The Liability Gap
Who is responsible when AI gets it wrong, and how boards build a defensible chain of accountability.
Board briefs, model policies, templates and assessments. Register once, free, to download any document.
Who is responsible when AI gets it wrong, and how boards build a defensible chain of accountability.
What boards owe beneficiaries when AI is used in programs, eligibility and case management.
What funders are asking about AI use, and why transparent disclosure is an advantage.
How ungoverned AI can embed bias in programs, hiring and communications, and why that is a mission issue.
Who owns what your AI learns, and the contract protections to require.
Why consequential decisions about people require human review, and what that standard means in practice.
The governance obligations employers hold when AI tools collect data on staff.
The hidden AI risks in vendor contracts and what to ask before renewing.
The AI legislation heading toward nonprofits, and why proactive governance is the best defense.
Whether your D&O and liability coverage actually extends to AI-related harms.
The affirmative case that governance is the precondition for sustainable AI adoption.
Donor privacy, authentic communications and the ethics of algorithmic donor targeting.
The heightened duty of care when AI interacts with or makes decisions about young people.
Keeping AI standards consistent across affiliates, chapters and sites.
When AI-drafted content stops representing the authentic voice of the mission.
When beneficiaries do not know AI is involved, and what meaningful notice looks like.
What boards must require before something goes wrong.
Turning informal, ungoverned staff use of AI into a defensible, auditable posture.
How HIPAA-covered nonprofits can adopt AI without putting protected health information at risk.
Governing AI across recruiting, evaluation, compensation and the rest of the HR cycle.
What boards should and should not do as AI is implemented, and how to avoid category confusion.
Why effective governance begins with knowing where the organization actually stands.
Turning a readiness score into a phased, functional governance framework.
The distinct risks of tools that produce text, images and code, and how to govern them.
Governing the AI your vendors have already built into the platforms you use.