Advisory
I help fundraising leadersfigure out what AI actually changes, and what to do about it.
Strategy and governance work for nonprofits, foundations, and philanthropy platforms putting AI to work without losing donor trust.
The work
What this is.
Most fundraising teams are trying to figure out two things at once: which AI tools are real, and how to adopt them without burning donor trust. Vendor decks do not answer either question. Generic AI workshops do not either.
I work with a small number of organizations each year on what comes after the demo. Strategy, governance, and the specific decisions that move revenue or capacity in ninety days. Most engagements run three to six months. Every one produces a written AI use policy your board can sign off on, named tools, and measurable outcomes. Not a slide deck.
I am the author of AI for Nonprofit Fundraising (June 2026). My operating background, including CEO of Giving Compass and co-founder of Goodworld, informs the work but does not define it.
The thesis
The thesis
AI did not change fundraising because it made tasks faster. It changed fundraising because it changed where judgment lives. The job of leadership is to redesign the workflow around that shift, not to bolt tools onto the old one.
From AI for Nonprofit Fundraising
Scope
What we work on, and what we will not do.
| Focus area | What we work on | What we will not do |
|---|---|---|
| Strategy | Specific decisions, named tools, measurable outcomes tied to revenue or capacity. | Generic frameworks or maturity models that do not produce a decision. |
| Ethics and governance | Donor consent, data residency, model risk, written policy your board can sign off on. | Slogans about “responsible AI” without operational meaning. |
| Implementation | Pilots tied to a revenue, retention, or capacity hypothesis you can test in 90 days. | Tool demos disconnected from your CRM, your data, and your team. |
| Measurement | Pre-AI baselines and post-pilot deltas, reported in the language your board uses. | Vanity metrics or vendor-supplied case studies. |
Process
How engagements run.
Most engagements start with a two-week diagnostic. A review of your current fundraising operation, donor data, tool stack, team capacity, and one or two priority use cases.
From there we agree on a 90-day or six-month plan with named deliverables. You will know exactly what is being decided, by whom, and when.
Three-month strategy sprints are common. Six-month implementation partnerships are more common. A small number of foundations and platforms work with me on senior advisor retainers across longer build cycles.
Fit
Who this is for.
This work fits best for
- Nonprofit CEOs and Chief Development Officers building a credible AI strategy for the board.
- Foundations briefing grantees, program officers, or trustees on responsible AI adoption.
- Donor advised fund platforms, wealth advisors, and fintechs integrating AI into philanthropy products.
- Boards that want a serious, non-hype briefing on what is actually changing in donor behavior.
It is not the right fit for
- Organizations looking for a vendor to install software.
- Teams seeking general “AI literacy” training disconnected from fundraising.
- Anyone hoping to outsource the judgment that AI is making more important, not less.
Frequently asked
Frequently asked questions.
- What does an advisory engagement actually look like?
- Most engagements start with a two-week diagnostic: a review of your current fundraising operation, donor data, tool stack, team capacity, and one or two priority use cases. From there we agree on a 90-day or six-month plan with named deliverables. You will know exactly what is being decided, by whom, and when.
- How long does a typical engagement run?
- Advisory engagements run three to six months, occasionally extending to a senior advisor retainer for foundations or platforms with a longer build cycle.
- How is this different from a generative AI workshop?
- Most AI workshops teach prompt writing. This work starts from the fundraising P&L and works backward. The goal is not for your team to use ChatGPT more often. The goal is to identify the two or three workflows where AI changes your unit economics, and to build those out responsibly.
- What size organizations do you work with?
- Engagements range from $1M to $500M in annual revenue, plus foundations, DAF platforms, and advisor firms. The common thread is leadership that takes both fundraising performance and donor trust seriously.
- Do you also speak and run workshops?
- Yes. Keynotes and team workshops are available alongside advisory work. Use the contact form below and tell me what you are looking for.
- Do you work with vendors or only nonprofits?
- Both. I advise a small number of philanthropy platforms, fintechs, and foundation-backed initiatives where the work is genuinely useful to the field. Engagements are conducted independently of my role at Giving Compass. Any potential conflicts are disclosed in writing at engagement start.
- How do you handle donor data and ethics?
- Donor data does not leave your environment without a written agreement. Ethics is treated as an operational discipline, not a values statement, with named decisions about consent, transparency, model use, and human oversight. Every engagement produces a written AI use policy your board can review.
- How do I get started?
- Use the contact form below or email directly. Briefly describe your organization, what you are trying to decide, and your rough timeline. You will hear back within three business days.
Get in touch
Ready to start?
Tell me what you are working on. I respond within three business days.
Or just exploring
Read Chapter 1 of AI for Nonprofit Fundraising for free and get the monthly dispatch on AI and philanthropy.