Select AI tools
While AI offers many promising applications in nonprofit settings, it isn't always clear whether AI is the right tool to create efficiencies or solve specific problems. There're also times when AI isn't needed, for example, when a simpler, non-AI tool can do the job just as effectively.
Understand when AI is the right fit
To support better decision-making, NetHope developed the AI Suitability Toolkit, a resource that helps nonprofits build internal expertise and capacity to evaluate, develop, procure, and use AI responsibly.
This framework equips teams to make informed choices, improve their work, ensure that communities understand the technologies affecting them, and anticipate potential risks or challenges associated with AI. The toolkit guides users through key considerations across five stages:
- Defining the opportunity
- Evaluating data and bias
- Resourcing the solution
- Implementing the solution
- Maintaining and extending the solution
Even if AI adoption is not yet happening at the organizational level, the following are practical ways to evaluate and responsibly integrate AI tools that support your individual role and workflow.
Criteria for selecting AI tools for your role
These key criteria help determine whether an AI tool is suitable for specific tasks and responsibilities. It guides decision-making by highlighting what to look for, what risks to consider, and how to ensure the tool aligns with the work, data, and values.
General guidelines
- Approved tools and usage: Teams must strictly use organization-approved GenAI tools, tools explicitly approved by IT/Security, and tools with clear contractual privacy guarantees. Avoid free or consumer versions unless authorized.
- Preferred tool characteristics: Preference should be given to tools with data isolation (no training on user inputs), enterprise controls, encryption (at rest and in transit), and strong access controls and audit logs.
- Avoid personal accounts: Don't use personal accounts for work data. Using personal accounts risks exposing sensitive organizational data to unintended third parties.
- Use smaller, task-specific models where possible: Smaller, task-specific models are just as smart and accurate as large ones, yet can cut energy use by up to 90%. Currently, users rely on large, general-purpose models for all their needs. Research indicates that using smaller models designed for specific tasks, such as translation or summarization, can significantly reduce energy consumption without sacrificing performance. It's a smarter, more cost-effective, and resource-efficient approach: matching the right model to the right task rather than relying on a single large, all-purpose system for everything.
AI supports role-specific tasks
Nonprofit organizations operate across diverse functions where teams often manage time-intensive, repetitive, or information-heavy tasks. AI helps reduce this burden by supporting administration, analysis, drafting, monitoring, knowledge retrieval, and communication, allowing teams to focus on strategic insights, stakeholder engagement, and mission-driven decision-making.