AI Skills for Social Impact & Engagement Practitioners (L1 - Foundations)

USD 0.00

Next course date: Tuesday, 24 November 2026

This foundational training course for social impact and stakeholder engagement practitioners helps build confidence, AI literacy, and ethical grounding to responsibly and effectively use AI for common social impact functions including research, data analysis (qualitative and quantitative), stakeholder engagement, evaluation, SROI, and report preparation.

Who it’s for

·       Social impact professionals

·       SIA & social safeguard practitioners

·       Community & stakeholder engagement specialists

·       Local government staff

·       Projects or organisations within the infrastructure, energy & development sectors

Core learning topics:

  • Common AI terms & capabilities

  • AI tools and use cases for social impact & stakeholder engagement functions

  • The strengths/limits of LLMs

  • Basics of prompt engineering and agentic AI

  • Risks & ethical issues around AI & social impact

  • Responsible practice elements such as AI data use policies, informed consent, and data sovereignty considerations

  • Social impacts of AI data centres


Next course date: Tuesday, 24 November 2026

This foundational training course for social impact and stakeholder engagement practitioners helps build confidence, AI literacy, and ethical grounding to responsibly and effectively use AI for common social impact functions including research, data analysis (qualitative and quantitative), stakeholder engagement, evaluation, SROI, and report preparation.

Who it’s for

·       Social impact professionals

·       SIA & social safeguard practitioners

·       Community & stakeholder engagement specialists

·       Local government staff

·       Projects or organisations within the infrastructure, energy & development sectors

Core learning topics:

  • Common AI terms & capabilities

  • AI tools and use cases for social impact & stakeholder engagement functions

  • The strengths/limits of LLMs

  • Basics of prompt engineering and agentic AI

  • Risks & ethical issues around AI & social impact

  • Responsible practice elements such as AI data use policies, informed consent, and data sovereignty considerations

  • Social impacts of AI data centres