Problem
A national healthcare non-profit that provides health information to priority populations recognized that AI was beginning to reshape how healthcare, advocacy, and information access operate. With several high-traffic websites and a mission centered on trust and equity, the organization knew it needed to adapt—but lacked a clear, responsible strategy to do so.
Key challenges included:
- Manual workflows limiting operational efficiency across grant writing, donor engagement, and policy tracking.
- Limited visibility into data needed for strategic decision-making and measuring funding effectiveness.
- Difficulty evaluating AI tools, separating signal from noise, and understanding how AI influences broader technology and ecosystem decisions.
- Growing pressure to ensure the accuracy of AI-generated health content, especially as their communities increasingly rely on chatbots and AI search.
- Interest in launching earned revenue streams with AI components, but lacking architectural guidance and clarity on implementation challenges.
- A need to maintain leadership in health policy and AI governance, despite limited internal resources.
The organization sought a thoughtful, phased roadmap to integrate AI in a way that would enhance impact, safeguard equity, and align with its long-term mission.
Action
To support responsible and sustainable AI adoption, we partnered with the organization to design a strategic roadmap grounded in real-world constraints, mission alignment, and long-term impact.
Our approach included:
- Stakeholder Discovery: Conducted in-depth interviews with leadership across development, programs, marketing, and technology to understand concerns, priorities, and current perceptions around AI.
- Baseline Assessment: Evaluated existing tools, data infrastructure, technical capabilities, and governance readiness to identify gaps and opportunities for AI enablement.
- Roadmap Development: Created a phased AI strategy focused on near-term pilots, onboarding plans for proven tooling, and long-term transformation goals—while aligning with funding and staffing limitations.
- Risk & Adoption Planning: Addressed internal concerns around AI-driven change by designing low-risk, high-impact entry points and clearly defined staff onboarding and training processes.
- Governance & Feasibility Constraints: All recommendations considered the organization’s limited tech budget, ethical obligations, and need for secure, privacy-conscious AI use.
The roadmap prioritizing stability, clarity, and trust over hype while still ensuring the organization remained relevant in an AI-powered future.
Results
We delivered a comprehensive AI strategy and roadmap tailored to the organization’s mission, resource constraints, and risk posture. Our work focused on identifying high-impact use cases, reducing complexity, and enabling responsible adoption across operations, advocacy, and digital engagement.
Key outcomes included:
- Strategic AI Roadmap: A phased plan for AI adoption across three stages—foundations, scaling, and long-term growth—aligned with budget realities and ethical considerations.
- Executive Alignment & Board Preparation: Partnered directly with the CTO to align leadership on priorities, prepare board-level materials, and build internal buy-in.
- Tactical Rollout Plan: Developed a responsible implementation path that emphasized early wins, minimized organizational burden, and addressed staff concerns about AI adoption.
- Financial Sustainability Enablement: Outlined AI use cases and implementation plans to enhance grant writing, improve donor targeting, and support new revenue streams through AI-augmented products.
- Advocacy & Engagement Strategy: Defined options and technical approaches to leverage AI for misinformation monitoring, audience targeting, and digital content optimization.
- Operational Integration: Embedded AI into core workflows with governance, training, and workforce augmentation plans to boost productivity without overextending the team.
Pending final discussions with the board, the organization is now equipped to move into the implementation phase with confidence—armed with a clear roadmap, robust frameworks for decision-making in a rapidly evolving AI landscape, and a practical plan for developing and deploying the most impactful use cases.
