AI, Data, and Technology Governance Training Course: Understanding Ai Risk, Data Ethics, And Board Accountability

Introduction

In an era where Artificial Intelligence (AI) is rapidly transforming industries and reshaping business models, boards face an urgent imperative to understand not only the opportunities but also the profound risks and ethical considerations associated with these powerful technologies. This 5-day training course on AI, Data, and Technology Governance is meticulously designed to equip board members, senior executives, and governance professionals with the essential knowledge and strategic frameworks to effectively oversee AI adoption, navigate complex data ethics, and ensure robust board accountability in this new technological frontier. Participants will gain deep insights into assessing AI risk, developing responsible AI principles, ensuring data integrity and privacy, and establishing governance structures that foster innovation while safeguarding trust and mitigating potential harms.

This intensive program is tailored for Non-Executive Directors (NEDs), Executive Directors, CEOs, Chief Information Officers (CIOs), Chief Data Officers (CDOs), Legal Counsel, and other senior leaders with governance responsibilities over technology and data. It will empower attendees with methodologies for asking critical questions about AI development and deployment, understanding regulatory landscapes, overseeing the ethical use of data, building a culture of responsible AI, and integrating AI and data governance into the overall enterprise risk management (ERM) framework. By mastering the principles of AI, Data, and Technology Governance, this course aims to enable participants to proactively steer their organizations through the complexities of the AI revolution, ensure ethical innovation, and drive sustainable growth with accountability at its core.

Duration: 5 Days

Target Audience:

  • Non-Executive Directors (NEDs)
  • Executive Directors and C-suite Executives (CEOs, CFOs, COOs, CIOs, CTOs, CDOs)
  • Members of Audit, Risk, and Digital/Technology Committees
  • Board Chairs and Lead Independent Directors
  • Company Secretaries and Governance Professionals
  • Legal Counsel and General Counsels
  • Chief Compliance Officers and Ethics Officers
  • Heads of Enterprise Risk Management
  • Senior Regulators and Policy Makers
  • Aspiring Board Members seeking to understand AI and data governance.

Objectives: Upon completion of this course, participants will be able to:

  • Articulate the board's strategic oversight role in AI, data, and technology governance.
  • Understand the fundamental concepts of AI, its applications, and associated risks.
  • Navigate complex data ethics challenges and ensure responsible data stewardship.
  • Develop frameworks for ethical AI principles, trustworthy AI systems, and accountability.
  • Integrate AI and data governance into existing corporate governance and risk management structures.

Course Modules:

Module 1: The Board's Mandate in AI and Data Governance

  • Defining AI, data, and technology governance in the boardroom context.
  • The board's fiduciary duties and legal liabilities in the age of AI and big data.
  • Understanding the strategic imperative of AI adoption and its disruptive potential.
  • The critical link between robust governance, public trust, and organizational value.
  • Case studies of governance challenges and successes in AI and data.

Module 2: Understanding AI Systems and Their Risks

  • Introduction to Artificial Intelligence (AI) and Machine Learning (ML) concepts: types, capabilities, and limitations.
  • Identifying key AI-specific risks: algorithmic bias, explainability (XAI), privacy, security, societal impact, unintended consequences.
  • The AI lifecycle and where governance interventions are crucial.
  • Understanding AI's impact on decision-making processes and organizational operations.
  • Tools and frameworks for AI risk assessment and management.

Module 3: Data Ethics and Responsible Data Stewardship

  • Core principles of data ethics: fairness, transparency, accountability, privacy, security.
  • Navigating ethical dilemmas in data collection, usage, sharing, and retention.
  • The concept of data "for good" vs. data "for harm."
  • Ensuring data integrity, quality, and provenance.
  • Developing a data-driven ethical culture within the organization.

Module 4: Regulatory Landscape for AI and Data Privacy

  • Overview of emerging global AI regulations (e.g., EU AI Act, national AI strategies).
  • Key international data protection and privacy laws (e.g., GDPR, CCPA, local data acts).
  • Understanding cross-border data transfer regulations and their implications.
  • The board's role in ensuring compliance and anticipating future regulatory changes.
  • Legal and ethical considerations in AI deployment and liability.

Module 5: Building Trustworthy AI Systems and Accountability

  • Principles of trustworthy AI: robustness, security, safety, fairness, transparency, human oversight.
  • Implementing Responsible AI (RAI) frameworks and policies.
  • The importance of AI auditing and impact assessments.
  • Establishing clear accountability structures for AI development and deployment.
  • Whistleblower mechanisms and redressal processes for AI-related harms.

Module 6: Board Oversight of Cybersecurity for AI and Data

  • Cybersecurity challenges unique to AI systems and large datasets.
  • Protecting AI models from adversarial attacks, data poisoning, and manipulation.
  • Securing data pipelines, storage, and access controls.
  • The board's role in overseeing cyber resilience strategies for AI-driven operations.
  • Incident response planning for AI-related security breaches.

Module 7: Data Governance Frameworks and Implementation

  • Core components of a robust data governance framework: policies, roles, processes, technology.
  • The role of the Chief Data Officer (CDO) and data stewardship.
  • Data classification, cataloging, and metadata management.
  • Ensuring data quality and master data management.
  • Metrics for measuring data governance effectiveness.

Module 8: Integrating AI, Data, and Technology Governance into the Boardroom & Action Plan

  • Optimizing board committee structures for technology and data oversight (e.g., Technology, Digital, or ESG Committees).
  • Enhancing AI and data literacy among board members.
  • Fostering a culture of continuous learning and responsible innovation.
  • Embedding AI and data governance into the Enterprise Risk Management (ERM) framework.
  • Participants' action plans for enhancing AI, data, and technology governance within their organizations.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

 

Ai, Data, And Technology Governance Training Course: Understanding Ai Risk, Data Ethics, And Board Accountability in Costa Rica
Dates Fees Location Action