“The environment is where we all meet, where we all have a mutual interest; it is the one thing all of us share. It is not only a mirror of ourselves, but a focusing lens…” ~ Lady Bird Johnson

“A system is never the sum of its parts; it’s the product of their interaction.” ~ Russell Ackoff

Over the years, our TechTrends column has explored creativity, education, and emerging technologies. This past year, we’ve examined generative AI through diverse lenses—interviews with thinkers like Ethan Mollick, Ronald Beghetto, and Mairead Pratschke; focus groups with K–12 leaders; and articles offering historical context, theoretical grounding, and practical strategies.

In our latest piece, my colleagues Danah Henriksen, Lauren Woo, and I shift the conversation from “which AI tools should we use?” to a deeper question: How do we create learning environments that can evolve thoughtfully with AI, rather than simply adopting AI tools within existing structures?

We challenge the deterministic narrative that AI will inevitably revolutionize education. Technologies acquire impact only through the cultural, organizational, and systemic contexts in which they’re embedded. Consider this familiar scenario: A school invests heavily in an AI tutoring system, provides training, and launches with enthusiasm. Six months later, it sits unused—too time-consuming to integrate, frustrating for students, lacking ongoing support. This reveals the critical difference between adoption (acquiring technology) and implementation (creating conditions for it to work).

Drawing on systems thinking and our Five Spaces for Design in Education framework, we explore how AI tools are just one artifact. Their impact depends on whether educators reconfigure assessment processes, design collaborative experiences, adapt support systems, and cultivate cultures of experimentation.

The article addresses several critical dimensions of sustainable AI integration. We explore how two schools can adopt identical AI systems with radically different outcomes depending on their organizational resilience—what we call “ecological compatibility.” We discuss the challenge of “cognitive offloading,” arguing that schools may need to deliberately design “cognitive workouts” to preserve the productive difficulty essential for deep learning. The article examines “assessment disruption,” making the case for shifting focus from evaluating products to understanding processes. Finally, we emphasize building adaptive capacity through psychological safety, distributed leadership, and sustained professional learning communities.

AI’s future in education is not predetermined—it will be co-constructed through human choices, organizational priorities, and cultural commitments. The story is still being written. By focusing on building environments that can evolve with AI, we can harness its potential while preserving what makes learning fundamentally human.

Link to article and abstract given below

Henriksen, D., Woo, L. J., & Mishra, P. (2025). Beyond Tools and Training: Building Sustainable Learning Environments that Evolve with AI. TechTrends, 69, 869-875. https://doi.org/10.1007/s11528-025-01134-5

Abstract: This article examines how educational organizations can build sustainable learning environments that evolve with artificial intelligence (AI) and generative AI (GenAI). Drawing on systems thinking, organizational learning, and educational change research, we argue that effective integration requires attention beyond tools and training to the ecological conditions that influence adoption and implementation. We explore how physical and digital learning spaces, organizational culture, professional development, and leadership practices influence whether AI amplifies or undermines learning. Using the Five Spaces for Design in Education framework, we highlight the importance of adaptability, psychological safety, and collaborative networks in navigating uncertainty and preventing deterministic narratives of technological inevitability. We find that the future of AI in education depends not on the technologies themselves but on the human choices and resilient ecosystems that guide their use.