IntelliCademy AI Transformation Leader
Take this course through FAU Continuing Education in partnership with Applied Technology Academy — live online or in the Boca Raton classroom, taught by ATA's practitioner instructors.
AI Transformation Leader is an advanced four-day course and certification for senior leaders, program managers, transformation officers and decision-makers re
Course Overview
- 32 hours of instruction across four days, delivered by IntelliGenesis instructors.
- Aligned to DCWF work roles AI Innovation Leader (902) and AI Adoption Specialist (753).
- Progresses from strategic foundations to applied governance and operational planning.
- Discussion-based learning, scenario analysis, planning exercises and decision-making activities.
Prerequisites
- Experience in leadership, management, program oversight, innovation, policy, operations or transformation-related roles.
- Familiarity with organisational decision making, strategic planning or enterprise initiatives.
- Basic understanding of emerging AI capabilities and their potential application.
- Ability to engage with policy, governance, risk and performance discussions at an organisational level.
- A laptop or device capable of accessing course materials and completing practical exercises.
What You'll Learn
Develop AI strategy and governance — create mission-aligned AI strategies, and design governance structures, oversight mechanisms and decision frameworks for responsible, sustainable adoption.
Manage risk, ethics and regulatory alignment — interpret and apply AI policies, regulations and ethical principles, and evaluate AI risk across security, privacy, bias, trustworthiness and operational use.
Plan for sustainable AI adoption — align resources, workforce capabilities, structures and investment, accounting for acquisition, funding, implementation and organisational change management.
Measure AI performance and mission impact — define success metrics and reporting that capture value, quality, efficiency and effectiveness, and lead continuous assessment.
Engage stakeholders and influence decision makers — advise senior leaders on opportunities, tradeoffs and risks, and promote AI literacy across stakeholder groups.
Oversee responsible AI operations — provide executive oversight aligned to risk tolerance, ethical frameworks and security standards, balancing innovation with control.
Apply core AI/ML concepts — explain fundamentals across the AI/ML lifecycle, select appropriate approaches, and oversee evaluation, deployment and monitoring.