Datasets:

hewyler
/

hernan-huwyler-ai-governance-portfolio

Location: Copenhagen Metropolitan Area, Denmark
Contact: LinkedIn
Expertise: AI Governance, Quantitative Risk Management, Responsible AI, Digital Compliance, GRC Frameworks, EU AI Act, ISO 42001, NIST AI RMF, Algorithmic Auditing

Executive Summary

I am an AI risk manager and GRC executive empowering leaders to drive business objectives through AI governance, digital compliance, and responsible AI in multinational companies. With over two decades of global executive experience, I specialize in steering Fortune 500 organizations to achieve financial success and operational excellence.

My expertise spans quantitative risk management, algorithmic auditing, responsible AI frameworks, digital compliance, and process audits across diverse industries, including technology, consultancy, energy, and engineering. I actively partner with global boards, event organizers, and multinational HR departments, offering freelance consulting, corporate training, and executive speaking engagements on the intersection of AI adoption and regulatory compliance.

Armed with an MBA, CAIO and CPA, I possess deep knowledge of financial audits under US GAAP and IFRS. My technical capabilities include advanced AI model validation using Python, TensorFlow, PyTorch, Scikit-learn, and XGBoost, as well as ERP systems like SAP FiCo, SAP GRC, and SAP MM. Fluent in English and Spanish, I leverage cross-cultural expertise to build trust and align stakeholders in global enterprises, managing compliance, mitigating risks, and achieving operational excellence across regulatory jurisdictions.

Core Competencies

Domain	Expertise
AI Governance and Strategy	Responsible AI, Algorithmic Auditing, Digital Compliance, EU AI Act, NIST AI RMF, ISO 42001, AI Risk Assessments, Generative AI Governance, Model Risk Management
Quantitative Risk Management	Model Risk, Predictive Risk Models, AI Impact Assessments, Monte Carlo Simulations, Stress Testing, Value at Risk (VaR), Loss Exceedance Curves, Financial Exposure Modeling, Risk-Adjusted ROI, Stochastic Modeling
Executive Management	Corporate Governance, Board Advisory, Freelance Consulting, Executive Training, Keynote Speaking, Strategic Planning, Business Transformation, Change Management
AI and Machine Learning Stack	Python, R, TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, AWS DataBrew, ServiceNow AI
Compliance and Auditing	ERP Management, SAP FiCo, SAP GRC, SAP MM, SOX 404, GDPR, FCPA, Data Privacy (ISO 27001/27701), Internal Controls, COSO Framework, Performance Audits
Enterprise Risk Management (ERM)	Internal Controls, COSO Framework, Performance Audits, ESG Reporting, IT Governance (COBIT, ITIL), Third-Party Due Diligence, NIST 800-53, MITRE ATLAS

Professional Experience

Capgemini

Senior Manager AI Governance and Digital Compliance | AI Risk Manager and Applied AI Lab Lead January 2025 to Present | Copenhagen Metropolitan Area

Leading enterprise-wide AI Governance and Responsible AI initiatives, integrating Algorithmic Auditing, machine learning, and predictive models to enhance operational resilience and regulatory compliance.

Directing AI initiatives, conducting feasibility studies, and implementing AI-driven Quantitative Risk models for fraud detection, regulatory reporting, and cybersecurity threat identification.

Advising senior executives on AI governance, algorithmic accountability, and risk-based decision frameworks, providing data-driven insights for Digital Compliance.

Leading AI risk assessments and controls implementation, ensuring adherence to the EU AI Act, NIS 2, GDPR, SOX, FCPA, and DORA.

Designing and executing technology risk assessments, incorporating AI bias detection, adversarial testing, and model risk validation using Python, TensorFlow, PyTorch, and Scikit-learn.

Developing AI cost-benefit analysis and risk-adjusted ROI models to optimize AI investment strategies and mitigate financial exposure.

Project: Applied AI Lab (RIOT) Leadership and Innovation Acceleration

Spearheaded the internal acceleration program to develop, commercialize, and deploy cutting-edge, compliant AI solutions for Fortune 500 clients across multiple sectors.

Steered the strategic vision for the Applied AI Lab, establishing AI Governance methodologies that position the firm as a premier advisor in enterprise AI transformation. Functioned as the internal AI Risk Manager, ensuring developed capabilities and consulting solutions adhered to global regulatory frameworks and data privacy laws. Developed go-to-market roadmaps and AI use cases for the life sciences, defense, telecom, and oil and gas sectors, directly driving new business development.

Championed Responsible AI as a core differentiator, embedding ethical AI frameworks into solutions built on SAP Joule, ServiceNow AI, and enterprise Copilots. Architected GenAI strategies that revolutionized client HR, Finance, and GRC functions, shifting organizations toward intelligent process automation. Produced high-impact thought leadership on the intersection of workforce transformation and Digital Compliance, training internal consultants and advising C-suite clients.

Applied Quantitative Risk analytics to model the financial impact and ROI of deploying enterprise AI systems versus maintaining legacy processes. Fostered rapid innovation cycles by identifying and prioritizing AI use cases that solved immediate, high-value business challenges for key global accounts. Designed standardized toolkits for Algorithmic Auditing, allowing field consultants to quickly assess and remediate client AI models during engagements. Cultivated cross-functional data strategies, ensuring that client data architecture was mature enough to support advanced, data-driven finance and compliance solutions.

Project: ESG GRC Automation and Data Architecture Transformation

Led a high-stakes digital transformation to automate and secure non-financial sustainability reporting (ESG, GHG) through advanced AI enablement and rigorous data governance for a major global energy corporation.

Directed a global GRC transformation focused on automating ESG reporting, substantially reducing compliance costs and increasing data fidelity for board-level sustainability disclosures. Architected Digital Compliance workflows spanning SAP MDG, IoT sensors, and enterprise data lakes to ensure real-time aggregation integrity for GHG and water consumption metrics.

Applied Quantitative Risk modeling to validate environmental estimation methodologies, eliminating data discrepancies and mitigating the risk of regulatory fines for greenwashing. Identified and prioritized high-ROI AI use cases to streamline non-financial data collection, driving a sustainable business strategy aligned with ISO 14001 and ISO 14064.

Instituted cross-functional AI Governance models to oversee automated reporting tools, ensuring algorithmic outputs were accurate, transparent, and fully traceable. Strengthened the underlying data architecture by implementing strict access controls, data quality validation gates, and continuous anomaly detection.

Advised the C-suite on industry best practices for leveraging Responsible AI to achieve corporate sustainability targets without compromising operational efficiency. Mapped data flows and control processes to prepare the enterprise for external audits by top-tier assurance firms. Delivered actionable roadmaps for technology enablement, shifting the organization from manual spreadsheet reporting to intelligent, automated process performance. Upskilled internal teams on modern data governance standards, fostering a culture of production accountability and precision in ESG performance tracking.

Project: Enterprise AI Governance and Autonomous Systems Controls

Designed and operationalized AI risk and control assessments for advanced autonomous driving systems and machine learning pipelines for a global automotive manufacturer.

Engineered a group-wide AI Governance operating model to dictate consistent lifecycle controls, approval gates, and risk acceptance thresholds across global subsidiaries. Acted as AI Risk Manager, defining corporate strategy for EU AI Act compliance and alignment with ISO/IEC 42001 (AI Management Systems).

Established robust Algorithmic Auditing protocols to evaluate third-party procured AI solutions and internal machine learning models for bias, security posture, and reliability. Developed a Quantitative Risk taxonomy tailored to AI threats, enabling leadership to financially measure and map vulnerabilities aligned with ISO/IEC 27004 and ISO 42005.

Institutionalized Responsible AI principles by designing RACI matrices that clearly defined C-suite accountability across model development, deployment, and decommissioning. Spearheaded Digital Compliance initiatives to evaluate build-vs-buy decisions, ensuring external AI vendors met stringent enterprise security and ethics requirements.

Delivered executive-level risk advisory reports, translating AI threat models into actionable, business-driven risk treatment plans. Supported the design of continuous AIOps monitoring processes to detect data drift, algorithmic bias, and performance degradation in real-time autonomous systems. Embedded compliance-by-design into ML automation pipelines and procedures, reducing the time-to-market for compliant vehicle software deployments. Created standardized, scalable templates for AI impact assessments, ensuring seamless traceability and audit readiness for future regulatory scrutiny.

Project: AI Clinical Data Automation and Algorithmic Quality Assurance Proof of Concepts

Validated the technical and regulatory viability of AI-driven automation for clinical trial data for a global pharmaceutical enterprise.

Led a high-visibility Proof of Concept to modernize clinical trial data management, proving that Digital Compliance can be achieved at scale through AI automation. Executed Algorithmic Auditing on automated data review processes, ensuring AI-generated corrections met the strict control attributes required for clinical trial data.

Assessed AWS Glue DataBrew to run control checks and Quantitative Risk assessments on vast clinical datasets, identifying anomalies and mitigating trial-compromising data errors. Championed Responsible AI by implementing structural safeguards in automated workflows, ensuring zero compromise to patient safety or data integrity.

Engineered and tested GenAI prompts within Signavio process flows to automatically generate, update, and validate Standard Operating Procedures in strict alignment with legal language. Bridged the gap between clinical operations and IT by translating complex regulatory frameworks into deployable, automated system rules.

Proved substantial ROI by quantifying the reduction in manual data review hours, justifying the executive decision to scale the PoC into enterprise-wide pilot deployment. Strengthened AI Governance by documenting the exact lineage of automated corrections, ensuring total transparency for upcoming regulatory inspections. Optimized targeted workflows to handle automated correction packages, minimizing human-in-the-loop bottlenecks while retaining ultimate human oversight. Delivered a comprehensive feasibility report to life science executives, outlining the strategic roadmap for fully autonomous, compliant data management systems.

IE Business School

Executive Education Director, Professor and Speaker: AI Governance, GRC and Digital Compliance January 2013 to Present | Madrid Area, Spain

Promoting corporate sustainability, ethical leadership, compliance, and risk management through high-level executive training and corporate speaking engagements.

IE Law School and IE Business School: Advanced Program in Compliance Director. Topics include compliance and reputation risks, corruption offenses, ISO 37001, ISO 19600, OCEG/GRC frameworks, KRIs and KCIs, investigations, data privacy.

Universidad Complutense de Madrid (UCM): Professor and tutor at the Masters in Compliance and Corporate Social Responsibility.

International University of La Rioja (UNIR): Professor Corporate Compliance and Data Security Masters.

Centro de Estudios Financieros (CEF): Professor Course in Compliance. Topics include global compliance, environmental compliance, compliance for oil and gas, energy, and mining.

Institute For Research Resources (iiR) Spain: Professor and Lecturer. Chairman, Compliance Day 2016. Teaching internal control systems for US regulations (FCPA, SOX, Dodd Frank), compliance management systems, global compliance plan design, and GRC for executive boards.

Speaking Engagements: Active freelance speaker in forums, workshops, and round-tables on AI governance, quantitative risk, compliance, cyber, privacy, and auditing (The Institute of Internal Auditors IIA, ISACA).

Canon Group Milestone Systems

Head of Group Risk and Control | AI Risk Manager and Quantitative Risk Lead August 2022 to November 2024 | Copenhagen Metropolitan Area

Led cross-functional teams to identify, assess, and quantify risks across AI, software development, finance, operations, compliance, and cybersecurity.

Designed, evaluated, and backtested Quantitative Risk models to ensure Responsible AI and quantify risks for decision-making processes (R, Python, ISO 31000, 31022, 37301, 23894, 42001).

Drove and oversaw control solutions, ensuring cybersecurity and compliance with the EU Artificial Intelligence Act, anti-corruption, intellectual property, privacy, and data ethics requirements (FCPA, GDPR, CCPA).

Managed audit and control readiness programs to certify SOX controls, information security, privacy, software development, and data management.

Project: Quantitative Risk Modeling and AI Financial Exposure Validation

Directed the design, backtesting, and implementation of advanced Quantitative Risk models to mathematically measure, stress-test, and mitigate the financial exposure of enterprise AI systems.

Engineered a Quantitative Risk framework using Monte Carlo simulations to calculate Value at Risk (VaR) and the financial exposure associated with deploying generative AI.

Advised the executive leadership team on the risk-adjusted ROI of enterprise AI investments, embedding these financial thresholds into the overarching AI Governance plan.

Bridged the gap between data science and enterprise GRC by translating complex algorithmic uncertainties into clear financial metrics, ensuring strict Digital Compliance with NIS 2, the EU AI Act, ISO 42001, and model risk management guidelines.

Pioneered Algorithmic Auditing pipelines using Python (Scikit-learn, PyTorch) and R to systematically stress-test machine learning models for data drift, predictive degradation, and adversarial vulnerabilities.

Enforced Responsible AI controls by mathematically quantifying and neutralizing algorithmic bias in credit-scoring models, protecting the institution from regulatory fines.

Developed robust stochastic models in Python to simulate extreme market volatility against AI-driven trading algorithms, fortifying operational resilience.

Built and deployed predictive risk algorithms using XGBoost and R to proactively forecast AI system failures and anomalies.

Standardized the technical documentation of risk methodologies, probability distributions, and confidence intervals to satisfy external audit requirements.

Upskilled internal teams on the intersection of stochastic modeling, machine learning risk thresholds, and compliance-by-design architectures.

Danske Bank

IT Risk, GRC and Digital Compliance Senior Lead June 2020 to August 2022 | Copenhagen, Capital Region, Denmark

Led and coached risk, internal control, and compliance specialists and consultants.

Established and maintained a cyber risk and control program to ensure that bank-wide IT systems and information assets were adequately protected.

Assessed information security, cybersecurity, cloud services, and IT risks against industry best practices (ISO 27001, 27701, NIST 800-53, COBIT, SOC 1 and 2) and EBA regulatory requirements.

Head of Supplier Due Diligence Compliance Strategy and Procurement Center of Excellence (September 2019 to July 2020): Piloted a centralized due diligence process to comply with EBA guidelines on outsourcing arrangements. Managed ongoing due diligence of suppliers regarding GDPR and ethical procurement.

ISS A/S

Head of the ISS Center of Excellence for Risk Management and Compliance June 2018 to September 2019 | Copenhagen Area, Capital Region, Denmark

Established the Center of Excellence (CoE) in risk management, internal controls, and compliance in collaboration with Deloitte Denmark.

Drafted and supervised global governance policies to meet Board needs and comply with Fortune Global 500 client requirements.

Integrated risk and control frameworks and governance models into global and local procedures aligned to ISO 31000.

Monitored risk treatment plans to meet business and compliance requirements, such as GDPR, DPIA, ISO 27001, financial reporting, and labor laws.

Deloitte

Senior Manager Operational Risk and Risk Advisory June 2017 to June 2018 | Copenhagen Area, Denmark

Led, managed, and delivered a portfolio of risk and control consultancy projects in coordination with Deloitte North West Europe.

Oversaw engagements in business process and control transformation, risk strategy, operational risk assessment, compliance audits, internal audit outsourcing, IT, SAP, GDPR, and SOX process review.

Main projects managed: Cybersecurity governance for a global energy company; Internal control transformation for a global manufacturer; GDPR compliance for a top national bank; Third-party compliance audits for a global pharma company.

Veolia

Risk Management and Internal Controls Director May 2011 to June 2017 | Madrid Area, Spain

Monitored compliance with the corporate program and methodology to continuously assess, treat, and report on risk for 80 subsidiaries in Iberia and LatAm.

Led a team of 14 risk and audit specialists, developing control self-assessments and risk identification tools under ISO 31000, ISO 19600, ISO 37001, COSO, COBIT, and GDPR.

Planned for SOX 404 scope, testing, and reporting, presenting pragmatic GRC solutions to upper management and the CFO.

Tenaris

Compliance Audit Coordinator August 2008 to September 2010 | International

Developed a comprehensive corporate compliance assurance program governing SEC, FCPA, SOX, US GAAP, IFRS, and OFAC requirements.

Supported SAP GRC and Business Intelligence initiatives (MicroStrategy). Engineered an automated alerting system to flag high-risk transactions.

Baker Hughes

Business Process Support - SAP / Finance Business Specialist and Compliance Auditor April 2006 to June 2008 | Houston, Texas Area

Coordinated process design and re-engineering utilizing internal project management methodology and ITIL.

Conducted SOX 404 compliance audits and financial reviews in international locations, identifying and reporting internal control deficiencies. Won the Baker Hughes Core Value Award (in gold) after improving audit methodology to maximize SAP resources.

ExxonMobil

Inventory and Accounting Compliance Specialist March 2005 to April 2006 | Dallas/Fort Worth Area

Controlled and reported on the migration of the finance and control process from the crude oil accounting department to a new shared service center. Assessed and mitigated market, credit, and operational risks related to trading activities.

Deloitte

Senior Risk, IT and SOX Compliance Consultant / Senior Financial Auditor January 2001 to March 2005

Performed Sarbanes-Oxley Act, risk, operational, and IT controls audits. Tested general computer controls using Audit Command Language (ACL). Analyzed financial statements for compliance with policies, IFRS, and US GAAP.

Education

Degree	Institution	Period
MBA in Organizational Management	Escuela Superior de Negocios y Tecnologias	2010 to 2011
International Diploma in Business, Management and Administration	University of Cambridge	2010 to 2011
Business Administration and Certified Public Accountant (CPA)	Universidad del Centro Educativo Latinoamericano	1995 to 2000

Courses and Global Certifications

Certified Chief AI Officer (CAIO), Copenhagen Compliance
Quantitative Finance with R (Portfolio optimization, asset pricing, risk management)
CRISC: Certified in Risk and Information Systems Control
CISSP: Certified Information Systems Security Professional
ISO 37301 Compliance Management Systems
PMI Agile Certified Practitioner (PMI-ACP)
IBM Cybersecurity Analyst Professional Certificate
CISRM - Certified Information Systems Risk Manager
IT Risk Assessment Practices
Governance and Risk Management

Languages

Language	Proficiency
English	Native or Bilingual
Spanish	Native or Bilingual
French	Professional Working

Skills

AI Governance, Responsible AI, Quantitative Risk Management, Enterprise Risk Management (ERM), GRC Frameworks, EU AI Act Compliance, ISO 42001, NIST AI RMF, Algorithmic Auditing, Model Risk Management, AI Risk Assessments, Python, R Programming, Monte Carlo Simulations, Value at Risk (VaR), Predictive Modeling, Machine Learning, TensorFlow, PyTorch, Scikit-learn, XGBoost, SAP GRC, SAP FiCo, Internal Controls, SOX 404, GDPR Compliance, FCPA, ISO 27001, ISO 27701, ISO 37301, COSO Framework, IT Governance, COBIT, ITIL, Third-Party Due Diligence, Data Privacy, Cybersecurity, NIST 800-53, MITRE ATLAS, Threat Modeling, AI Ethics, Bias Detection, Adversarial Testing, Generative AI Governance, Model Validation, Backtesting, Stress Testing, Loss Exceedance Curves, Financial Exposure Modeling, Risk-Adjusted ROI, Quantitative Risk Analysis, Stochastic Modeling, Data Architecture, Process Automation, Business Intelligence, MicroStrategy, SQL, AWS DataBrew, ServiceNow AI, Robotic Process Automation (RPA), Six Sigma, KPI Development, Data Migration, Continuous Improvement, Root Cause Analysis, Business Process Optimization, Internal Audit, External Audit, Compliance Audits, Performance Audits, Financial Audits, US GAAP, IFRS, OFAC Compliance, Export Controls, Anti-Corruption, ESG Reporting, Data Governance, Cloud Governance, AI Threat Modeling, STRIDE, DREAD, ISO 31000, ISO 23894, NIS 2 Compliance, DORA Compliance, CCPA Compliance, Red Teaming, AI Impact Assessments, Model Interpretability, Algorithmic Accountability, Executive Management, Board Reporting, Change Management, Strategic Planning, Business Transformation, Process Improvement, Risk Communication, Cross-Functional Leadership, Team Development, Stakeholder Management

Publications

Book: AI Management Systems: Operational Playbook for Chief AI Officers and Compliance Risk Managers

Publisher: Google Play Books / Apple Books / Global Retailers ISBN-13: 9798233615009

This flagship book positions AI management as a board-level obligation rather than a technology side project, giving Chief AI Officers, risk leaders and compliance managers a complete, end-to-end operating system for AI governance. It translates the requirements of the EU AI Act, ISO/IEC 42001 and the NIST AI Risk Management Framework into concrete engineering and oversight tasks that can be assigned, tracked and audited.

The work introduces a "Moneyball" approach to AI risk, replacing subjective heat maps with rigorous financial quantification of algorithmic bias, model drift, security failures and operational disruptions. Readers learn how to design lifecycle governance from feasibility and board lexicons through deployment and decommissioning, supported by integrated impact, vulnerability and threat assessments. A central AI Control Matrix links system telemetry, alerts, SLAs and regulatory clauses, enabling transparent, real-time assurance.

The book also covers human-AI architectures, workforce psychology and automation anxiety, ensuring AI portfolios remain value-accretive assets rather than latent liabilities. For organizations looking to build ROI-positive, responsible AI programs that can stand up to regulators, auditors and investors, this publication serves as a practical blueprint connecting the data science lab to the executive suite.

Paper: Standardized Threat Taxonomy for AI Security, Governance, and Regulatory Compliance

Published in: arXiv / AlphaXiv / Open Science Repositories DOI: arXiv:2511.21901

This research provides one of the first rigorous bridges between technical AI vulnerabilities and financial risk quantification, filling a major gap between frameworks like MITRE ATLAS and regulatory mandates such as the EU AI Act. It introduces the AI System Threat Vector Taxonomy, an ontology of 9 Critical Domains and dozens of threat categories, covering misuse, poisoning, hallucinations, privacy leakage, drift and more, empirically validated against 133 real-world AI incidents.

By explicitly mapping each threat domain to ISO/IEC 42001 controls and NIST AI RMF functions (especially the Map and Measure phases), the paper creates a standardized, auditable bridge from incident patterns to governance controls and documentation pathways. The taxonomy supplies structured inputs for convolved Monte Carlo models, enabling organizations to move beyond qualitative traffic-light charts and perform robust quantitative risk assessments on AI systems, including loss distributions, regulatory penalty scenarios and customer-churn impacts.

It also outlines how AI auditors, red-teaming specialists and compliance officers can use the taxonomy as a checklist, test scope definition and methodology for demonstrating "known and foreseeable risks" under the EU AI Act.

Paper: Quantitative Risk Assessment in R: An Open-Source Convolutional Framework for Modeling Uncertainty and Reserves

Published in: Quantitative Finance and Risk Management / Zenodo DOI: 10.5281/zenodo.17687261

This technical monograph delivers a free, open-source framework for quantitative risk assessment using Monte Carlo and convolution methods in R, making industrial-grade probabilistic modeling accessible to teams previously constrained by expensive proprietary tools. It replaces simplistic risk matrices and deterministic scoring approaches with a mathematically sound process that integrates discrete event frequencies, such as Poisson-modeled occurrences, with continuous loss magnitudes modeled via Lognormal distributions.

The paper offers executable R scripts that allow practitioners to run 100,000-plus simulations in seconds on standard hardware or cloud notebooks, producing risk statistics, contingency reserves, histograms and loss exceedance curves. These scripts can be directly embedded into budgeting, financial plans, legal claims valuation, cyber risk analysis, compliance exposure assessments and operational risk studies, giving organizations a repeatable way to quantify "fat tail" risks that traditional averages miss.

The work also reports empirical performance metrics, such as median loss estimates and percentile-based reserve levels, showing how probabilistic modeling can materially improve reserve adequacy and decision quality compared with subjective methods. By publishing under an open-science model, the study promotes transparency, replicability and community enhancement.

Book: GRC Framework: Governance for Risk and Compliance

Publisher: Ediciones Roble

This book lays the conceptual foundation for enterprise Governance, Risk and Compliance programs, serving as a practical guide for organizations seeking to align board expectations, regulatory demands and operational execution under a unified GRC framework. It explains how governance structures, risk taxonomies and compliance processes can be integrated into a single operating model that supports strategy execution rather than merely documenting controls.

The work covers principles drawn from ISO 31000, COSO and international compliance standards, translated into pragmatic tools such as policy architectures, roles and responsibilities matrices, and risk and control libraries. Readers learn how to construct governance models that connect group-level oversight with local procedures, shared service centers and front-line operations.

The book emphasizes how to embed risk and compliance into planning, budgeting and performance management cycles, ensuring that risk information becomes a driver of decisions instead of a reporting afterthought.

Proprietary Methods, Tools and Assets

AI Management Systems Playbook and AI Control Accelerator

A proprietary AI Management System that operationalizes AI governance for boards, CAIOs, and GRC leaders, derived from AI Management Systems: Operational Playbook for Chief AI Officers and Compliance Risk Managers. It translates EU AI Act, ISO/IEC 42001 and NIST AI RMF requirements into concrete roles, workflows, and layered controls, anchored by an AI Control Matrix that links real-time telemetry (drift, hallucinations, failure modes), impact thresholds, SLAs, and contractual clauses to specific control owners and escalation paths.

The framework covers full lifecycle governance, from feasibility and board lexicon through deployment, monitoring, and secure decommissioning, alongside structured assessment protocols (risk/impact, threat, vulnerability) and explicit human-AI architecture patterns (teams, psychology, automation anxiety, delegation limits).

AI System Threat Vector Taxonomy and Quantification Model

A semi-proprietary threat taxonomy and quantification model, based on Standardized Threat Taxonomy for AI Security, Governance, and Regulatory Compliance. It codifies nine primary AI threat domains and dozens of detailed attack categories, including misuse, poisoning, prompt injection, hallucinations, data leakage, model theft, and drift, validated against more than one hundred real-world incidents.

Each threat is mapped to ISO/IEC 42001 control themes and NIST AI RMF functions (map, measure, manage, govern) so every technical failure mode has a clear governance, security, and compliance response. On this ontology is layered a Quantitative Risk engine that converts threat profiles into loss distributions via Monte Carlo and compound frequency-severity models, enabling translation of AI vulnerabilities into reserves, budgets, capital allocation and liability caps.

AI GRC Framework Datasets and Governance Ontology Library

A curated library of machine-readable AI GRC datasets, published as governance-ready resources under the label "AI GRC Framework - AI Risk and Threat Model" and ISO-42001 mapping datasets. The library encodes 20+ AI-relevant standards and guidance documents, ISO 42001, 42005, 23894, 38507, 25059, the EU AI Act, OWASP LLM Top 10, MITRE ATLAS, ENISA threat landscapes, into structured ontologies and JSON/CSV datasets.

Core tables include AI Risk Scenarios, AI Threat Vectors, AI Loss Taxonomy, AI Quality Objectives, and AI Control Families, each mapped to specific requirements, control IDs, and indicative financial ranges. These assets can be ingested into GRC platforms, risk registers, internal AI governance tools, or used to fine-tune governance-aware LLMs for Digital Compliance and AI Governance use cases.

QUANTRRA Convolutional Quantitative Risk Framework in R and Python

An open-source but professionally curated Quantitative Risk engine, documented in Quantitative Risk Assessment in R: An Open-Source Convolutional Framework for Modeling Uncertainty and Reserves and supporting GitHub repositories. QUANTRRA implements compound frequency-severity models using Poisson (or mixed) frequency and lognormal (or alternative) severity, solved via Monte Carlo and numerical convolution to generate full loss distributions, reserves, exceedance curves, and capital metrics.

The codebase is optimized to run tens of thousands of simulations on commodity hardware or cloud notebooks and includes utilities for parameter calibration, sensitivity analysis, and stress testing across operational, cyber, legal, and compliance risk scenarios.

Correlations Systemic Risk Index and Network Modeling Toolkit

A systemic AI and GRC risk methodology branded as invisible correlations, combining PCA, correlation analysis, and network graph techniques to move beyond independent risk registers. The toolkit models cascading failures across AI systems, cyber assets, business processes, and compliance obligations, quantifying first-, second-, and third-order impacts through shock propagation simulations.

It incorporates scenario-based war-gaming and produces a composite Systemic Risk Index that prioritizes interventions where they deliver the highest resilience per unit cost. For executive stakeholders, it reframes risk from static lists to dynamic system behavior under stress, showing how failure in a single AI-augmented process can propagate into regulatory breaches, financial loss, and reputational damage across regions.

Regression and AI Risk Modeling Suite (Python / Scikit-learn / TensorFlow)

A suite of Python notebooks and reusable components that apply regression and machine learning to predict compliance, legal, operational, or cyber incidents from historical loss data, control metrics, and context variables. The suite includes generalized linear models, tree-based methods, and neural networks, with a structured approach to separating irreducible baseline risk from sensitivity to specific controls and business drivers, making coefficients and feature importance explainable at board level.

Built on scikit-learn and TensorFlow, with baked-in governance guardrails (train/validation splits, error analysis, stability checks, fairness metrics, and explainability via SHAP/LIME), the suite turns models into Responsible AI tools for early-warning systems, capacity planning, and targeted internal audit.

AI Risk Assessment and Corporate GPT Governance Toolkit

A practical assessment and governance toolkit for internal GPT-style deployments and LLM-based assistants, built from workshop material and Risk Awareness Week sessions. It combines structured questionnaires, scenario libraries, and quantitative templates to evaluate threats such as prompt injection, data exfiltration, hallucination-driven decisions, and unauthorized training data use.

The toolkit includes impact assessment forms, RACI templates, and spreadsheet or script-based risk calculators that map each scenario to business actors, attack vectors, technical and organizational controls, and estimated loss ranges. The emphasis is on translating technical vulnerability language into risk narratives that product owners, architects, compliance officers, and internal audit can act on.

AI-Aware Contract and SLA Clause Library

A structured library of contract clauses, KPIs, and SLA patterns that embed AI Risk Management and Responsible AI obligations directly into commercial agreements and procurement templates. The library covers topics such as model performance baselines, acceptable drift and retraining thresholds, explainability and logging requirements, data-use and retention rules, security controls, audit and access rights, indemnities, and tiered liability caps linked to modeled loss distributions.

It leverages the threat taxonomy and quantification work to define objective metrics and financial triggers, ensuring that contracts are anchored in realistic risk assumptions rather than arbitrary numbers.

AI GRC Accelerator Package for Certifications, Training and Executive Education

A modular AI GRC Accelerator used in CAIO and Director of AI Governance programs and executive education at institutions such as IE Law School. It bundles structured curricula, maturity models, role charters, risk appetite templates for AI, control catalogues, assessment workflows, case studies, and exam-style scenarios into a coherent learning path.

The accelerator covers core domains, AI Governance, AI Risk Management, Quantitative Risk, Responsible AI, Algorithmic Auditing, and Digital Compliance, allowing organizations to train cohorts of executives, risk managers, auditors, and product leads on consistent methods.

Internal Audit and GRC Analytics Starter Kits (Python / R / Excel)

A family of lightweight analytics kits designed to help internal audit, compliance, and GRC teams adopt quantitative techniques without needing full-time data scientists. The kits provide parameterized scripts and templates for sampling optimization, anomaly detection in transactions or logs, control-failure simulation, portfolio-level risk aggregation, and visualization of loss exceedance curves and confidence intervals.

Built primarily in Python and R with Excel front-ends, they map directly to standard assurance questions: which areas to prioritize in the audit plan, what level of residual risk remains after remediation, and how to evidence control effectiveness quantitatively.

Thought Leadership and Analyst Platforms

Recognized Global Thought Leader and Ranked Expert by Thinkers360

Thinkers360 is the world's largest platform for ranking and credentialing business thought leaders, analysts, authors, and influencers across technology, management, and professional disciplines. The platform uses a proprietary algorithm to score and rank individuals based on the quality, consistency, and reach of their published content, speaking engagements, and advisory contributions.

Hernan Huwyler is profiled as a Director at IE Law School and recognized for sustained, high-impact contributions in AI Governance, AI ethics, risk management, compliance, GRC, education, and predictive analytics. Being ranked on Thinkers360 provides independent, third-party validation of thought leadership status, which is used by conference organizers, media outlets, corporate procurement teams, and executive recruiters to identify and vet subject matter experts for keynote speaking, advisory boards, freelance consulting, and executive training engagements worldwide.

Thinkers360 Badges

Top 10 Thought Leader in AI Ethics Hernan Huwyler is ranked among the top 10 global thought leaders in AI Ethics by Thinkers360, placing him in an elite group of recognized experts worldwide whose published work, speaking engagements, and advisory contributions on the ethical dimensions of artificial intelligence have been independently evaluated and scored by the platform's algorithm. This ranking validates his authority on fairness, bias mitigation, transparency, accountability, and the integration of Responsible AI principles into corporate governance and regulatory compliance frameworks.

Top 10 Thought Leader in AI Governance Hernan Huwyler is ranked among the top 10 global thought leaders in AI Governance by Thinkers360, confirming his position as one of the recognized experts worldwide in the design, implementation, and oversight of enterprise AI Governance frameworks. This ranking reflects the depth and consistency of his published research, executive training programs, consulting engagements, and conference presentations on AI lifecycle governance, EU AI Act compliance, ISO/IEC 42001 implementation, NIST AI RMF alignment, and board-level AI strategy.

Top 25 Thought Leader in GRC (Governance, Risk Management, and Compliance) Hernan Huwyler is ranked among the top 25 global thought leaders in GRC by Thinkers360, recognizing his two-decade track record of designing, implementing, and directing integrated GRC frameworks for multinational organizations across six industries and four continents. This ranking reflects his published book on GRC frameworks, his executive education programs at IE Business School, and his operational leadership of GRC functions at Capgemini, Danske Bank, Milestone Systems, ISS, Deloitte, and Veolia.

Top 25 Thought Leader in Risk Management Hernan Huwyler is ranked among the top 25 global thought leaders in Risk Management by Thinkers360, validating his expertise in enterprise risk management, Quantitative Risk modeling, operational risk, AI risk assessment, cyber risk, compliance risk, and financial risk across regulated industries. This ranking reflects his published research on Quantitative Risk assessment using Monte Carlo simulation in R, his design and backtesting of probabilistic risk models, and his teaching of risk management methodologies at IE Business School.

Top 50 Thought Leader in Education Hernan Huwyler is ranked among the top 50 global thought leaders in Education by Thinkers360, reflecting his 13-year career as a professor, executive education director, and training program designer at IE Business School, Universidad Complutense de Madrid, UNIR, Comillas Pontifical University and ICADE, CEF, and Copenhagen Compliance. This ranking recognizes his development of the Certified Chief AI Officer (CAIO) program and his directorship of the Advanced Compliance Program at IE Law School.

Top 50 Thought Leader in IT Operations Hernan Huwyler is ranked among the top 50 global thought leaders in IT Operations by Thinkers360, recognizing his expertise in IT risk management, IT governance, cybersecurity operations, technology risk assessment, and the integration of AI systems into enterprise IT environments. This ranking reflects his operational leadership at Danske Bank, Milestone Systems, and Capgemini, as well as his certifications in CRISC, CISRM, CISSP, and IBM Cybersecurity.

Top 100 Thought Leader in Legal and IP Hernan Huwyler is ranked among the top 100 global thought leaders in Legal and IP by Thinkers360, reflecting his work at the intersection of regulatory compliance, corporate legal obligations, intellectual property protection, and AI regulation. This ranking recognizes his directorship of the Advanced Compliance Program at IE Law School, his published work on corporate criminal liability, anti-corruption compliance, data privacy regulation, and the EU AI Act.

Top 100 Thought Leader in Predictive Analytics Hernan Huwyler is ranked among the top 100 global thought leaders in Predictive Analytics by Thinkers360, recognizing his technical proficiency in building and validating predictive models using Python, R, TensorFlow, PyTorch, Scikit-learn, and XGBoost. This ranking reflects his design of Quantitative Risk models using Monte Carlo simulation and his published open-source framework for convolutional Monte Carlo risk assessment in R.

Academic and Institutional Affiliations

IE University, IE Law School, and IE Business School

Academic Director, Professor, Executive Education Director, and Speaker

IE University is one of Europe's most prestigious business schools, consistently ranked among the top 10 in Europe and top 30 globally by the Financial Times, QS, and The Economist. IE is recognized worldwide for its innovation in executive education, entrepreneurship, and technology-driven learning.

Hernan Huwyler serves as Academic Director of the Advanced Compliance Program at IE Law School and holds a long-standing faculty appointment teaching AI Governance, compliance, predictive analytics, internal control, risk management, and GRC across master and postgraduate programs. He leads AI-enabled learning platforms and case-based teaching across compliance, risk, audit, cybersecurity, and finance for working executives.

Expert Contributor at IE Insights (IE University Thought Leadership)

IE Insights is the thought leadership and observatory platform of IE University, publishing expert analysis, research commentary, and practitioner perspectives on business, technology, governance, and global affairs. The platform serves as the institutional voice of IE's faculty and associates, reaching a global audience of executives, policymakers, and academics.

Hernan Huwyler is recognized as an author and expert on governance, risk, compliance, and AI Governance for IE Insights, where he publishes and contributes as an institutional expert on the intersection of artificial intelligence, corporate compliance, and enterprise risk management.

The Institute of Internal Auditors (IIA), Madrid Chapter

Member and Co-Chairman of the Technical Committee for Non-Financial Assurance

The Institute of Internal Auditors is the global professional association for internal auditors, with more than 230,000 members across 170 countries. The IIA sets the International Standards for the Professional Practice of Internal Auditing and provides the CBOK that defines the profession worldwide.

Hernan Huwyler is a member of the IIA Madrid Chapter and serves as co-chairman of the technical committee providing guidance on non-financial reporting and assurance standards, including ISAE 3000, ISAE 3402, SSAE 16, and SOC 1/2 reporting. This co-chairmanship is particularly relevant for Algorithmic Auditing and AI assurance, as the IIA is actively developing guidance on how internal audit functions should address AI systems within their audit universe.

Researcher, Speaker, and CAIO Program Lead and Instructor at Copenhagen Compliance

Copenhagen Compliance is a leading Nordic compliance, governance, and risk management organization that develops and delivers professional certification programs, training tools, templates, and research for compliance and risk practitioners across Scandinavia and internationally. The organization is closely associated with the Information Security Institute and operates at the intersection of regulatory compliance, data protection, information security, and AI governance.

Hernan Huwyler serves as a researcher and speaker promoting compliance and risk practices, tools, and training. He is also the program lead and instructor for the Certified Chief AI Officer (CAIO) certification, a specialized professional credential focused on AI Governance, AI risk management, compliance, and strategic AI implementation aligned with ISO 42001, ISO 23894, NIST AI RMF, and the EU AI Act.

Researcher at Information Security Institute

The Information Security Institute is a research and professional practice organization dedicated to advancing the protection of data, information systems, and IT assets through the development and promotion of security standards, audit procedures, and certification programs. The Institute operates in alignment with ISO 27001 and ISO 27002 and provides guidance on security governance, risk assessment, and assurance.

Hernan Huwyler serves as a researcher developing audit procedures and programs for information security certifications and assurance engagements. This affiliation reinforces his credentials in cybersecurity governance, IT risk management, and the security dimensions of AI Governance.

Collaborator, Researcher, and Lecturer at EU GDPR Institute

The EU GDPR Institute is a specialized research and professional practice organization focused on data protection, privacy governance, and regulatory compliance under the European Union General Data Protection Regulation. The Institute promotes data protection tools, conducts research on compliance methodologies, and develops training programs for privacy professionals.

Hernan Huwyler serves as a collaborator, researcher, and lecturer, researching methodologies to comply with and demonstrate assurance on GDPR requirements. This affiliation is directly relevant to AI Governance and Responsible AI, as GDPR intersects with the EU AI Act on matters of automated decision-making, data protection impact assessments, privacy by design, and the processing of personal data by AI systems.

Collaborator, Speaker, and Research Committee Member at CUMPLEN (Spanish Compliance Officers Association)

CUMPLEN is the leading professional association for compliance officers in Spain, bringing together compliance practitioners, legal professionals, academics, and corporate governance leaders to advance the practice of corporate compliance across Spanish-speaking markets. The association organizes professional events, publishes research, and advocates for compliance standards and best practices.

Hernan Huwyler is a collaborator and speaker, serving as a member of the research committee responsible for creating content and organizing professional events for members. This affiliation positions him within the Spanish-speaking compliance community as both a recognized practitioner and thought leader.

Expert Contributor at KuppingerCole Analysts AG

KuppingerCole is one of the world's leading independent analyst firms specializing in identity management, cybersecurity, AI governance, and digital sovereignty. The firm produces authoritative research, organizes the European Identity and Cloud Conference, and advises enterprise clients and government bodies on technology governance and security strategy.

Hernan Huwyler maintains a listed speaker profile with KuppingerCole for major identity, security, and AI Governance conferences, where he is described as a Governance, Risk, and Compliance director and Academic Director at IE Law School. Being listed as a KuppingerCole speaker provides significant credibility with European CISOs, CIOs, Chief AI Officers, and technology governance leaders.

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Paper for hewyler/hernan-huwyler-ai-governance-portfolio

Standardized Threat Taxonomy for AI Security, Governance, and Regulatory Compliance

Paper • 2511.21901 • Published Nov 26, 2025