AI Cyber Risk
AI Risk Services for K-12, Government, and Public Agencies
AI Cyber Risk Governance & Vulnerability Management for Public Entities
Identify AI exposure, reduce cyber risk, and implement responsible governance for generative AI tools, AI-enabled software, and internal AI initiatives.
- Dedicated Cybersecurity Advisor
- No Long-Term Contracts
- Built for Schools and Public Agencies
What this service helps you do
- Identify AI tools and AI-enabled software in use
- Evaluate AI-related cybersecurity and data exposure risks
- Review governance, policy, and oversight gaps
- Assess vendor AI practices and integration risk
- Build a practical roadmap for ongoing risk management
AI Is Already in Your Environment — Managed or Not
72%
Of employees already use AI tools at work — most without IT approval
"Shadow AI is the fastest-growing source of unmanaged risk in public sector organizations — and most IT teams have no visibility into which tools are in use."
Source: Microsoft Work Trend Index 2024
3 in 4
AI-enabled software vendors share data with third parties by default
"The AI features embedded in the tools your district or agency already uses may be processing sensitive data in ways that were never reviewed or approved."
Source: Common Sense Media AI in Education Privacy Report 2024
89%
Of public entities have no formal AI governance policy
"AI risk cannot be managed without visibility. Most public entities have neither — creating exposure to FERPA, HIPAA, and CJIS violations they may not even be aware of."
Source: NASCIO / IBM State & Local Government AI Governance Survey 2024
Artificial intelligence is being adopted rapidly across education and public sector organizations — often without formal governance, risk assessment, or oversight. Staff are using AI tools to process sensitive student data, and vendors are embedding AI into core platforms without full disclosure. The risks are real, measurable, and growing.
Common AI Risks Facing Public Entities Today
Many of these risks arise from rapid AI adoption without clear visibility or governance.
Shadow AI Use
Staff may begin using AI tools informally, without approval, security review, or data handling guidance. Generative AI tools, browser plugins, and third-party assistants are already in use at most public entities — whether IT knows or not.
Sensitive Data Exposure
Confidential student, employee, legal, financial, or operational data may be entered into AI systems without appropriate safeguards. Once data is submitted to an AI platform, retrieval and deletion rights depend entirely on the vendor's policies.
AI-Enabled Software Risk
Organizations may not fully understand how AI features embedded in vendor software process, retain, or use their data. Many common education and government platforms now incorporate AI features that were not present when contracts were signed.
Governance Gaps
Many public entities do not yet have policies, approval workflows, or oversight structures for responsible AI use. Without clear governance, staff have no guidance — and leadership has no visibility into how AI is affecting operations and risk.
Integration Vulnerabilities
AI systems connected to internal data sources or operational systems can introduce cybersecurity weaknesses if not properly reviewed. APIs, automated workflows, and data connectors are common attack surfaces that AI integrations can expand.
Limited Ongoing Oversight
Without structured monitoring and reporting, organizations may struggle to track new AI use cases or unresolved risk over time. The AI risk landscape changes rapidly — a one-time review without ongoing oversight quickly becomes outdated.
What the Assessment Covers
A structured review of the AI tools, data practices, governance, and vendor relationships that define your organization’s AI risk posture.
AI Exposure Discovery
Where AI tools and AI-enabled software may be in use across the organization is identified — including third-party platforms, vendor integrations, and internal initiatives. The result is an AI usage inventory that most public entities do not currently have.
AI Cybersecurity Risk Review
Potential vulnerabilities associated with AI systems, integrations, workflows, and internal or vendor-supported AI capabilities are evaluated. Risk findings are mapped to recognized frameworks including NIST AI RMF and NIST CSF.
Data Exposure & Privacy Review
Whether sensitive information could be exposed through prompts, uploads, integrations, or AI-supported business processes is assessed — across FERPA, HIPAA, CJIS, and state privacy requirements.
Governance & Policy Evaluation
Your organization's policies, oversight processes, and accountability structures for responsible AI use are reviewed. Gaps between current practices and recognized governance standards are identified and documented.
Vendor AI Risk Review
How AI vendors address security, data protection, retention, and operational risk in the products your organization uses is evaluated. Vendor data practices are compared against contract obligations and applicable regulatory requirements.
Risk Mitigation Roadmap
Clear next steps to help leadership strengthen governance, reduce vulnerabilities, and improve ongoing oversight are delivered. The roadmap prioritizes actions by risk level and implementation feasibility.
AI-Powered
AI-Powered Risk Discovery That Finds What Manual Reviews Miss
AI analysis dramatically expands discovery coverage — identifying shadow AI use, data exposure pathways, and vendor risk patterns that manual review processes cannot efficiently uncover at scale.
- Automated vendor contract and data practice analysis that flags discrepancies between stated data protections and documented AI data handling practices
- AI governance gap scoring that benchmarks your current policies against NIST AI Risk Management Framework and state AI governance requirements
- Continuous AI risk monitoring that tracks new tool adoption, policy deviations, and emerging AI vendor risk between formal assessment cycles
A Perfect Fit for Schools and Public Entities.
ResoluteGuard Cybersecurity tools are designed for your budget, your team size, and your compliance requirements.
Built for Public Sector AI Governance Realities
AI governance in schools and public agencies is fundamentally different from enterprise AI risk. FERPA, HIPAA, CJIS, state student data privacy laws, and public records considerations are central — not afterthoughts. The assessment is designed around these requirements from the ground up.
Lower Your Insurance Costs
Cyber insurers are beginning to ask about AI governance — specifically whether policies exist and whether vendor data practices have been reviewed. A documented AI risk assessment provides the evidence insurers require and positions your organization for lower premiums.
Practical Recommendations Your Team Can Actually Implement
Assessment findings are translated into recommendations that reflect the staffing, budget, and operational realities of public-sector organizations. Every recommendation includes an implementation priority and difficulty rating — not just a list of ideal controls.
AI Risk Maturity Model for Public Entities
Public entities are at different stages in their ability to manage AI-related risk. This model helps organizations understand where they are today and what stronger governance looks like over time.
AI Risk Maturity Model for Public Entities
01
Initial Consultation
Your environment, current AI usage, and areas of concern are reviewed so the assessment can be tailored to your organization. The scope of AI tools, vendor platforms, and internal initiatives to be evaluated is defined collaboratively.
02
AI Exposure & Risk Review
Where AI tools and AI-enabled platforms are being used is identified, and potential data, cybersecurity, and governance risks are reviewed. Vendor data practices, staff-adopted tools, embedded AI features, and integration points are all examined.
03
Risk Analysis & Findings
Information collected during the review is evaluated and vulnerabilities, operational concerns, and areas where governance controls are needed are identified. Findings are mapped to NIST AI RMF, NIST CSF, and applicable regulatory frameworks.
04
Recommendations & Roadmap
Practical recommendations and a prioritized roadmap for strengthening AI governance and reducing cyber risk are delivered. The roadmap is designed to be implemented with the resources and staffing your organization actually has.
Find out what's at risk
Discover where AI tools are in use in your organization and what governance and cybersecurity risks may already exist — at no cost and with no commitment.
- No long-term contracts
- Free initial assessment
- Expert cybersecurity advisor support
Prefer to call? Reach us directly:
888-728-6030 cyberadvisor@resoluteguard.com
Request a Free Assessment
No spam. No obligation. A real Cybersecurity Advisor will reach out — not a sales bot.
Vulnerability Scanning
Continuously identify security gaps across your systems before attackers can exploit them.
Cyber Tabletop Exercises
Test your team's incident response with scenario-based exercises that reveal gaps before a real attack.
Compliance as a Service
Stay audit-ready with continuous compliance monitoring for FERPA, CIPA, and NIST CSF.
Common Questions
Everything you need to know about backup and recovery for schools and public agencies.
How do we know if AI tools are already being used in our organization?
Many organizations discover staff are already using AI tools informally. An AI risk assessment helps identify where these tools may be in use — across departments, devices, and applications — and whether policies or safeguards are needed. Discovery often reveals use cases leadership was not aware of.
Are AI tools safe to use with sensitive student or employee data?
That depends on how specific tools store, process, retain, and protect submitted information. Some AI platforms retain data for model training or share it with third parties by default. Reviewing vendor data handling practices is a core component of the AI risk assessment.
Does AI use by our vendors create risk even if our staff isn't using AI?
Yes. AI features embedded in vendor software — student information systems, productivity platforms, communication tools, and administrative applications — may process your data in ways that were not disclosed when contracts were signed. Vendor AI risk review is a dedicated component of the assessment.
What compliance frameworks apply to AI use in public entities?
FERPA, HIPAA, CJIS, COPPA, and state student data privacy laws all apply to how personal information is handled — regardless of whether that handling is by humans or AI systems. NIST AI RMF and NIST CSF provide governance frameworks. State-level AI governance requirements are also expanding rapidly.
Does our organization need an AI policy before the assessment?
No. Many organizations use the assessment to inform the development of their first AI policy. The assessment identifies where policies are needed, what they should cover, and how to prioritize governance improvements.
How is AI risk managed on an ongoing basis after the assessment?
AI risk management should be ongoing — not a one-time activity. The assessment roadmap includes recommendations for establishing continuous oversight, tracking new AI adoption, and maintaining governance as your environment and the AI landscape evolve. AI risk documentation is prepared for your insurer.
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