Slava Matvejevs, Director of Innovation and Technology at WLSA Shanghai Academy, delivered the welcome address.

While schools around the world are asking how to respond to educational transformation in the age of AI, WLSA Shanghai Academy has delivered an answer through a comprehensive upgrade from infrastructure to pedagogical philosophy. Matvejevs pointed out that this past year’s journey had been bold and ambitious.

Leveraging a strong team of professional IT specialists, WLSA has rolled out a digital upgrade spanning core infrastructure, collaborative teaching platforms and campus data architecture, gradually reshaping the school’s operational system at the foundational level. However, he emphasized that these system upgrades are just the tip of the iceberg, and the deeper shift is happening in the relationship between humans and technology.

For decades, technology in schools was mostly transactional, merely a tool to search and store; but today, AI is becoming more relational, as it collaborates and learns with us and from us. In response, WLSA holds a clear educational philosophy: AI can generate ideas, but only humans can generate meaning; AI can analyze patterns, but only humans can understand purpose; AI can support learning, but only humans can shape character.

To ensure technology serves positive educational outcomes, the school avoided blanket, one-size-fits-all restrictions and instead built a human-centric, ethics-driven AI governance framework. This includes establishing clear guidelines for responsible AI use, ensuring transparency in data handling, and heavily supporting teachers with training and professional development.

Lina Bankert, Managing Director and Partner at Boston Consulting Group, has highlighted that the debate surrounding AI’s transformative impact has been fully settled. The pressing question now, she stresses, lies in how we take meaningful action in response.

To help the educators present feel the changes in the external world more intuitively, Bankert shifted the focus to the business world that students are about to enter. BCG’s data reveals that 90% of global CEOs believe that by 2028, AI will significantly transform what success looks like in their organizations. Furthermore, this transformation has fully escalated into a core strategy personally led by the highest corporate decision-makers.

As AI agents take over more routine or rules-based work, Bankert stressed that deep, “durable human skills”—such as critical thinking, emotional intelligence, and relationship building—are increasingly demonstrating their irreplaceable value and becoming the core competitive advantages in future society. At the same time, education systems must rapidly integrate competencies like responsible AI usage, preventing students from being structurally disadvantaged in the future labor market.

When discussing how education systems can break through these challenges, Bankert drew upon a recent global symposium involving leaders from 55 countries to share a highly practical “10-20-70 principle”: in a successful digital transformation, 10% of the time and energy should go to the algorithm, 20% to the technology, and a full 70% must be focused on people, process, and change management.

As the symposium entered the case study segment, James Patterson, Director of the Kutler Center and Summer Programs, Harvard-Westlake School, began his keynote presentation.

Harvard-Westlake is a traditional, 120-year-old school that for many years was predominantly an Advanced Placement (AP) program. However, within this highly traditional academic environment, the school also needed a “testing ground” to breathe freely and explore interdisciplinary boundaries. In memory of a remarkable late student, Brendan Kutler, who loved independent research and thinking about connections between disciplines, the Kutler Center was established to complement the traditional curriculum.

The leadership and entrepreneurship initiative led by Patterson is exactly the fruit born from this testing ground. Here, teaching kids “entrepreneurship” is not about encouraging them to go up to Silicon Valley and cash out a startup at a young age; its core purpose is to guide students to lead with empathy, understand their community, and solve real-world problems.

Using the formalism of “design thinking” (empathize, define, ideate, prototype, test), Patterson guides students to slow down. When students accustomed to traditional education are eager to jump to a solution, teachers remind them to spend more time understanding the environment and recognizing true opportunities. Whether a problem requires a for-profit solution, a non-for-profit or NGO-style action, or even driving innovation within an existing hundreds-of-years-old organization, the entire focus is on truly identifying the crux of the problem.

So, how does such a practice-oriented interdisciplinary center relate to AI education? Patterson pointed out that it provides an inclusive space for trial and error. Outside the rigorous traditional academic system, the Kutler Center creates an absolutely safe “sandbox” or laboratory for teachers. The school explicitly encourages teachers to boldly try bringing AI into these elective classrooms, telling them unreservedly that if they try something and it fails, that’s totally fine, and the school will support them.

In this burden-free atmosphere, students in the business class use AI to help with note-taking for absent students, and kids in the entrepreneurship class naturally use AI to assist when creating and polishing their pitches.

From this experience, Patterson told the attending educators: if schools want their existing education systems to adopt AI smoothly, the best way is to first create a special space for teachers and students to innovate. In this space, people can freely try new ideas and make mistakes without pressure.

• AI Applications in Teaching and Learning Across Subjects

  Delving into the frontlines of teaching, this session invited guests to share exemplary case studies encompassing student projects, subject-specific teaching resources, and AI-empowered courses. Participants collaboratively explored how AI could be deeply integrated across various disciplines to forge teaching practices that were both technologically advanced and highly collaborative.