Schell IPWhiteford
Whiteford
Whiteford
Mountain West
Technical lead magnet prototype

Build an AI compliance gameplan before the first legal meeting.

Answer a short set of non-confidential questions and get a readiness heat map, priority workstreams, and a suggested Whiteford service path.

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Assessment inputs

Score AI readiness without sharing confidential facts.

Use conservative answers. The preview updates instantly and does not submit anything until you affirmatively opt in below.

Use-Case Inventory
The company has a current inventory of AI uses by team, purpose, owner, vendor, data touched, and decision impact.

Includes internal productivity tools, embedded product features, and shadow AI use.

Vendor Risk
AI vendor terms have been reviewed for data use, confidentiality, IP ownership, indemnity, audit rights, and security obligations.

Covers standalone AI tools and AI features inside existing SaaS platforms.

Human Review
Consequential AI outputs have a defined human review, override, escalation, and recordkeeping path.

Especially where AI affects access, eligibility, pricing, employment, legal, or customer decisions.

Data Sensitivity
Sensitive, confidential, personal, regulated, and customer-provided data are mapped before use in AI systems.

Includes prompts, uploads, training, fine-tuning, retrieval, logs, retention, and vendor reuse.

Governance Owner
A named business owner has authority over AI intake, approvals, policy exceptions, vendor review, and reporting.

The owner can coordinate legal, security, product, HR, and operations rather than just publishing a policy.

Customer-Facing AI
Customer-facing AI features, claims, outputs, disclaimers, and support escalation paths are reviewed before release.

Covers chat, recommendations, scoring, summaries, agents, copilots, and AI-labeled product features.

Employment / HR AI
AI used for recruiting, hiring, performance, scheduling, monitoring, compensation, or workforce analytics has extra review.

Employment AI often needs more bias, notice, documentation, and human review discipline.

Colorado / Mountain West
The company is tracking Colorado and Mountain West AI, privacy, employment, and consumer-protection readiness issues.

The goal is practical readiness for changing obligations, not a one-time legal conclusion.

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Board-level readiness gap

AI use appears ahead of the operating controls. The first legal step is a focused inventory, risk triage, and owner map.

50 ready / 100 risk
Readiness score50/100
Risk exposure100/100

Category scores

Use-Case Inventory50
Partial
Vendor Risk50
Partial
Human Review50
Partial
Data Sensitivity50
Partial
Governance Owner50
Partial
Customer-Facing AI50
Partial
Employment / HR AI50
Partial
Colorado / Mountain West50
Partial

Top gaps

Data Sensitivity

Map sensitive data flows and retention before expanding AI use or adding new vendor integrations.

Vendor Risk

Prioritize vendor contract review for tools touching customer, employee, source code, or regulated data.

Human Review

Define when humans must review, approve, override, and document AI-assisted decisions.

Use-Case Inventory

Build a current AI use-case and vendor inventory before policy, contract, or customer questions become reactive.

Recommended next step

Create a data sensitivity matrix for AI prompts, uploads, logs, model training, and retention.

Suggested Whiteford path: AI Compliance Readiness Sprint.

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This educational tool does not provide legal advice, certify compliance, or create an attorney-client relationship. Do not submit confidential facts.

Research anchors

The tool is framed as readiness, not a legal determination.

Colorado SB24-205Colorado SB25B-004Colorado SB26-189