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  1. Courses
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  3. GenAI For Sustainability

GenAI For Sustainability

This course offers a practical, reflective look at how GenAI supports sustainability, designed for sustainability professionals, social impact leaders, and AI practitioners focused on real-world impact.

Joyce Wong
Joyce Wong
Business | intermediate | 7 hours 30 minutes |   Published: Jun 2025

    Discussions

Overview

1KSTUDENTS*
98.9RECOMMEND*

This course includes:

  • On-demand videos
  • Practice assessments
  • Multiple hands-on learning activities
  • Exposure to a real-world project
  • 100% self-paced learning opportunities
  • Certification of completion

Sustainability and artificial intelligence are two of the most powerful forces shaping the future. Yet, they are often discussed in isolation. Sustainability professionals face growing challenges, including complex regulations, resource constraints, and the demand for transparent, data-driven strategies. Meanwhile, AI is transforming industries, offering new capabilities in analysis, automation, and problem-solving. How can these intersect? Can Generative AI (Gen AI) be leveraged for real environmental and social impact while ensuring ethical and responsible use? 

This course provides a practical, critically reflective approach to Gen AI’s role in sustainability. Unlike AI courses focused on technical skills or business efficiencies, this program is designed for sustainability professionals, social impact leaders, and AI practitioners seeking real-world applications. Participants will explore concrete use cases, including AI-powered sustainability strategy development, supply chain decarbonization, circular economy design, and social inclusion initiatives. 

Beyond showcasing AI’s potential, this course directly addresses its limitations and risks. AI itself has a significant ecological footprint, requiring vast amounts of energy and computational resources. While AI can support sustainability efforts, it must also be evaluated for its own environmental impact. Additionally, participants will examine bias, misinformation, and ethical concerns, ensuring AI applications promote fairness, accountability, and inclusivity rather than reinforcing inequalities. 

This is not a passive learning experience. Through case studies, discussions, and applied ideation, participants will critically assess the feasibility of AI-driven sustainability projects in their own fields. Whether working in corporate sustainability, social impact, entrepreneurship, or policy, learners will leave with actionable insights that can be directly applied to their work. 

As AI and sustainability continue to converge, professionals who understand both will be in high demand. This course equips learners with the knowledge and critical perspective needed to navigate this evolving landscape, ensuring they can lead conversations, make informed decisions, and drive meaningful changes. If you’re ready to explore how AI can be strategically and responsibly leveraged for sustainability, this course will provide the framework, tools, and insights to take action. 

Skills You Will Gain

Gen AI
Sustainability
AI Ethics
AI Impact Assessment
Data Analysis

Learning Outcomes (At The End Of This Program, You Will Be Able To...)

  • Explain the basics of Gen AI, its key competencies, potential benefits, ethical considerations, and limitations. 
  • Analyze the systemic aspects of environmental and social sustainability, and the potential application of Gen AI.
  • Apply learnings and insights from real-world use cases, and ideate their own Gen AI for sustainability projects.
  • Evaluate the feasibility and robustness of Gen AI for sustainability projects.

Prerequisites

Basic concepts of sustainability, basic computer skills, basic experience with AI technologies.

Who Should Attend

This course is ideal for sustainability professionals, social impact leaders, and practitioners working with Generative AI who are seeking to apply AI to real-world environmental and social challenges. It also welcomes individuals from diverse backgrounds—whether in corporate sustainability, nonprofits, public policy, entrepreneurship, or technology—who are curious about leveraging AI for good. Whether you’re looking to enhance your sustainability strategy, explore AI-driven innovation, or ensure ethical integration of emerging technologies, this course offers a practical and inclusive approach suited to professionals across sectors.

Curriculum

Instructors

*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Chapter 1: Introduction
2Chapter 2: Introduction to Generative AI and Sustainability
3Chapter 3: Gen AI for Climate Action and Circular Economy
4Chapter 4: Gen AI for Equity, Inclusion, and Social Good
5Chapter 5: Ethical and Environmental Challenges of AI
6Chapter 6: Conclusion

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Segment 04: What is Generative AI

Segment 05: Benefits of Gen AI for Businesses _ Sustainability

Segment 06: What is Sustainability

Segment 07: UN SDGs and Sustainability Frameworks

Segment 08: Reading - GenAI for the Global Goals

Segment 09: Hands-On-Learning: Interactive Activity: Ideating AI & Sustainability Use Cases

Segment 10: Introduction to Generative AI and Sustainability

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Segment 00: Welcome to the Course: Course Overview

Segment 01: Welcome and Course Overview

Segment 02: Introduction to GenAI

Segment 03: Sustainability Challenges _ AI’s Role

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Segment 11: AI for ESG data tracking and Gen AI for modelling and scenario planning-

Segment 12: Interview call with Max Mizi: Introduction on AI Meets Sustainability

Segment 13: Interview call with Max Mizi: GitHub’s Role in Climate Tech and Green Software

Segment 14: Interview call with Max Mizi: How GitHub Supports Global Green Innovation

Segment 15: AI for Sustainability Transition Strategization

Segment 16: AI in Circular Economy _ Eco-Design

Segment 17: Reading - How Supply Chains Benefit From Using Generative AI

Segment 18: GenAI for Climate Action and Circular Economy

Joyce Wong

Joyce Wong

With a distinguished background in cross-sector collaboration and qualitative research, she is deeply committed to advancing social innovation and sustainable development. Her academic training in historiography and postcolonial studies provides a strong foundation for understanding complex socio-economic dynamics, enabling her to navigate and address multifaceted challenges. Driven by a passion for launching and managing impactful, social-purpose projects, she expertly combines ecosystem building, user research, and design methodologies to drive meaningful change. Her expertise lies in steering social innovation projects and facilitating multi-stakeholder engagement, with extensive experience in designing and managing initiatives that bridge gaps across sectors, from social finance to community-building endeavors. In her role, she not only oversees project development but also leads advocacy and capacity-building programs that empower communities and organizations. Through strategic program design and rigorous impact measurement, she ensures that initiatives are both effective and sustainable. Beyond practical experience, she actively contributes to thought leadership in the field, presenting at international conferences and facilitating workshops on critical topics such as social innovation, youth empowerment, and the future of work. Her background in social finance, coupled with her skills in qualitative research and program management, equips her to provide deep insights and actionable strategies for driving positive social impact. With a focus on transformative change, she remains dedicated to fostering inclusive, resilient, and sustainable communities.
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You need to enroll in this course to access the curriculum. Click 'Enroll' to get started!

Segment 28: Environmental Cost of AI Training _ Usage

Segment 29: Strategies for Greener AI Models

Segment 30: Detect coded biases

Segment 31: Understand the limitations of AI

Segment 32: Readings - Generative AI’s Environmental Impact

Segment 33: Quiz - Ethical and Environmental Challenges of AI

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Segment 19: AI in Education Accessibility

Segment 20: Interview call with Louis: Introduction to Decisions lab

Segment 21: Interview Call with Louis: Personalizing Marketing with Generative AI

Segment 22: Interview call with Louis: From AI Personas to Real-World Impact in the Social Sector

Segment 23: AI for Social Impact Nonprofits

Segment 24: AI for Workplace Diversity _ Inclusion

Segment 25: Accessible Healthcare Information and Support

Segment 26: Reading - AI for Social Good

Segment 27: Quiz - GenAI for Equity, Inclusion, and Social Good

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Segment 34: Designing Sustainability Initiatives with Gen AI (Part 1)

Segment 35: Course wrap up video

Segment 36: Project: Real-World Solutions with Generative AI