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Humanizing Data & AI Strategy

4 hours

About Course

Humanizing Data & AI Strategy is an executive-level program based on Tiankai Feng’s human-centered approach to data and AI strategy.

The program explores how organizations can move beyond technology-first approaches and develop data and AI strategies that create business value while putting people, culture, trust, ethics, and organizational purpose at the center.

Drawing from Feng’s Humanizing Data Strategy and Humanizing AI Strategy, participants explore the 5Cs Framework — Competence, Collaboration, Communication, Creativity, and Conscience — and learn how these human capabilities influence the success of data and AI initiatives.

The program connects strategy, leadership, data, AI, governance, and organizational change to help leaders answer not only “What can we do with data and AI?”, but also “What should we do, and how can we do it responsibly?”

What Will You Learn?

  • By completing the program, participants will be able to:
  • Understand the human dimension of data and AI strategy and why technology alone does not guarantee transformation success.
  • Apply the 5Cs Framework: Competence, Collaboration, Communication, Creativity, and Conscience.
  • Connect data and AI initiatives with business objectives and organizational values.
  • Identify the human and organizational factors that can enable or derail data and AI initiatives.
  • Build stronger cross-functional collaboration between business, data, technology, and AI teams.
  • Communicate data and AI strategies in ways that are understandable and actionable for different stakeholders.
  • Foster creativity and innovation in data and AI initiatives.
  • Incorporate ethics, responsibility, trust, and human values into strategic decision-making.
  • Develop a more effective approach to AI adoption and organizational change.
  • Think critically about AI initiatives by asking not only “Can we do it?”, but also “Should we do it?” and “How can we do it right?”
  • Understand how data strategy and AI strategy are interconnected and why lessons from previous data-management challenges should inform today's AI transformation.
  • Develop a more human-centered and sustainable strategy for data and AI.

Material Includes

  • Humanizing Data & AI Strategy course materials
  • Instructor presentations and visual frameworks
  • 5Cs Framework reference materials
  • Strategic exercises and reflection activities
  • Case studies and real-world examples
  • AI strategy and governance discussion frameworks
  • Recommended readings and reference resources

Requirements

  • No advanced technical prerequisites are required.
  • Participants should have:
  • Basic familiarity with data and/or artificial intelligence.
  • An understanding of organizational or business strategy.
  • Interest in leading or participating in data and AI initiatives.
  • Experience working in a business, technology, data, or transformation environment is recommended.
  • Programming, data science, machine learning, or advanced AI knowledge is not required.
  • This positioning is important because Feng's approach deliberately focuses less on how AI works technically and more on how organizations work with AI effectively and responsibly.

Audience

  • Designed for professionals who influence or lead data, AI, digital transformation, innovation, technology, and business strategy, including:
  • Executives and senior leaders
  • Data & AI leaders
  • Chief Data, Analytics, Digital or AI Officers
  • Data strategists and governance professionals
  • AI product and transformation leaders
  • Business and technology managers
  • Digital transformation professionals
  • Consultants and advisors
  • Professionals responsible for AI adoption and organizational change

Course Content

WELCOME

  • SVFI Intro
    00:35
  • Tiankai Feng welcome
    02:48
  • 5 C’s Framework
    03:18

1st C – COMPETENCE

2nd C – COLLABORATION

3rd C – COMMUNICATION

4th C – CREATIVITY

5th C – CONSCIENCE

CAPSTONE PROJECT

CLOSING

Instructors

Tiankai Feng

Tiankai Feng

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2 Courses

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