monitoring?

What is your primary role?

• Executive/VP
• Director/Manager
• Data science/ML
• Software/IT/DevOps
• Product/Operations
• Security/Compliance/Risk
• Quality/Manufacturing
• Other

Which function do you primarily belong to?

• Engineering/IT
• Data/AI
• Product
• Operations
• Manufacturing/Supply chain
• Security/Risk/Compliance
• Finance
• HR
• Other

How many years of experience do you have in data, AI, or analytics?

• 0–1
• 2–4
• 5–9
• 10+

Which region best describes your primary work location?

• North America
• Europe
• APAC
• Latin America
• Middle East & Africa
• Multiple regions

Thank you for completing this survey! Your input will help prioritize edge AI governance and monitoring improvements across your organization. Results will be shared in aggregate form.