Enterprise AI Governance · TAIM Framework · Human Signal
TAIMScore™
Trusted AI
Model Score
72 Controls · 4 Domains · 1 Audit-Ready Score
TAIMScore™ is the enterprise standard for scoring AI governance maturity and quantifying AI Incident Probability. It gives compliance professionals, auditors, and AI risk leaders a structured, repeatable methodology to assess, document, and continuously improve the governance structures around every AI system in their environment.
Framework Definition
What Is TAIMScore™?
TAIMScore™ — the Trusted AI Model Score — is an AI governance maturity and risk assessment framework developed by Taiye Lambo, Founder and Chief Artificial Intelligence Officer (CAIO) of HISPI, the Holistic Information Security Practitioner Institute. TAIMScore™ emerged from Project Cerebellum — a HISPI AI Governance Think Tank that evolved into a Community of Practice (CoP) designed to crowdsource open source Responsible AI work products. HISPI is an independent 501(c)(3) nonprofit organization.
The framework's mission is direct: providing effective guardrails for Safe, Secure, Responsible, and Trustworthy AI use cases. TAIMScore™ is the scoring instrument that makes that mission operational — giving auditors, compliance officers, and executives a structured, repeatable methodology to assess the governance structures surrounding every AI system they deploy.
The distinction from other AI risk tools matters. Most frameworks evaluate model performance: accuracy rates, bias metrics, output quality. TAIMScore™ evaluates institutional readiness — the accountability structures, escalation paths, policy documentation, monitoring protocols, and incident response capabilities that determine whether your organization can actually govern AI at the moment of execution. That is a different problem. And it is the one that causes institutions to fail.
"Most institutions will not fail because of a bad AI model. They will fail because of a broken governance structure around it."
— The Workflow Thesis · Human Signal
TAIMScore™ operationalizes this insight. The framework produces a quantified score — an AI Incident Probability rating — derived from 72 controls evaluated across four governance domains. The score tells an organization not only where it is today, but where the highest-risk gaps exist and what remediation actions to prioritize.
For regulated industries — federal agencies, healthcare systems, financial institutions, critical infrastructure operators — TAIMScore™ provides an audit-ready documentation layer that maps directly to NIST AI RMF, ISO/IEC 42001, SOC 2, and the EU AI Act. One assessment. Multiple compliance frameworks addressed simultaneously.
Framework Architecture
The Four Domains of TAIMScore™
TAIMScore™ organizes its 72 controls across four domains. Each domain targets a distinct layer of institutional AI governance. Weaknesses in one domain propagate across the others. A complete assessment scores all four.
GOVERN
19 Controls
Accountability structures, AI policy documentation, executive ownership, and escalation authorities. Who owns the AI decision? What is the escalation path? Who has deactivation authority?
MAP
20 Controls
AI system inventory, risk categorization, model provenance documentation, and stakeholder impact mapping. You cannot govern what you have not mapped.
MEASURE
18 Controls
Performance monitoring, bias and fairness evaluation, outcome verification, and continuous scoring. Governance without measurement is assumption.
MANAGE
15 Controls
Incident response protocols, model retirement procedures, vendor oversight, and continuous governance operations. The MANAGE domain is where policy becomes practice.
Human Signal applies all four TAIM domains to real-world AI failures in the Failure Files™ series. Every failure case demonstrates precisely which controls were absent at the moment of incident. Real institutions fail across multiple domains at once. TAIMScore™ surfaces that multi-domain exposure before the incident — not after.
Assessment Methodology
How TAIMScore™ Works
The TAIMScore™ assessment follows a structured six-step process conducted by a trained assessor using the HISPI platform. Output: audit-ready report, quantified scores, control gap inventory, prioritized remediation roadmap.
Inventory Your AI Systems
Identify every AI system in your environment — including vendor-supplied and third-party models. Classify each by use case, data access, operational scope, and deployment context. Undiscovered systems cannot be governed. This step frequently reveals AI exposure organizations did not know they had.
Score the GOVERN Domain
Apply the 19 GOVERN controls. Assess accountability structures, executive AI ownership, policy documentation quality, and escalation paths. GOVERN failures are the most common root cause of high-stakes AI incidents. If no one owns the decision, no one can stop the harm.
Score the MAP Domain
Apply the 20 MAP controls. Evaluate AI risk categorization, model provenance documentation, and stakeholder impact analysis. MAP gaps are often discovered late — after deployment, after harm. Proactive mapping is the difference between governance and liability management.
Score the MEASURE Domain
Apply the 18 MEASURE controls. Evaluate performance monitoring cadences, bias and fairness tracking protocols, and outcome verification procedures. If you are not measuring, you are not governing — you are hoping.
Score the MANAGE Domain
Apply the 15 MANAGE controls. Assess incident response procedures, model retirement policies, vendor governance requirements, and ongoing operational controls. MANAGE is where frameworks become real. Paper governance fails in this domain.
Generate Your AI Incident Probability Score
Aggregate domain scores into an overall TAIMScore™ rating. Use the score to prioritize remediation, produce audit documentation, and establish a governance maturity baseline to benchmark against over time. The score is not the endpoint — it is the starting line.
Regulatory Alignment
TAIMScore™ and Global AI Standards
A single TAIMScore™ assessment maps simultaneously to the major AI governance and risk management frameworks in effect globally — eliminating duplicative assessment work and producing a unified compliance evidence package.
NIST AI RMF
The U.S. federal benchmark for AI governance. TAIMScore™'s four domains map directly to the NIST AI RMF GOVERN, MAP, MEASURE, and MANAGE functions.
ISO/IEC 42001
The international standard for AI management systems. TAIMScore™ controls address accountability, risk treatment, and continual improvement requirements.
SOC 2
GOVERN and MANAGE domain controls align with SOC 2 Trust Services Criteria for availability, processing integrity, and confidentiality in AI-assisted processing environments.
EU AI Act
Requires risk classification, transparency documentation, and human oversight for high-risk AI systems. TAIMScore™'s MAP and MEASURE domains directly address these requirements.
Human Signal develops NIST 800-53 and FedRAMP AI governance playbooks that integrate TAIMScore™ as the AI risk quantification layer. Available through the Human Signal consulting practice.
TAIMScore™ Applied · Failure Files™
What TAIMScore™ Looks Like in the Real World
Human Signal's Failure Files™ series applies the TAIMScore™ framework to documented real-world AI incidents — mapped to the specific TAIM controls that were absent or insufficient. These are not hypotheticals. They are forensic autopsies of institutions that deployed AI without governance structures capable of intervening when the system failed.
Microsoft TAY — When Your AI Learns to Hate on Company Time
Four TAIM controls failed simultaneously. No adversarial input controls. No kill-switch SLA. No deactivation authority designated before launch.
Wrongful Arrests — The Algorithm Said It Was Him. It Wasn't.
Three wrongful arrests. No demographic performance analysis documented before deployment. Fairness evaluated after the lawsuits — not before the harm.
Korean Air / KC&D — When Your Vendor Becomes Your Vulnerability
Divested subsidiary retained 30,000 employee records for five years. No data return requirement. No patch SLA. The breach came from outside the risk model's boundary.
Affiliate Disclosure · Human Signal
Human Signal and TAIMScore™
TAIMScore™ was developed by Taiye Lambo, Founder and Chief Artificial Intelligence Officer (CAIO) of HISPI — the Holistic Information Security Practitioner Institute. HISPI is an independent 501(c)(3) nonprofit organization. TAIMScore™ is a work product of Project Cerebellum — a HISPI AI Governance Think Tank that evolved into a Community of Practice (CoP) built to crowdsource open source Responsible AI work products. Framework methodology, scoring systems, and certification standards are governed entirely by HISPI.
Human Signal is an authorized affiliate partner of HISPI. Human Signal does not own the TAIMScore™ framework and holds a promotional agreement limited to the TAIMScore™ Assessor Workshop. Human Signal applies the TAIMScore™ framework — with HISPI's affirmation — to independent governance research, including the Failure Files™ series and The AI Governance Briefing podcast.
Dr. Tuboise Floyd holds the TAIMScore™ Certified Assessor credential (HISPI, March 2026) and is a member of the HISPI Advocacy & Education Working Group, Project Cerebellum AI Think Tank.
Independence is not a feature. It is the product. Human Signal does not receive commissions that compromise editorial judgment. The TAIMScore™ framework earns its place in Human Signal's methodology because it is the most comprehensive AI governance scoring tool available to practitioners — not because of a commercial arrangement.
Common Questions
TAIMScore™ FAQ
What does TAIMScore™ stand for?
TAIMScore™ stands for Trusted AI Model Score. It is the scoring framework developed by HISPI — the Holistic Information Security Practitioner Institute — through Project Cerebellum, a HISPI AI Governance Think Tank and Community of Practice. The four assessment domains are GOVERN, MAP, MEASURE, and MANAGE.
How many controls are in TAIMScore™?
72 controls total: 19 in GOVERN, 20 in MAP, 18 in MEASURE, and 15 in MANAGE. Free interactive flashcards covering all 72 are available at humansignal.io/taimscore_access. No login required.
What is AI Incident Probability?
The core output metric of a TAIMScore™ assessment — quantifying the likelihood that an organization will experience a harmful AI-related incident based on governance control gaps across all four domains. A high score requires immediate remediation.
What standards does TAIMScore™ align with?
NIST AI RMF, ISO/IEC 42001, SOC 2, and the EU AI Act. A single assessment produces documentation relevant to all four frameworks simultaneously.
How do I become a TAIMScore™ Certified Assessor?
Complete the official TAIMScore™ Assessor Workshop — one day, instructor-led, virtual. Earn 6 CPEs and the TAIMScore™ Assessor Certificate. Sessions run on the third Friday of every month at 10am ET.
Is TAIMScore™ relevant for federal agencies?
Yes. TAIMScore™'s alignment with NIST AI RMF makes it directly applicable to federal AI governance requirements. Human Signal develops NIST 800-53 and FedRAMP AI governance playbooks integrating TAIMScore™ as the AI risk quantification layer. Contact Human Signal through the consulting practice for federal engagements.
Legal Disclaimer · TAIMScore™ Assessor Workshop
Legal Disclaimer
Educational Scope
The TAIMScore™ Assessor Workshop is an educational training program designed to build practitioner competency in applying the TAIM framework to AI vendor risk assessment. Completion of this workshop and receipt of a TAIMScore™ Assessor Certificate does not constitute licensure, accreditation, regulatory certification, or qualification to provide legal, compliance, or professional services of any kind in any jurisdiction. The certificate documents participation in an educational program only.
Continuing Professional Education
Continuing Professional Education (CPE) credits are provided for educational participation. Human Signal makes no representations that these credits will be accepted by any specific professional body, licensing authority, or employer. Participants are solely responsible for verifying CPE eligibility with their relevant credentialing organizations prior to registration.
Framework Ownership & Affiliate Relationship
TAIMScore™ is a proprietary framework developed by HISPI · Project Cerebellum (projectcerebellum.com). Human Signal operates as an authorized affiliate partner exclusively to promote and host the TAIMScore™ Assessor Workshop. Framework methodology, scoring systems, and certification standards are governed by HISPI. Human Signal assumes no liability for institutional decisions, vendor assessments, regulatory actions, legal proceedings, financial losses, or other consequences arising from application of TAIMScore™ methodology by workshop participants.
No Professional Advice
Workshop content, materials, and the Failure Files™ case studies are provided for educational purposes only and do not constitute legal, regulatory, compliance, investment, or professional advice. Case studies reference publicly documented AI incidents and are used solely for analytical and pedagogical purposes. No attorney-client, consultant-client, or fiduciary relationship is created by participation in this workshop.
Cancellation & Modifications
Refund and cancellation policies are governed by the terms presented at registration. Human Signal reserves the right to modify workshop dates, format, speakers, or curriculum. Participants are encouraged to obtain qualified legal and compliance counsel for institutional AI governance decisions specific to their jurisdiction and circumstances.
© 2026 Human Signal. All rights reserved. GASP™ and L.E.A.C.™ Protocol are Human Signal IP. TAIMScore™ is licensed from HISPI · Project Cerebellum. Independence is not a feature. It is the product.
TAIMScore™ Assessor Workshop · HISPI · Human Signal
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Score Your Organization.
One day. Six CPEs. A repeatable AI governance scoring methodology you can use immediately. Third Friday of every month — virtual, instructor-led, audit-ready.