In his recent webinar, Beyond GDPR AI, Data Requests, and Key Legal Updates for Charities 2025,Mark Finan explained that Artificial Intelligence (AI) is reshaping how charities operate, from fundraising and donor engagement to program delivery and impact measurement. While AI offers powerful tools for efficiency and innovation, it also brings legal, ethical, and practical challenges—particularly around data protection, transparency, and stakeholder trust.

How AI is Used in Charities

Charities are leveraging AI in multiple ways:

• Fundraising and Donor Engagement: Automated systems send prompt acknowledgements to donors, personalise appeals, and segment donor bases for targeted campaigns. For example, the American Cancer Society increased donations by 400% through AI-driven donor segmentation.
• Program Delivery and Impact Measurement: Machine learning models can assess program outcomes in real time, providing instant insights for institutional funders. Predictive AI models have been used to reduce dropout rates in healthcare programs by sending reminders and personalised follow-ups.
• Service Innovation: Chatbots and virtual assistants can answer donor or beneficiary queries instantly, extending engagement without increasing staff workload.
• Fundraising Optimisation: AI can predict future trends, identify underrepresented donor groups, and inform diversification strategies.

Implementation Challenges

Despite the potential benefits, charities face key barriers when adopting AI:

1. Resource Constraints: Limited budgets and technical expertise can hinder AI adoption.
2. Data Quality: AI output is only as good as its input (“garbage in, garbage out”). Poor or biased data risks misleading results.
3. Integration with Existing Systems: Aligning AI tools with current processes requires careful planning and training.
4. Staff Skepticism: Employees may fear job losses or distrust AI systems, making change management essential.
5. Ethical Concerns: Risks include algorithmic bias, exclusion of vulnerable groups, and privacy breaches.

Practical Steps for Responsible AI Adoption

Mark Finan outlined several best practices for introducing AI in a charity setting:

• Assess Organisational Needs and Readiness: Match AI tools to the charity’s size, data volume, and goals. Start with low-risk pilot projects.
• Invest in Staff Training: Equip staff and volunteers with AI literacy and ethical awareness.
• Collaborate with Experts: Work with trusted tech partners and sector specialists.
• Document Processes: Keep detailed records of AI implementation, from risk assessments to decision-making processes.
• Monitor and Evaluate: Regularly review AI outputs for accuracy, bias, and compliance.
• Create an AI Policy: Define acceptable use, oversight measures, and GDPR safeguards.

Transparency and Stakeholder Communication

Openness is key to maintaining trust:

• Inform Donors, Beneficiaries, and Staff: Clearly explain if and how AI is being used.
• Address Job Security Concerns: Emphasise upskilling opportunities and potential role enrichment.
• Comply with GDPR: Ensure data subjects have consented to their data being processed by AI, especially when dealing with special category data.
• Manage Third-Party Risks: Avoid feeding personal data into uncontrolled AI platforms (e.g., public versions of ChatGPT) without robust data processing agreements.

AI offers Irish charities a chance to enhance efficiency, deepen donor relationships, and improve service outcomes. However, adoption must be strategic, ethical, and transparent. By starting small, investing in training, and maintaining human oversight, charities can harness AI’s potential while safeguarding stakeholder trust and complying with legal obligations.

For the full session, please click here. This comprehensive session covers the following three critical topics for Irish charities:

• The use of Artificial Intelligence (AI)
• Data Subject Access Requests (DSARs)
• Recent legal developments

The contents of this article are meant as a guide only and are not a substitute for professional advice. The authors accept no responsibility for any action taken, or refrained from, as a result of the material contained in this document. Specific advice should be obtained before acting or refraining from acting, in connection with the matters dealt with in this article.