What We Learned: Exploring the Role of Educators in the Age of AI

This post is written in collaboration with NewSchools Venture Fund and FullScale.

A Moment of Inflection

AI has opened unprecedented possibilities for teaching and learning, but at a pace that exceeds the systems, supports, and assumptions surrounding today’s classrooms. Leaders across the field are already navigating the impact of AI on staffing models, instructional practice, professional development, and resource procurement—often without the evidence, clarity, or guardrails needed to guide decisions.

For teachers and students, AI expands what’s possible while introducing new layers of uncertainty and complexity. This raises a defining question for the moment: How can we reimagine the role of educators so AI strengthens—not replaces—the human work at the center of teaching and learning?

In October 2025, NewSchools Venture Fund and Overdeck Family Foundation brought together grantees to address this question. Planned and facilitated in partnership with FullScale, the event assembled more than 40 organizations, representing tools, models, and educator supports. While participants arrived at varying stages of AI exploration, each shared a belief that improving learning for all students, especially those furthest from opportunity, will require reimagining teaching itself to be more effective, sustainable, and joyful.

This brief synthesizes themes that surfaced across discussions, including insights, tensions, and opportunities that may guide funders and field builders interested in shaping the conditions for a more equitable and sustainable future of teaching and learning in the age of AI.

The State of the Field

A pre-convening landscape scan and participant interviews revealed several areas of alignment around both the promise and risks of AI:

• AI adoption in K-12 education remains incremental, even as other sectors experience rapid transformation. AI’s impact in K-12 education depends on the design and implementation choices we make now. These decisions will determine who benefits, and who may be left out and underserved.
• While tools are advancing quickly, outdated mental models and narratives about teachers as dispensers of knowledge continue to shape decisions and limit the field’s imagination about future educator roles.
• Evidence is still emerging, and the field lacks shared language, frameworks, and learning structures to help guide responsible experimentation. Releasing these outdated narratives and embracing shared experimentation will be essential moves for building the coherence the field currently lacks.

Provocations that Framed the Convening

The convening opened with a series of bold provocations designed to surface underlying assumptions and spark debate. Participants wrestled with recurring questions such as:

• What should the role of educators become in an AI-enabled future?
• Are we using AI to deepen learning or simply to make existing systems more efficient?
• How should curriculum, differentiation, and assessment evolve?
• Who decides what responsible AI use looks like, and whose needs are centered?
• How do we ensure AI strengthens human relationships and the student experience rather than undermining them?

These questions did not always generate consensus, but they help illuminate the moment we are in and the choices the field faces.

What We Learned: Insights From the Convening

Across two days of dialogue, several themes surfaced repeatedly.

1. AI should augment, not automate, the human work of teaching. Participants expressed urgency about moving beyond efficiency-driven use cases. AI should expand educator capacity and enable deeper learning, not automate tasks in ways that narrow instructional opportunities, erode relationships, or limit student opportunities for “productive struggle.” As one participant noted, “Looms automate work that humans can do; cranes do work that humans can’t do on their own. We should be building cranes.”
2. Educator co-design is essential for responsible AI-enabled models. Participants emphasized that educators should be designers, not end users, of AI tools and school models. When teachers lead, AI strengthens the relational and judgment-driven work at the core of teaching. Without co-design, tools risk solving the wrong problems or arriving too late for classroom realities.
3. Teaching roles, staffing models, and use of time must evolve. Discussions explored how team-based staffing models, redesigned classrooms with multiple adults, and new uses of instructional time could create space for deeper relationships, targeted instruction, and more sustainable workloads, with AI playing a supporting role.
4. Inclusive design must guide decisions from the start. Participants raised concerns about AI widening existing disparities in access, quality, and experience. Responsible AI requires centering the needs and experiences of students furthest from opportunity and ensuring innovations do not reinforce these inequities.
5. The field would benefit from greater coherence to avoid fragmentation. Participants identified a need for shared frameworks, common guardrails, research partnerships, and learning ecosystems. Without these, experimentation may remain fragmented, and promising insights may not translate into collective progress.

Tensions the Field Must Navigate

Participants surfaced several tensions that require continued exploration within the field:

• Efficiency vs. transformation: AI can make tasks easier, but ease does not equal deeper learning or stronger relationships.
• Rapid innovation vs. responsible guardrails: Tools evolve faster than research, raising questions about judgment, ethics, and oversight.
• Personalization vs. coherence: AI’s capabilities challenge assumptions about curriculum, shared learning experiences, and what should be consistent across classrooms.
• Expanded educator capacity vs. educator sustainability: AI may shift the distribution of work, but without redesigned roles and supports, longstanding challenges such as burnout may persist.

These tensions are not obstacles. They illuminate areas where further collective learning and clarity are needed.

A Call to Action for Field Builders

Insights from the convening point to a clear mandate that no single organization, pilot, or innovation, no matter how promising, can meaningfully shift educators’ roles or redesign how students learn. Progress requires coordinated, coalition-level action across the field.

Funders, policymakers, and regional intermediaries can accelerate this work in four ways:

• Invest in shared learning for effective AI adoption. Prioritize elements such as cross-sector collaboratives, shared research frameworks, ethical guardrails, datasets, and evidence standards that enable organizations to learn from one another, reduce duplication, and build toward a coherent evidence base rather than isolated signals.
• Resource school- and system-level redesign that simultaneously reimagines educator roles and student experience. Support new school models, not just isolated pilots, that rethink roles, staffing, differentiation, and professional learning, so that AI-enabled designs translate into more meaningful student experiences, more joyful and sustainable educator roles, and more excellent and equitable student outcomes.
• Center educator expertise and student experience in designing and implementing AI-enabled models. Invest in design studios among technologists, educators, and students, and professional learning that strengthens teachers’ judgment and instructional decision-making so that AI deepens student learning and doesn’t rob them of opportunities for productive struggle.
• Strengthen coordination and storytelling across the field. Align convenings, communication, and funding signals to amplify exemplars backed by evidence. Strengthen sector-wide storytelling to build a cohesive vision for how AI can support human-centered teaching and student learning.

Together, these actions can help the field move from isolated pilots to a coordinated, human-centered redesign of educator roles and student learning experiences.

From Experimentation to Collective Design

The convening made clear that a new era of teaching is already emerging, shaped by technological advances and educator creativity. But the shape of that transformation remains open. The field must act with intention to ensure innovation strengthens, rather than replaces, the human core of teaching. The greatest risk may lie in drifting towards dehumanizing uses of AI through inertia or fragmented effort.

By coordinating investments in shared learning, new models, educator and student co-design, and storytelling, field builders can help shape a coherent, equitable vision for teaching in the age of AI. The window to set this direction is open—but it will not stay open indefinitely.