Before you dive into identifying AI opportunities or selecting tools, it’s vital to establish a dedicated AI Core Team or AI Committee. This team will be the driving force behind your AI initiatives, ensuring they are well-planned, effectively implemented, and aligned with your organization’s goals.
Building the right team is essential. It shouldn’t be solely an IT function. Aim for a diverse group with a mix of skills and perspectives.
Every organization is different, but you might want to include this kind of profiles:
It can be a formal committee with regular meetings or a more informal working group that meets only when it’s needed.
You should define the roles and responsibilities of the AI Team, so everyone understands their contribution and prevents overlap or gaps.
You might also want to design an “AI Officer” that is in charge of most day-to-day tasks related with AI, while the AI Team/Committee only takes care of the big decisions.
Here are the most common responsibilities related with AI:
We have a created a AI Template that might help you follow the steps for this roadmap. For this step, check the “TEAM” tab.
With your AI Team assembled, it’s time to brainstorm and identify specific areas where AI can make a real difference in your organization. The goal is to find AI applications that are both impactful (they significantly advance your mission) and feasible (you have the resources and capacity to implement them).
There are hundreds of ways to use AI for your organization. We’ve compiled +40 common AI use cases for nonprofits. You should review that database (and maybe ask ChatGPT for specific ideas based on your priorities) and make a list of all the relevant ideas for your nonprofit.
Once you have a big list of potential AI use cases, you need a way to prioritize them. You can evaluate each opportunity based on the following criteria:
You can put all the ideas on a spreadsheet and give them a score for each criteria, so you can quickly identify the top priorities for your first AI pilot projects. Hopefully you will find some high-impact, low-cost and low-risk ideas.
We have a created a AI Template that might help you follow the steps for this roadmap. For this step, check the “OPPORTUNITIES” tab.
Once you’ve identified high-priority AI opportunities, the next step is to choose the right tools and technologies to bring those ideas to life. This can be a difficult task, as the AI landscape is vast (thousands of different tools and providers) and constantly evolving. This section provides a practical guide to navigating this process.
You basically have 3 options:
Building your own tools and models gives you more flexibility and control, but it requires much more resources and it’s not guaranteed that you will get better results (the training of AI models could go wrong, you could open unexpected security risks, your custom tool could get obsolete very quickly if the commercial providers keep improving their tools and models… ).
For most nonprofits, the first option (starting with no-code platforms) is the recommended approach. It allows you to test AI solutions quickly, affordably, and with minimal technical risk. You can always consider custom development later if your needs outgrow the capabilities of these platforms.
Does the tool actually do everything you need it to do?
This includes if the AI tool have the features you need (e.g. Research websites or documents, image creation, big context window, structured outputs, team/access management, API, etc.) and also if the AI model is intelligent enough for your tasks.
Is the tool user-friendly for your staff? Will they be able to use it effectively with minimal training?
Consider the technical skills of your team. You also have to judge if it will be better for your organization to use a multi-purpose AI tool for most tasks (e.g. ChatGPT) or many specific AI tools that are great for certain tasks (e.g. AdCreative for ads, Ideogram for image creation, Cursor for code generation/optimization, Otter for meetings, etc.)
What is the total cost of ownership?
The main cost could be fixed-price subscriptions or variable costs (e.g. API usage). But you should also add the cost of training, support, maintenance, potential integration costs, etc. Consider free or open-source options where available.
Does the tool integrate with your existing systems (e.g. CRM, email marketing platform, database…) or at least with connector platforms (e.g. Zapier, Make, n8n…)?
If your systems are not integrated, your staff will spend more time on low-value repetitive tasks (e.g. copying or uploading data manually) and it will increase the risk of working with old or incomplete data.
Ensure that the tool meets your data security and privacy requirements, including compliance with relevant regulations (GDPR, CCPA, HIPAA, etc.). Look for features like encryption, access controls, and data anonymization.
Choose a reputable vendor with a proven track record of providing reliable support. Read reviews, check their customer satisfaction ratings, and ask for references. Also request demos or trials to test the tools before buying.
You might want to create a checklist with all the general requirements that all your AI tools have to comply with (regulations, integrations, etc.) and maybe add specific requirements for certain goals.
You are a AI consultant for nonprofit organizations. Create a comprehensive checklist for a nonprofit organization to evaluate potential AI tools. The checklist should help them assess whether a tool aligns with their specific needs and requirements. Take into account Our Context and the specific Requirements mentioned below.
# Key areas #
The checklist should include at least the following sections:
1. Functionality
2. Ease of use, cost
3. Integrations
4. Data security and privacy
5. Vendor reputation and support
Feel free to add any other relevant criteria or sections you think would be helpful for a nonprofit in this decision-making process.
# Our context #
> Our mission:
> Our challenges:
> Our goals:
> Software that we use:
> People and skills that we have:
> Available budget for AI projects:
> Legal and Ethical considerations:
# Requirements #
1. Include specific questions or criteria within each area that a nonprofit should consider.
2. The checklist should be in a format that allows for a 'Yes/No' or a rating scale (e.g., 1-5) response for each item.
1. Functionality
2. Ease of Use
3. Cost & Total Ownership
4. Integrations
5. Data Security & Privacy
6. Vendor Reputation & Support
7. Mission Alignment & Impact
8. Additional Considerations
We have a created a AI Template that might help you follow the steps for this roadmap. For this step, check the “TEAM” tab.
You’ve identified promising AI opportunities and selected the right tools. Now it’s time to put your plans into action. The key to successful AI implementation, especially for nonprofits with limited resources, is to start small, learn fast, and iterate. This is where pilot projects come in.
Pilot projects allow you to:
Choose your first pilot project carefully. It should be a good representative of the type of AI application you envision using more broadly, but it should also be manageable in scope. Here are some criteria to consider:
A pilot project should be an iterative process:
We have a created a AI Template that might help you follow the steps for this roadmap. For this step, check the “TEAM” tab.
As your nonprofit begins to implement AI, it’s essential to establish clear guidelines and principles for its responsible and ethical use. This is where an AI policy comes in.
Your AI policy should be tailored to your organization’s specific context, mission, and the types of AI applications you are using. However, most AI policies should include the following key elements:
We have a created a AI Policy template. It’s designed to be quite easy to understand and apply. It’s quite brief and doesn’t use language that is too formal or difficult. Because a document like this is useless if many people in your organization ignore it or doesn’t know how to apply it easily.
You can use it as the base for your own AI Policy document (maybe adapting a few things to your organization) or just as inspiration to create your Policy from scratch or based or other documents.
Instead of creating a completely standalone AI policy, you may want to add AI-specific provisions into your existing policies (Data Privacy, IT, Ethics or other specific policies).
If you have time, it’s great to check other AI policies and guidelines to get ideas for your own document. We mention here a few good ones:
The AI Library is a living document (or set of documents) that evolves over time as your organization gains experience with AI. It’s a place to store best practices, lessons learned and helpful resources. It promotes knowledge-sharing, consistency, efficiency, and continuous learning.
Your AI Library should probably include the following components:
Choose a platform for your AI Library that is easily accessible and user-friendly for your team. So it’s probably better to use the same tool that you’re already using for knowledge sharing. Some options include:
It’s important that the Library can be easily updated, so it remains relevant and useful. You can let any user edit it (and keep track of changes) or maybe only give edit permissions to your AI Officer or AI Core Team.
One of the most powerful elements of the AI Library is sharing great prompts. But to create great prompts, you should know first the basics of prompt engineering. Check our guide “Prompt Engineering for Nonprofits“. If you have time, check also other articles about this, like “Working with AI: Two paths to prompting” and “How to Write Great Generative AI Prompts for Nonprofit Workflows“
As mentioned above, we have a created a AI Template that might help you follow the steps for this roadmap.
The link above will invite you to copy the file (it’s created with Google Sheets, so you will need a Google account). After that, you will own the new file. You will be able to edit as you wish and nobody else will be able to access it until you configure your sharing preferences.
This template has “fake examples” (not coming from a real organization), but they might give you some useful ideas to implement this on your own organization.