How to Build an AI Roadmap that Centers Accessibility from Day One

As artificial intelligence (AI) reshapes higher education, institutional leaders need structured approaches to implementation that prioritize accessibility and equity. The four-phase framework for AI adoption—developed by Glass Half Full Consulting and detailed in The Transformative Potential of AI in Student Affairs: Recommendations for Student Affairs Leaders—offers a comprehensive roadmap that balances innovation with inclusion.

Phase 1: Rapid Implementation

The first phase focuses on implementing readily available AI solutions that address current challenges with minimal disruption to existing processes. This approach builds momentum for further adoption while delivering immediate benefits.

During this phase, accessibility considerations should be front and center.

Leaders should:

• Conduct preliminary accessibility evaluations of AI tools before deployment

• Implement "quick win" AI solutions that enhance existing accessibility efforts

• Establish baseline metrics for measuring accessibility impact

• Identify key stakeholders, including accessibility/disability service professionals and students with disabilities, to involve in assessment

For example, an institution might implement an AI writing assistant that includes plain language conversion capabilities, benefiting students with cognitive disabilities while serving the broader student population. This phase is about demonstrating value while building accessibility considerations into the foundation of AI adoption.

Phase 2: Resource and Capacity Building

The second phase focuses on allocating resources and building institutional capacity for more complex AI implementations.

Here, accessibility expertise becomes crucial:

• Invest in AI literacy training for faculty, staff, and students, with explicit focus on accessibility implications

• Develop procurement guidelines that include robust accessibility criteria

• Build technical infrastructure that supports accessible AI implementation

• Cultivate partnerships with accessibility experts and disability advocacy organizations

This phase should include developing comprehensive evaluation rubrics for AI tools that go beyond compliance checklists to include cognitive accessibility, multimodal interactions, and customizability. By embedding these considerations into resource allocation decisions, institutions ensure that accessibility isn't treated as an afterthought.

Phase 3: Scaling Solutions

As successful AI implementations demonstrate value, the third phase focuses on expanding proven solutions across the institution.

This scaling process presents both challenges and opportunities for accessibility:

• Document accessibility successes and lessons learned from early implementations

• Standardize accessibility testing protocols for AI tools prior to wider deployment

• Develop communities of practice around accessible AI implementation

• Establish feedback mechanisms specifically addressing accessibility concerns

During this phase, institutions might expand AI-powered personalized learning systems while ensuring they accommodate diverse cognitive styles and learning preferences. The focus shifts from isolated projects to institutional transformation with accessibility as a core value.

Phase 4: Strategic Transformation

The final phase involves developing an expansive vision for AI-enhanced student affairs that transcends current limitations and aligns with broader institutional goals.

This transformative approach should:

• Reimagine accessibility as a driver of innovation rather than a compliance requirement

• Integrate AI accessibility considerations into institutional strategic plans

• Develop governance structures that center equity and accessibility in AI decision-making

• Position the institution as a leader in accessible AI implementation in higher education

This phase might include developing institution-specific AI models trained on diverse datasets that reflect the full spectrum of human variation, or creating integrated support ecosystems that leverage AI to provide personalized accommodations automatically.

Implementation Challenges and Solutions

Throughout all phases, higher education leaders should anticipate common challenges:

• Resistance to change: Address through comprehensive training and involving skeptics in implementation planning.

• Resource limitations: Start with high-impact, low-cost solutions and document ROI for future investments.

• Technical complexities: Partner with vendors committed to accessibility and build internal expertise gradually.

• Ethical concerns: Develop clear policies on AI use that address privacy, bias, and accessibility.

• Accessibility gaps: Establish regular testing protocols involving users with diverse abilities.

The inside Higher Ed Student Voice Survey reveals the urgency of strategic implementation: only 16% of students report that their institutions have published clear AI policies. These gaps create particular challenges for vulnerable populations, including students with disabilities who may benefit most from appropriate AI use but face barriers to adoption.

By following this four-phase framework with accessibility as a guiding principle, higher education leaders can harness AI's transformative potential while ensuring these powerful technologies advance rather than hinder educational equity.

The path forward requires both vision and careful planning, but the potential rewards—more personalized, accessible, and effective educational experiences—make this effort essential for forward-thinking institutions.

Ready to move from promise to practice in your AI strategy?

Dr. Claire Brady offers “From Promise to Practice: AI’s Role in Higher Ed Accessibility,” that equips higher education leaders with the tools to design, implement, and evaluate AI technologies through an equity and accessibility lens. Whether you're a disability services professional, a senior leader exploring AI adoption, or a faculty champion for inclusive innovation—this training will challenge your thinking and sharpen your approach. Explore this session and other high-impact AI trainings at www.drclairebrady.com, or reach out directly to schedule a conversation.