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AI CERTS® certification

AI+ Chief AI Officer Practitioner™

Formerly known as AI+ Chief AI Officer™ AI Leadership for Chief Officers: Driving Innovation and Intelligence

AI+ Chief AI Officer Practitioner™ certification badge

Course overview

Review the course before deciding whether it is suitable.

Leadership Upgrade: Equip C-suite executives to lead AI-driven innovation Efficiency Focus: Use AI tools to optimize operations, decision-making, and resources Strategic Role: Aligns AI implementation with business intelligence goals Course + Exam: Combines theory and practical insights in a compact format

Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
Instructor-Led: 1 day (live or virtual)Self-Paced: 8 hours of content
Exam format
50 questions, 70% passing, 90 minutes, online proctored exam
Prerequisites
Basics of business management, Experience in a leadership or business admin role, Familiarity with fundamental AI concepts.

Course focus

Why this certification may be relevant.

01

Drive AI Strategy:

Learn to develop and execute a strategic AI roadmap to guide organizational growth and innovation.

02

Manage Cybersecurity Risks:

Gain insights into mitigating cybersecurity threats and ensuring AI systems' security and privacy.

03

Foster Data-Driven Decisions:

Master techniques to utilize data effectively for informed decision-making and business optimization.

04

Build High-Performing Teams:

Learn strategies to assemble and lead AI-focused teams that drive successful project execution.

05

Navigate Regulatory Frameworks:

Understand the regulatory environment around AI and ensure compliance while maximizing business impact.

Who it may suit

Check the intended audience against your experience and goals.

Course content

Modules supplied by AI CERTs.

Open each module to review the stated topics.

01Module 1: Foundations of AI and Leadership in the Digital Era
  • 1.1 Defining Artificial Intelligence
  • 1.2 Key AI Technologies
  • 1.3 The CAIO’s Unique Role
  • 1.4 Navigating Cybersecurity Challenges
  • 1.5 Establishing Cross-Departmental Collaboration
  • 1.6 Case Study
02Module 2: Crafting a Strategic AI Roadmap
  • 2.1 Aligning AI with Business Objectives
  • 2.2 Setting Measurable Goals
  • 2.3 Identifying Opportunities for Innovation
  • 2.4 Engaging Stakeholders Across Departments
  • 2.5 Monitoring Progress and Adjusting Plans
  • 2.6 Case Study
03Module 3: Building a High-Performance AI Team
  • 3.1 Key Roles in an AI Team
  • 3.2 Recruitment Strategies for Top Talent
  • 3.3 Cultivating a Collaborative Culture
  • 3.4 Continuous Learning Initiatives
  • 3.5 Evaluating Team Performance
  • 3.6 Case Study
04Module 4: Ethics in AI Governance and Risk Management
  • 4.1 Integrating Ethical Frameworks into AI Development
  • 4.2 Conducting Ethical Impact Assessments
  • 4.3 Developing Risk Mitigation Strategies
  • 4.4 Establishing Transparency Protocols
  • 4.5 AI Governance Models and Frameworks
  • 4.6 Case Study
05Module 5: Data-Driven Decision-Making and Business Impact Assessment
  • 5.1 The Role of Data in AI Initiatives
  • 5.2 Business Impact Assessment Frameworks
  • 5.3 Measuring ROI from AI Investments
  • 5.4 Hypothesis Testing in AI Projects
  • 5.5 Resource Allocation Strategies
  • 5.6 Case Study
06Module 6: Driving Organization-Wide Adoption of AI
  • 6.1 Creating Change Management Strategies
  • 6.2 Communicating the Value of AI Initiatives
  • 6.3 Addressing Resistance to Change
  • 6.4 Metrics for Success Evaluation
  • 6.5 Case Study
07Module 7: Leveraging Generative AI for Business Innovation
  • 7.1 Understanding Generative AI Capabilities
  • 7.2 Identifying Areas for Innovation with Generative AI
  • 7.3 Integrating Generative Solutions into Business Processes
  • 7.4 Managing Risks Associated with Generative Applications
  • 7.5 Creating Interdepartmental Synergies with Generative AI
  • 7.6 Case Study
08Module 8: Capstone Project
  • 8.1 Project Overview and Objectives
  • 8.2 Collaborative Work Sessions
  • 8.3 Presentation Skills Workshop
  • 8.4 Final Presentations and Constructive Feedback
  • 8.5 Reflection on Key Takeaways from the Course Experience
09Optional Module: AI Agents for Chief AI Officer
  • 1. What Are AI Agents
  • 2. Key Capabilities of AI Agents for the Chief AI Officer
  • 3. Applications and Trends of AI Agents for the Chief AI Officer
  • 4. How Does an AI Agent Work
  • 5. Core Characteristics of AI Agents
  • 6. Types of AI Agents

Tools referenced by AI CERTs

Platforms and tools included in the course information.

LeewayHertz (ZBrain)C3.aiCoupa (LLamasoft)Zebra (Workcloud Demand Intelligence Suite)
Before you enrol

This course information is supplied through the AI CERTs catalogue. Kiwi Fern Education will confirm current availability, delivery arrangements, inclusions and fees before enrolment. The programme is not presented as a New Zealand Qualifications Authority qualification.

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