AI hub

It seems like everyone is talking about AI, but there are many misconceptions about what it is and what it can do.  

So let’s first dive into a definition:

“AI is a machine’s ability to perform the cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem solving and even exercising creativity.”

Read more about the definition of AI in: What is AI (Artificial Intelligence)?

1. Research and conversation – Build awareness and understanding across your team by exploring how AI can be used in the sector, through peer discussions, events and resources. These insights help surface ideas, build confidence, and shape a shared approach to how AI can support your work.

2. Develop and review your AI policy – Establish clear boundaries and principles for how AI should be used across your organisation. Define approved tools, data management and where human oversight is required. A well-understood policy builds confidence and consistency across teams.

3. Assess your current use of AI – Take stock of how AI is used in your team and gather any recommendations colleagues might have. Understanding your starting point helps identify gaps and opportunities for improvement.

4. Map out where AI can help you most – Identify the areas of work where AI can add the most value, such as automating routine tasks, drafting content or analysing supporter data. Work as a team to pinpoint opportunities to free up capacity, solve problems and more.

5. Experiment and pilot – Start with small, low-risk projects to test AI tools in practice. Use tools already approved in your policy or propose pilots for new ones, such as video creation tools. Track what works, measure impact and build confidence before rolling out across teams and campaigns to ensure buy-in and uphold best practices.

6. Incorporate into repeatable workflows – Build on what works by embedding successful experiments, prompts, or processes into your workflows. Develop simple templates or checklists to ensure AI use remains consistent and easily repeatable by the team.

7. Upskill and share learning – Encourage team members to keep learning and share what they discover. Sharing knowledge openly builds confidence, sparks new ideas, and helps your charity develop a shared, informed approach to AI.

8. Scale and develop – Once you’ve shown how valuable AI can be in certain areas, look for ways to scale across teams, campaigns, or projects. Measure results, such as time saved or increased output, and apply the lessons learned to continue refining your approach.

1. Use AI as a collaborative tool: Frame AI as a collaborative tool to enhance your work, rather than replace it. Use it to free up time or spark ideas that only your team can bring to life.

2. Be transparent: Clearly communicate with colleagues and audiences when you have used AI in your work. Transparency helps to maintain trust and understanding from your audiences.

3. Keep ethics practical: When addressing ethical concerns, focus on actionable steps for your team. For example, fact-check outputs, use data responsibly, and question bias to ensure AI-generated content aligns with your charity’s values.

4. Remain human-focused: Communications are most effective when they feel human. Keep people and your purpose at the heart, using your creativity and human insight to shape stories and messages that connect.

5. Stay curious: The AI landscape is evolving. Where possible, set aside small amounts of time to stay updated with the latest news and resources and explore new tools that might be useful. Bookmark our AI hub and other resources shared for reference.

We are trialling AI internally as a team with a few vetted software choices, taking a conscientious and purposeful approach. This helps us understand first-hand how charities can use AI while also freeing up our team to work on activities with bigger impact. AI tools will help us in tasks like making first content drafts, transcribing calls, and performing research.   

Hearing from peers and experts in the sector and beyond using AI, we are applying the best practice principles and tips that we’ve loved and learned along the way, including conducting regular reviews. 

Any of our own work supported by AI will now have a disclaimer and will always be checked by our team. We will never use or process any personal data when using AI tools like Large Language Models. The only instances where data may be processed is in event recording or meeting transcribing tools, where we will get express permission. Wherever possible, we will be asking our members to do the same with us. Read more in our data policy.