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A free guide to developing an organizational AI policy, with guidance on responsible AI use, data protection, human oversight, tool approval, and three templates you can adapt for your organization.

Learn how to use AI as a practical Excel assistant for your finance work. Get help writing and troubleshooting formulas, analyzing financial data, working with PivotTables and charts, and checking AI-generated outputs before you rely on them.

A practical guide to using AI for variance analysis, reforecasting, and clear financial reporting.

AI is influencing decisions across nonprofits, often without clear policies or oversight in place. This white paper helps leaders and boards understand the risks, ask better questions, and put practical safeguards around how AI is used.

AI is changing how development programs are delivered, but without the right skills, it can create risk as easily as value.
This guide outlines five practical competencies project managers need to use AI responsibly, effectively, and at scale.

A practical guide to designing AI pilots that deliver measurable outcomes, with clear metrics, ownership, and pathways to scale or stop.

AI is entering everyday project work—but most teams lack clear guardrails.
This guide outlines five simple practices to use AI safely while protecting data, quality, and trust.

This resource outlines practical ways project teams can integrate AI into planning, reporting, and learning cycles to improve delivery outcomes.

This resource provides a practical four-tier taxonomy to help project managers match AI capabilities to real delivery needs, from drafting and summarization to agentic workflows. Learn four critical questions to ask before adopting any tool, avoid common mistakes, and run a simple diagnostic to assess your current AI use.

Many teams are trying AI, but few are seeing positive results. This resource shows what changed recently and five simple steps project managers can use to turn small trials into everyday, reliable delivery.