Picture this: It’s September, and instead of being buried in admin tasks, you’re focused on what matters most: your students. As a tech coordinator, you've helped transform your school with AI. Teachers have more time for meaningful feedback, students get personalized learning support, and administrators use real-time insights to make better decisions.

This isn’t a distant future…it’s already happening. AI is streamlining administration, supporting IEPs, and enhancing personalized instruction across subjects. Yet while 60% of school leaders believe AI will transform education, only 25% feel prepared to use it effectively.

This guide gives you a practical roadmap to get your school AI-ready in just 60 days. You’ll move through five focused phases: exploring tools, building buy-in, preparing infrastructure, training staff, and using data to scale with confidence.

A tech coordinator's 60-day blueprint to building an AI-ready school

Transforming your school's approach to AI doesn't require a complete overhaul. As a tech coordinator, you'll apply your educational expertise strategically through five focused phases that align with proven implementation strategies.

Weeks 1-2: Explore and Evaluate
Form your AI task force with diverse representation, conduct a network assessment, and identify tools that solve real challenges.

Weeks 2-3: Build Vision and Stakeholder Buy-in
Craft a concise vision statement connected to district goals and address key concerns about data privacy and academic integrity.

Weeks 3-5: Prepare Infrastructure and Policies
Audit your systems and develop adaptable policies ensuring FERPA and COPPA compliance while allowing room for innovation.

Weeks 5-7: Train Staff and Launch Pilots
Deliver context-specific training that connects AI tools to actual teaching challenges your team faces.

Weeks 7-9: Review Data and Scale
Collect feedback and analyze results on student engagement and teacher efficiency using AI assessment tools, then expand what works.

Your first 30 days' priority actions:

• Assemble a diverse AI task force

• Complete network readiness assessment

• Shortlist 3-5 AI tools for testing

• Schedule stakeholder meetings

• Draft initial AI use policy

• Identify pilot participants

• Plan staff training sessions

AI works best as your teaching partner and in amplifying your expertise while keeping you in control of the learning experience. Success comes from viewing AI as a tool that handles routine tasks so you can focus on what matters most: teaching, connecting, and inspiring students.

Building stakeholder buy-in for AI tech

Building support for AI integration requires creating a shared vision centered on student success. As a tech coordinator, your role is to guide this process and address concerns proactively.

Start by forming a diverse task force including teachers from different subjects and grades, administrators, IT staff, counselors, parents, and, if possible, students. This group becomes your foundation for building trust and creates local expertise and advocacy. Schedule monthly planning meetings, then quarterly check-ins during implementation.

When presenting to stakeholders, focus on three concrete benefits:

• AI can handle routine tasks, giving teachers more time for student connections

• Tools can identify when students need support or enrichment

• AI features like text-to-speech and translation support inclusive learning

By emphasizing these benefits, you demonstrate how AI can assist in reaching every student with AI, aligning with our commitment to personalized support. Highlighting these advantages helps stakeholders envision the future of personalized learning and how AI integration aligns with our educational goals.

Address common concerns directly. For fears about replacing teachers, show how AI amplifies expertise. For data privacy, explain FERPA and COPPA compliance. For academic integrity, districts should be proactive in setting clear expectations early, defining responsible use versus misuse to create a culture of accountability.

Run a vision-setting workshop

Structure your workshop as a collaborative session, not a presentation. Begin by having participants share their biggest challenges, then explore how AI might address these specific pain points.

Use breakout groups for different stakeholders to explore their particular concerns and opportunities. Document all feedback transparently, addressing concerns about issues like algorithmic bias while capturing enthusiasm for potential benefits.

Create a one-page AI vision statement

Your vision statement should answer: What challenges will AI help solve? How will these tools support our values? What does success look like?

Include concrete commitments stakeholders can hold you accountable to, such as "AI will never replace teacher-student relationships" and "Student data privacy will be protected." End with measurable outcomes like "increased time for small-group instruction."

This vision becomes your North Star for every decision. When evaluating tools or programs, return to this document and ask if they align with community commitments. This consistent approach makes decision-making clearer when everyone shares the same destination.

Auditing infrastructure & data readiness: Steps for a tech coordinator

Before deploying AI tools in classrooms, assess your school's current infrastructure. This assessment helps identify what you need to make AI implementation successful for students and teachers. Document your current resources and prioritize areas for improvement to create a clear roadmap forward.

1. Network capabilities assessment

Review your internet infrastructure first. While 74% of districts report having sufficient connectivity, many still lack reliable access for AI tools. Test Wi-Fi strength in all learning spaces including classrooms, lecture halls, libraries, auditoriums, offices, and even common areas where students complete work  and document actual bandwidth during peak usage hours. AI platforms require consistent connectivity for real-time feedback and smooth user experiences.

Implementing AI for performance monitoring can help school administrators optimize network performance and ensure readiness for AI tools.

2. Device readiness review

Inventory available devices for both teachers and students, noting age, operating systems, and browser capabilities. While most AI platforms have modest hardware requirements, older devices may struggle with modern browsers. Consider your student-to-device ratio, as AI tools work best with direct student engagement rather than observation.

Network & hardware checklist

3. Data governance & privacy

Ensure your infrastructure complies with FERPA, COPPA, and other privacy requirements. AI platforms must demonstrate compliance with these frameworks, and your school's data policies should align accordingly. Prioritize platforms with a privacy-first design that minimize the collection of personally identifiable information.

4. Budget planning guidance

Federal funding sources can support necessary infrastructure improvements. Document your needs with cost estimates and map them to available funding sources to make your upgrade path financially feasible.

Selecting the right AI tools & platforms as a tech coordinator

You're facing an overwhelming marketplace of AI tools, each promising classroom transformation. The key to separating value from hype lies in systematic evaluation that prioritizes educational goals over flashy features. Focus your selection process on four key criteria: Usability, Privacy, Impact, and Cost. Usability ensures adoption without extensive training, Privacy confirms FERPA/COPPA compliance, Impact addresses genuine teaching pain points, and Cost considers total implementation resources beyond subscription fees.

Apply this 5-Question Vetting Rubric to any AI solution:

1. Does this solve a specific problem we've identified? Skip solutions looking for problems.

2. Can our teachers use this effectively within their current workflow? Integration should feel natural.

3. How does this handle student data, and does it meet compliance requirements? Districts should leverage existing vetting systems.

4. What evidence exists of this technology's educational impact? Seek research backing claims.

5. What's our total cost of ownership over three years? Include all associated expenses.

By applying these questions, you can effectively assess AI tools for classroom use, ensuring they meet your school's needs. Remember that integration and interoperability with existing systems matter more than flashy features. The best applications enhance current workflows rather than requiring complete overhauls.

Pilot vs. full adoption strategy

When implementing AI tools, you must choose between piloting and full adoption approaches. Pilots allow testing with willing early adopters, gathering real usage data, and refining strategies before scaling. They offer lower financial risk, build teacher confidence through peer advocacy, and allow iterative policy refinement. However, they may create uneven access and slower transformation.

Full rollouts provide faster district-wide benefits, simplified training, greater vendor negotiating power, and unified experiences. Yet they require higher initial commitment, may face more resistance, and create larger impacts if expectations aren't met.

Most successful AI implementations start small, prove value with real educators, and expand thoughtfully. This approach respects that sustainable educational change happens through people, not just technology purchases. By starting with targeted pilots and scaling based on proven results, you maintain control while ensuring solutions truly support your teaching mission.

Developing policies & best-practice guidelines

Creating thoughtful AI guidelines gives teachers confidence to use AI effectively while maintaining student safety and academic integrity. The best frameworks serve as supportive guardrails rather than restrictive roadblocks, evolving alongside the technology they govern.

Your AI guidelines should address four essential areas:

1. Acceptable Use establishes appropriate AI use patterns for your school community. Focus on flexible principles rather than rigid rules to keep your guidelines relevant as AI evolves.

2. Academic Integrity helps distinguish between AI that supports learning versus AI that undermines it. Consider varying standards for different types of assignments and assessments.

3. Data Privacy protects student information while enabling AI benefits. Ensure platforms comply with FERPA, COPPA, and other regulations through clear vetting protocols.

4. Accessibility ensures AI integration supports equitable learning for all students rather than creating barriers.

Digital Promise's AI Literacy Framework provides research-based guidance for developing these guidelines. Treat your framework as a living document with regular review cycles, consider quarterly reviews for rapidly changing areas and annual comprehensive reviews.

Most schools succeed by adapting existing technology policies rather than creating entirely new documents, maintaining consistency while reducing administrative burden.

Drafting your first policy in a day

Begin with your current acceptable use policies, academic integrity guidelines, and privacy procedures. Identify where AI considerations fit within these frameworks, then draft specific additions focused on guiding principles rather than specific tools.

Create simple decision trees to help evaluate AI use against educational goals, then schedule stakeholder feedback sessions. This initial framework serves as your starting point—the real value comes from implementation and refinement based on classroom experience. 

Building staff capacity & AI literacy

The gap between AI's promise and classroom reality starts with teacher preparation. Building meaningful literacy requires a structured, three-tier approach that meets educators where they are: foundational awareness of what these tools can and cannot do; practical application within specific subject areas; and advanced training for teacher leaders who support integration across your school. Successful implementation isn't about turning teachers into technologists, it's about building confidence with tools that streamline routine tasks while maintaining professional judgment.

Building AI literacy for educators requires a structured, three-tier approach that meets educators where they are.

Micro-credential pathways

Create clear progression pathways with micro-credentials that take 2-3 hours to complete, focusing on immediately applicable skills. A "Writing Support" credential might teach brainstorming techniques while maintaining academic integrity, while an "Assessment Helper" could show how to generate aligned quiz questions.

Successful programs often begin with pilot groups who earn initial credentials and then mentor colleagues. Each credential should deliver immediate classroom value: reduced grading time, more personalized feedback, or enhanced lesson planning. Stack these credentials toward larger certifications, ensuring each step provides standalone benefits that justify the time investment.

Peer mentoring & coaching models

Professional learning communities create the ongoing support essential for lasting change. Establish regular collaboration where teachers share successes and troubleshoot challenges together. Pair experienced users with newcomers through structured mentoring relationships. Mentors don't need to be experts, they just need to be one or two steps ahead in implementation.

The most effective approach avoids prioritizing tools over pedagogy. Instead of starting with platform instructions, begin with instructional goals like providing better writing feedback, then introduce technology as one strategy among many. This maintains teacher expertise while enhancing existing strengths.

Ongoing support through regular check-ins and collaborative planning creates sustained growth rather than one-time training events. Teachers need space to experiment, fail safely, and refine their approach with supportive colleagues. This community-based model helps these tools become natural extensions of good teaching rather than additional burdens. 

Pilot, iterate, and scale

Rolling out AI in your school requires thoughtful experimentation that prioritizes teachers and students. A structured pilot approach allows you to test strategies, learn from results, and confidently expand successful initiatives.

Begin with a focused 6-week pilot involving 2-3 willing teachers from different classrooms or a single department. This manageable scope ensures proper support while gathering meaningful insights. Select educators with varying technology comfort levels to understand diverse implementation experiences.

Establish clear success metrics from the start. Research shows that measuring AI's impact on curriculum design helps schools allocate resources effectively and ensures technology serves students. Focus on student performance, teaching efficiency, engagement levels, and personalization opportunities.

Measuring impact on student outcomes

Track both quantitative data (test scores, completion rates) and qualitative insights to evaluate AI's effectiveness. Collect baseline data before your pilot begins, then monitor these indicators throughout implementation.

Surveys from teachers, students, and parents reveal insights about satisfaction and real-world impact that numbers alone miss. Are students more engaged? Do they demonstrate increased confidence? Can teachers provide more individualized support?

Create a simple evaluation framework for your pilot results. If AI tools improve learning outcomes, boost teacher satisfaction, and fit within your resources, you're ready to expand. If results are mixed, adjust your approach before scaling.

Expand gradually and responsively. Successful pilots can extend to similar grade levels or departments, but avoid simultaneous school-wide implementation. Each expansion phase should maintain your initial measurement approach, ensuring quality while allowing process refinement.

Continuous improvement & future-proofing

Your AI journey evolves with your school's needs and the changing educational technology landscape. Establish an annual AI audit process that examines what's truly supporting your students and teachers. Create a straightforward template that tracks current tools, measures their impact on learning and workload, and identifies gaps. Connect with educator networks focused on AI in education to gain practical insights beyond vendor presentations.

Keep your eye on promising developments: real-time formative assessment tools, AI-powered early intervention systems, and automated accessibility features that support diverse learners. Remember that effectiveness depends on thoughtful implementation that maintains human connections.

Schedule quarterly check-ins with your AI task force to review progress and plan next steps. Approach AI as a teaching partner that amplifies what you already do well rather than fundamentally changing how you connect with students.

Troubleshooting & common pitfalls

Even well-planned AI implementations hit roadblocks. Successful schools treat these obstacles as learning opportunities rather than failures.

When the Iowa City Community School District faced teacher concerns about AI tool vetting, they built on existing review processes rather than creating entirely new systems, making adoption feel familiar rather than overwhelming.

Resistance often stems from uncertainty rather than opposition. Address knowledge gaps through clear communication and hands-on training. Remember that while AI supports teaching decisions, success depends on your professional judgment and classroom expertise. Whether that's more communication, additional training, or adjusted timelines, each obstacle reveals what your school community needs most.

Building an AI-ready school: A practical path forward

Creating an AI-ready school in 60 days is possible with a clear, phased approach. From stakeholder buy-in and infrastructure audits to tool selection, policy development, and staff training, each step builds sustainable momentum.

As a tech coordinator, you juggle administrative demands while enabling impactful learning. This guide offers strategies to reduce your workload and empower teachers to personalize instruction and connect with students more deeply.

AI integration isn’t a one-and-done effort… it’s a long-term shift. Schools that succeed treat AI as a teaching partner, not a replacement, ensuring the human side of learning remains central.

Ready to make progress this school year? SchoolAI’s AI Readiness Program is built to support you, from planning to implementation, with educator-designed tools and expert guidance tailored to your school’s real needs.

Key takeaways

• The five-phase roadmap spans exploration and evaluation, stakeholder buy-in, infrastructure preparation, staff training with pilots, and data review for scaling within 60 days.

• Stakeholder buy-in requires forming diverse task forces, addressing concerns about teacher replacement and data privacy, and creating collaborative vision-setting workshops with concrete benefits.

• Infrastructure auditing covers network capabilities, device readiness, data governance compliance with FERPA/COPPA, and budget planning using federal funding sources.

• Tool selection uses a 5-question vetting rubric focusing on specific problem-solving, workflow integration, data compliance, educational impact evidence, and total ownership costs.

• Staff capacity building employs three-tier AI literacy with micro-credentials, peer mentoring models, and structured 6-week pilots measuring student outcomes and teacher efficiency.