Creating custom solutions
For charities that have already explored basic AI tools and want to develop more tailored solutions, this pathway provides a structured approach to creating custom AI applications. Drawing from two years of hands-on experience implementing AI across the charitable sector, we outline practical steps for organisations ready to move beyond off-the-shelf solutions.
Pathway Steps
AI Fundamentals workshop
Conduct an AI Fundamentals workshop to initiate AI integration in UK charities. Cover AI basics, explore opportunities, assess feasibility and impact, and evaluate risks. Involve diverse stakeholders, produce an opportunity framework, guidelines, and governance plan. Regularly review outputs to maintain relevance.
Allocate resources for AI efforts
Allocate resources strategically for AI integration in charities. Establish clear ownership, create sustainable structures, and start with focused pilot projects. Consider both human and technical resource needs, including staff time, training, infrastructure, and budgets. Learn from digital transformation experiences and build flexibility into your approach.
Provide RAI training and education
Develop comprehensive Responsible AI (RAI) training tailored for charity staff. Build on foundational AI knowledge, focus on interactive sessions with charity-specific scenarios, and connect principles to practical actions. Integrate RAI concepts into existing learning pathways and use plain language to make complex ideas accessible.
Develop a common language across disciplines
Develop a common language for AI across disciplines in your charity. Create collaborative glossaries using metaphors and storytelling to bridge knowledge gaps. Balance accessibility with technical precision. Implement practical tips for building shared understanding. Foster ongoing learning to ensure inclusive participation in AI discussions while maintaining technical rigour.
Identify custom AI tool possibilities
Identify opportunities for custom AI tools to address unique organisational challenges. Assess feasibility and impact through process analysis, impact assessment, and data asset evaluation. Focus on high-impact, mission-aligned projects that leverage existing strengths and can be sustained long-term. Consider both quick wins and strategic investments.
Assess and improve data quality and infrastructure
Assess and improve data quality and infrastructure for AI implementation. Categorize existing data, establish AI Champions, and focus on high-impact areas. Begin with small, manageable improvements, document processes, and train staff. Build sustainable practices through regular audits, consistent naming conventions, and clear documentation methods.
Pilot custom AI tools
Begin with small-scale AI pilots, utilizing existing platforms. Prioritize robust evaluation and link AI features to mission impact. Document learnings and be prepared to adjust or halt development based on performance. Share experiences to benefit the wider charity sector.
Upskill teams with custom tools + evaluate performance
Implement custom AI tools in charities by selecting initial users and creating practical documentation. Measure adoption and impact, gather feedback, and focus on outcome-based evaluation. Emphasise continuous improvement and iterative development to ensure AI tools deliver meaningful benefits to the organisation.
Conduct systematic investigations to identify AI risks
Conduct systematic investigations to identify AI risks in charities. Perform day-in-the-life risk audits, mission-scenario stress testing, and stakeholder risk dialogues. Balance thorough assessment with implementation through phased approaches. Schedule regular audits, create edge-case scenario libraries, and establish cross-team discussions. Document findings to build institutional knowledge.
Implement mitigation strategies for identified risks
Implement practical AI safeguards in your charity. Create simple backstops within existing workflows, design for reversibility, and build cumulative protections based on real-world experience. Balance innovation with responsibility by regularly assessing measures, maintaining open communication, and establishing clear documentation and training processes.
Perform adversarial testing and threat modeling
Implement adversarial testing for AI systems in charities. Focus on mission-relevant threats and leverage internal expertise. Establish ongoing testing practices, including a 'friendly adversary' programme. Maintain detailed records to refine safeguards and improve system robustness. Emphasise continuous learning and improvement in AI security.
Establish an AI "Lab" within the organization
Establish an AI Lab within your charity to systematically explore and implement AI solutions. Form a cross-functional team, secure executive sponsorship, and set clear objectives. Maintain connections with operational teams and beneficiaries. Use a structured approach to innovation, focusing on mission-aligned experiments. Plan for gradual implementation and organizational change.
Adapting and evolving custom AI solutions
Adapt and evolve custom AI solutions by integrating existing assessment frameworks with AI-specific metrics. Implement structured experimentation and learn from human-AI workflows. Use data-driven decision-making in regular review cycles. Ensure changes align with charitable objectives and maintain focus on beneficiary outcomes and ethical standards.
Experiment with future-facing AI implementations
Reimagine service delivery using AI's transformative potential in charities. Consider AI as a general-purpose technology to revolutionise operations and create new possibilities. Explore practical examples for complex problem-solving and personalised support. Maintain mission focus while embracing technological advancements across different time horizons.
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