An Interactive 5-Day Training Course

Artificial Intelligence (AI) Ethics, Regulations & Compliance

Ensuring Responsible, Transparent and Compliant AI Across the Enterprise

Artificial Intelligence (AI) Ethics, Regulations & Compliance

Scheduled Dates

23 - 27 Nov 2026
Milan - Italy
$5,950
06 - 10 Dec 2026
Doha - Qatar
$5,950
07 - 11 Dec 2026
London - UK
$5,950
03 - 07 May 2027
London - UK
$5,950
23 - 27 Aug 2027
Amsterdam - The Netherlands
$5,950
23 - 27 Aug 2027
Online
$4,950
20 - 24 Sep 2027
Riyadh - Saudi Arabia
$5,950
06 - 10 Dec 2027
London - UK
$5,950

Why Choose this Training Course?

This Artificial Intelligence (AI) Ethics, Regulations & Compliance training course equips professionals with the knowledge and capabilities required to establish responsible AI practices, manage regulatory obligations and strengthen organisational oversight of artificial intelligence systems. As AI becomes increasingly integrated into business operations and decision-making, organisations must address ethical concerns, regulatory requirements and risks associated with automated and AI-assisted processes. Participants will examine the principles of fairness, transparency, accountability and human oversight while learning how these principles can be translated into practical governance policies and compliance controls.

The training course examines international AI governance frameworks, emerging regulatory requirements, AI risk assessment and the development of enterprise-wide compliance systems. Participants will explore the EU AI Act, GDPR considerations, the NIST AI Risk Management Framework and ISO/IEC 42001, alongside approaches to managing algorithmic bias, explainability, data protection and third-party AI risks. Particular attention is given to establishing governance responsibilities, documenting AI decisions, conducting compliance assessments and preparing for regulatory scrutiny. By integrating ethical principles with practical risk management and organisational governance, the course enables participants to develop structured approaches to responsible AI adoption and long-term compliance readiness.

This Artificial Intelligence (AI) Ethics, Regulations & Compliance training course will highlight:

  • Understanding ethical principles and responsible AI practices
  • Evaluating international AI regulations and governance frameworks
  • Identifying algorithmic bias, fairness and transparency risks
  • Establishing effective AI governance and compliance controls
  • Strengthening AI accountability, assurance and audit readiness
  • Developing responsible AI policies and implementation strategies

What are the Goals?

By the end of this training course, participants will be able to:

  • Apply ethical and responsible AI principles to organisational practices.
  • Interpret relevant AI regulatory frameworks and compliance requirements.
  • Identify and assess ethical, operational and regulatory AI risks.
  • Develop governance policies, accountability structures and compliance controls.
  • Evaluate AI assurance, monitoring and audit readiness requirements.
  • Develop a roadmap for strengthening responsible AI governance and compliance.

Who is this Training Course for?

This training course is specifically designed for professionals directly responsible for AI governance, regulatory compliance, risk oversight and responsible AI implementation, including:

  • AI Governance Managers and Officers
  • Responsible AI and AI Ethics Professionals
  • Regulatory Compliance Managers and Officers
  • AI Risk Management Professionals
  • Governance, Risk and Compliance (GRC) Managers
  • AI Assurance and Internal Audit Professionals
  • Data Protection and Privacy Officers
  • Model Risk Management Professionals
  • Legal and Regulatory Advisors responsible for AI compliance

How will this Training Course be Presented?

This training course combines expert-led presentations, regulatory examples, AI governance scenarios and structured discussions. Participants will examine ethical dilemmas, AI risk assessments, governance frameworks and organisational compliance challenges. Practical exercises will focus on evaluating AI risks, establishing oversight responsibilities and developing appropriate compliance controls. The methodology emphasises translating regulatory and ethical principles into governance arrangements that support responsible AI deployment and ongoing assurance.

Organisational Impact

Organisations will benefit from:

  • Stronger governance and accountability for AI systems
  • Improved identification and management of AI-related risks
  • Greater preparedness for evolving regulatory requirements
  • More consistent ethical and responsible AI practices
  • Improved transparency, documentation and compliance assurance
  • Stronger organisational confidence in AI adoption

Personal Impact

Participants will develop:

  • Greater understanding of AI ethics and regulatory requirements
  • Improved capability in evaluating AI compliance risks
  • Stronger knowledge of AI governance frameworks and controls
  • Better understanding of algorithmic fairness and accountability
  • Greater confidence in assessing AI assurance requirements
  • Improved ability to develop responsible AI policies and strategies

Daily Agenda

Day 1: Foundations of Ethical and Responsible AI
  • Understanding the need for AI ethics in modern organisations
  • Core principles: fairness, transparency, accountability, and human oversight
  • Ethical risks across machine learning, automation, and predictive analytics
  • Distinguishing between ethical AI, lawful AI, and trustworthy AI
  • Introduction to global AI ethics frameworks (OECD, UNESCO, NIST)
  • Challenges of implementing ethical principles in real-world environments
Day 2: Global AI Regulations and Emerging Compliance Standards
  • Overview of global AI regulatory landscape
  • Deep dive: EU AI Act, classification levels, and obligations
  • Understanding NIST AI Risk Management Framework
  • AI-related GDPR considerations: data minimisation, profiling, consent
  • Requirements for transparency, documentation, and human oversight
  • Preparing for future regulatory developments across regions
Day 3: AI Risk, Bias, Fairness, and Mitigation Strategies
  • Identifying sources of bias in datasets, models, and deployment
  • Evaluating fairness metrics and model performance
  • Assessing harm, unintended consequences, and discriminatory outcomes
  • Model transparency and explainability expectations
  • AI risk assessment techniques and risk scoring
  • Implementing mitigation controls across the AI lifecycle
Day 4: Designing AI Governance and Compliance Systems
  • Creating an organisational AI governance structure
  • Defining roles, responsibilities, and accountability lines
  • Documentation, audit trails, and lifecycle monitoring
  • Establishing model validation and approval processes
  • Responsible use policies, escalation procedures, and oversight controls
  • Embedding compliance into procurement and third-party AI systems
Day 5: Building a Responsible AI Culture and Future Readiness
  • Developing internal ethical standards and behaviour guidelines
  • Training and upskilling employees for AI literacy and governance
  • Managing change: communicating risks, responsibilities, and expectations
  • Integrating AI governance with corporate strategy and ESG commitments
  • Preparing for internal and external AI audits
  • Creating a long-term roadmap for responsible AI maturity

Certificate

  • Upon successful completion of this training course, delegates will be awarded an official PetroKnowledge Certificate of Completion, signed by the course facilitator. The certificate confirms successful participation and records the total learning hours completed.
  • Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.

Accreditation

NASBA Approved Training Courses

In Association With

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