AI By Design: Robust Infrastructure
Why it Matters: Equitable AI implementation depends on more than just access to tools; it requires a robust, reliable, and scalable infrastructure that ensures every student, regardless of location or background, can benefit from AI-enhanced learning. This includes access to high-quality devices, consistent high-speed internet, and cloud-based systems capable of supporting AI applications. Schools must also consider the long-term sustainability of their infrastructure, including regular upgrades, cybersecurity protections, and ongoing technical support. Without this foundation, AI tools may only widen existing gaps rather than close them, making infrastructure not just a technical issue, but a matter of educational equity and opportunity.
These guiding questions are designed to spark meaningful dialogue and reflection across your leadership team. Use them during planning meetings, workshops, or cross-departmental discussions to ensure your AI implementation strategy is equitable, transparent, and aligned with district goals.
By working through the questions collaboratively, teams can uncover blind spots, surface diverse perspectives, and build a shared vision for how AI can support teaching, learning, and operations, with students at the center of every decision.
- Does every student have access to the devices and bandwidth required for AI tools?
- Are infrastructure systems designed to scale and support evolving technologies?
- How do we ensure equitable access to resources in underserved areas?
- What redundancies are in place to maintain access if AI systems fail or experience downtime?
- Are student and staff devices optimized to run AI applications efficiently and equitably?
- Conduct an Access Audit: Assess and address infrastructure gaps to assess AI-readiness and reliability.
- Plan for Scalability: Develop infrastructure that can support increased AI adoption over time.
- Plan for Sustainability for AI Investments: Ensure AI adoption aligns with long-term district technology strategies.
- Prioritize Underserved Areas: Ensure resources and infrastructure investments focus on closing digital divides.
- Secure Funding: Leverage federal and state grants to support infrastructure development.
- Plan for environmentally sustainable AI infrastructure (e.g., energy-efficient servers, cloud storage, etc.) due to AI’s high energy usage levels.
- Establish a “customer-service mindset” as a department to quickly respond to AI-related classroom issues that arise.
