Abstract: As AI adoption accelerates across industries, workplace competencies are rapidly evolving—with direct implications for what, how and where students learn. The teacher’s role is evolving, and educators increasingly leverage AI to design and monitor meaningful learning experiences. While research confirms effective learning environments significantly impact K-12 student outcomes, schools are asking: Do we need to adapt the design of learning spaces to harness AI’s potential while preserving irreplaceable human elements of teaching and learning? Insights from literature, educators, technology professionals, students, and a space audit were synthesized to understand whether and how K-12 design should adapt to support evolving classroom dynamics, teacher mobility, and student peer interaction. Findings revealed that emerging pedagogies and learning needs demand adaptive, interconnected learning environments—not simply adding technology to traditional classrooms. AI-enabled environments support seamless transitions between analog and digital work while prioritizing human connection over digital dependency. The presenters will share a practical design framework where space, pedagogy, and educational technologies are considered simultaneously to best support inquiry, creation, critique, and reflection in integrated learning ecosystems.

Learning Objectives:

1. Describe how educators are using AI in K-12 settings to develop industry-aligned student competencies.
2. Identify adaptive spatial typologies and design strategies that can help K-12 learning environments support emerging AI learning practices while maintaining essential human social connections.
3. Assess current learning environments for readiness to support AI-enabled pedagogy using the study’s research-based framework and design principles.
4. Facilitate a human-centered planning process for designing future-focused learning spaces that consider the intersection of space design, pedagogical practice, and educational technologies like AI tools.