Checklist: AI tool evaluation & setupCopy

📋 Needs Assessment and Preparation

⬜️ 1. Define clear goals and success metrics before starting
Set measurable targets like hours saved per week, response time improvements, or donor engagement increases. Document baseline measurements to compare against later.

⬜️ 2. Set a complete budget (including hidden costs)
Calculate monthly subscriptions, training time, potential integration costs, data preparation work, etc.

⬜️ 3. Identify who will champion the AI implementation
Designate one staff member as the AI lead with 5-10 hours weekly for initial setup.

⬜️ 4. Map all your existing software and data sources
List your CRM, email platform, project management tools, and where your data lives. Note which systems have APIs or integration options for smoother AI connections.

🔍 Tool Evaluation and Selection

⬜️ 5. Research and compare at least 3 different AI tools for each use case
Create a comparison spreadsheet with features, pricing, integration options and other relevant elements (including the ones mentioned below)

⬜️ 6. Test each tool with your actual data and workflows
Use free trials to process real tasks (with sensitive data removed). Register their processing time, accuracy, and ease of use for each scenario. Also check for bias, hallucinations and other problematic outputs. 

⬜️ 7. Test accessibility and inclusivity features
Verify the tool is accessible for users with disabilities (WCAG compliance), supports multiple languages if needed, and can handle diverse data inputs reflecting your community.

⬜️ 8. Review support, training, and implementation resources
Evaluate available training materials, response times for support tickets, and whether they offer nonprofit-specific resources. Ask about onboarding timelines and dedicated account management.

⬜️ 9. Evaluate technical compatibility and integration capabilities
Confirm the tool works with your existing systems (CRM, email, databases, etc.). Request documentation on available APIs, webhooks, or native integrations. Test data import/export formats.

⬜️ 10. Verify data privacy, security, and compliance standards
Request compliance certificates for GDPR, CCPA, HIPAA, or other relevant regulations. Review data retention policies, encryption methods, and whether your data will be used to train their models. Get written confirmation of data ownership rights.

⬜️ 11. Assess mission alignment and ethical considerations
Verify the tool aligns with your values. Ask vendors about their AI ethics policies, bias mitigation strategies, and whether they have experience with nonprofits and vulnerable populations.

⬜️ 12. Evaluate vendor transparency and AI explainability
Ask how their AI makes decisions, what data it was trained on, and whether they offer explainable AI features. Avoid “black box” systems for critical decisions affecting beneficiaries or donors.

⬜️ 13. Assess vendor stability and long-term viability
Research the company’s funding history, years in operation, customer base size, data breaches and product roadmap. Request references from 2-3 nonprofit clients and check online reviews.

⬜️ 14. Check for nonprofit-specific pricing, grants, and discounts
Many vendors offer nonprofit discounts or free tiers. Check TechSoup, request nonprofit pricing directly, and ask about volume discounts or grant programs.

⬜️ 15. Calculate total cost of ownership
Beyond subscription fees, factor in training costs, integration expenses, ongoing support needs, and potential scaling costs as usage grows. Compare against the expected ROI and time savings.

⚙️ Initial Setup and Configuration

⬜️ 16. Create a dedicated organizational account
Use your organization’s domain email, not personal accounts. Set up shared password management for continuity when staff changes occur.

⬜️ 17. Enable maximum security settings
Turn on two-factor authentication, set strong passwords, and configure the strictest privacy settings available. Document all security configurations.

⬜️ 18. Configure appropriate user permissions
Start with minimal access and expand as needed. Create admin, editor, and viewer roles based on actual job functions, not seniority.

⬜️ 19. Customize the AI for your nonprofit’s voice
Upload 10-20 examples of your best content to train the AI on your tone. Include samples from different departments for comprehensive training.

⬜️ 20. Create and save template prompts
Write 5-10 standard prompts for common tasks. Store in a shared library.

📚 Training

⬜️ 21. Create one-page quick-start guides
Include screenshots, login info, and step-by-step instructions for the 3-5 most common tasks. Keep each guide under 10 steps and test with a new user.

⬜️ 22. Schedule hands-on training sessions
Plan 60-minute sessions using actual work examples, not generic demos. Include ethics training alongside technical skills.

⬜️ 23. Establish a feedback collection system
Set up channels for staff, beneficiaries, and stakeholders to report concerns or suggestions about AI use. Promise response within 48 hours.

🚀 Advanced Optimizations (Optional)

⬜️ 24. Integrate AI tools with your CRM through automation platforms
Create automated workflows using Zapier, Make, or native integrations. This can save 5-10 hours weekly for larger organizations.

⬜️ 25. Fine-tune AI models with your organization’s content
Upload grant proposals, impact reports, and successful communications to improve output relevance. This can increase accuracy by 30-40%.

⬜️ 26. Implement third-party audits for bias and security
Hire external experts annually to review your AI systems for algorithmic bias, security vulnerabilities, and ethical concerns.

⬜️ 27. Adopt explainable AI tools for transparency
For decisions affecting beneficiaries, use AI that can explain its reasoning. This is important for maintaining trust and accountability.

⬜️ 28. Create an innovation pipeline for emerging AI
Allocate quarterly time to explore new AI capabilities.