How We Saved a Nonprofit Weeks of Effort with One AI Prompt

This week, I wrote an AI prompt that saved a nonprofit weeks of effort—and what may have been $40,000 in a traditional consulting engagement. 

A non-profit client asked me during a business advisory and coaching call how I'd create a step-by-step process to guide their volunteers through the end-to-end client experience.

I began by outlining a typical consulting engagement: an assessment of the current state, future-state design, building recommended tools, running a pilot test, and developing a communications and training plan for volunteer adoption.

In my years as a client partner at a global firm, scoping, delivering, and overseeing work just like this, I might have drafted the Scope of Work (SOW) to look something like this:

• Services:

  • Assess: Audit existing processes, artifacts, and tools to identify gaps and opportunities. Interview up to ten (10) stakeholders to understand current processes, roles, responsibilities, pain points, and opportunities. Gather and document necessary business and technical requirements to inform the design. Conduct market and competitive research to identify industry frameworks, trends, and best practices.

  • Design: Facilitate a future-state design workshop using activities like empathy mapping to understand key personas' needs, and brainstorming to identify sequenced steps grouped by phase. Capture all inputs into a value stream map in Miro or a similar tool, including client experience, volunteer actions, key artifacts, and key meetings.

  • Build: Design an easy-to-use playbook with resources such as one-pagers for each phase, templates, tools, and coaching guides for volunteers. Evaluate and develop technical tools to facilitate and automate the process where possible. Develop materials for rollout and change adoption, including email communications, web landing pages, and training guides.

  • Test: Define an early prototype to test one (1) use case, gathering feedback and iterating on the design and change adoption materials. Define a pilot to test five (5) use cases, gathering feedback and iterating on the design and change adoption materials. Conduct workshop(s) to pressure test scenarios, evaluate contingency plans, and iterate on the process design.

  • Plan: Design a strategy and plan to roll out the new, end-to-end process. Develop a timeline or roadmap for rollout.

  • Engagement Management: Facilitate a formal kickoff of the engagement, reviewing objectives, success criteria, timeline, and activities. Provide regular status updates like meetings and reports to key sponsors and stakeholders. Conduct regular quality reviews of deliverables to ensure adherence to the scope and success criteria.

• Deliverables: Current State Assessment & Recommendations, Future-State Value Stream Map, Future-State Playbook, Change Adoption Strategy & Plan, and Timeline & Roadmap

• Est. Timeline: 6-8 weeks

• Resources: Engagement Lead, Process Optimization Lead, Change Management Lead

• Est. Cost: $180k - $240k

Sounds pretty involved, right?

Then, after explaining these steps, I said, "Why don’t we try putting this into AI to see what it comes up with?"

I opened Google Gemini and typed something like, "Can you create a step-by-step process including what the client is experiencing, what the volunteers are doing, which volunteer role is taking action, the artifacts that will be used, and the meetings that need to happen for a nonprofit that helps clients [x]."

It pumped out a beautifully outlined set of phases and steps that didn’t look too far off from what I envisioned a team designing. Then, I asked it to format it in a table. Then, I asked it to take the high-level phases and build a graphic. Finally, I asked it to build one of the recommended artifacts.

That alone was historically about a week or so of work in a design phase, valued at roughly $40,000.

My client’s jaw dropped. She exclaimed, "You just did in 5 minutes what I’ve been struggling to do for weeks!"

I, too, was surprised—and I spend most of my day vibing with the bots.

Yet, this experience amplified a question that’s been lurking in my mind for months: What is my job as a consultant if half of what I can do can be replaced by artificial intelligence (AI)?

So, naturally, I went down a rabbit hole of processing this. Here are my takeaways:

Prompt Engineering Requires Outcome Visioning

It took 15+ years of experience to know the outcome I wanted, to visualize the deliverable, and to articulate my needs clearly enough to get a good result. Those who struggle to express their desired outcome will struggle with AI. We all need to become more creative, descriptive, precise, and sophisticated in our prompting.

Lived Experience Informs an Understanding of Great

It also took 15+ years of lived experience to know that what AI generated was workable, evolvable, and improvable. Not every prompt yields a great outcome, but my experience helps me discern quality and experiment with better prompts. Those without lived experience might be AI wizards but won't recognize when an output isn't truly viable. We'll need both technical AI skills and deep practical experience in the future.

Change Adoption Doesn’t Happen From Great Solutions Alone

Coming up with a solution isn't necessarily the hardest part. Plenty of existing frameworks and past experiences inform effective designs—hence why conversational AI can do it in seconds. While AI excels at generating initial drafts or the "first mile", the true challenge and value now shift to the "last mile." That is, integrating the solution into an existing environment and securing human buy-in, adoption, and sustainment. AI might provide the perfect blueprint, but a human consultant ensures it's actually built, adopted, and used effectively. After all, a perfect solution that isn’t adopted is just—a document.

AI Elevates the Consultant to a Strategist & Curator

My job isn't to do the data analysis or draft the process map anymore. It's to strategize where AI brings the most value, curate the inputs, validate the outputs, and integrate AI-generated components into a cohesive, impactful solution. I'm moving from primary producer to a sophisticated conductor or architect. This reframes the consultant's role from a task-doer to a higher-level strategic partner who leverages powerful tools and emphasizes critical thinking to identify optimal AI use cases.

AI Democratizes Expertise & Shifts Attention

AI tools are democratizing access to high-quality output and information that once required expensive expertise or extensive time. This doesn't eliminate the need for experts, but it shifts who can access that level of output and what experts focus on. For nonprofits, this is a huge opportunity to access capabilities they might never have afforded, highlighting AI's positive societal impact, especially for resource-constrained organizations.

We Need to be Intentional About Where We Use AI

Many of the activities in this particular engagement could benefit from AI, such as analyzing documentation, capturing interview notes, conducting market research, drafting value streams, writing playbook copy, and crafting communications. Yet, we must ask ourselves: just because we can use AI, should we? When we remove the human element, we risk missing connections, understanding, alignment, and engagement, which can lead to larger challenges. In the future, we’ll need to thoughtfully identify which pieces must remain human to create strong outcomes.

Storytelling (and the Human Narrator) Has Enduring Power

AI can generate compelling copy and outline narratives. But truly impactful storytelling—the kind that moves people, builds empathy, and inspires action—requires a human touch. It’s about understanding your audience’s deepest fears and hopes, the nuances of their environment, and delivering a message with authentic conviction. AI provides the words, but a human narrator provides the soul, tailoring the story on the fly based on reactions and weaving facts into an unforgettable journey. This emotional resonance is vital for buy-in and sustained change. In a world saturated with information, stories cut through the noise. Consultants aren't just delivering data; we're delivering a vision, a purpose, and a path forward that resonates deeply with the people who have to live and breathe the change.

The Imperative of Ethical AI & Responsible Use

Just because AI can do something doesn't mean it should or should be trusted blindly. Consultants must play a crucial role in advising clients on the ethical implications, data privacy, bias mitigation, and responsible governance of AI use, especially in sensitive areas like healthcare. The human element is essential for ensuring fairness, accountability, and transparency. This addresses AI's potential pitfalls and underscores the enduring need for human judgment and ethical frameworks, highlighting a new, critical area of consulting expertise.

My job, and frankly, the job of every consultant stepping into this AI-accelerated future, is to amplify impact by expertly navigating the "last mile" challenges of change adoption, ethical application, and deep empathetic connection. While AI takes on the heavy lifting of drafting, analysis, and initial solution generation, the consultant's role shifts to being the strategic architect, curator, and storyteller, wielding AI's raw power to drive tangible, human-centric results and truly transform an organization.

Oh, and that consulting engagement might take just as long—only now we’ll spend more time on the co-creation workshops, integration design, pilot testing,  and change adoption activities after we’ve quickly spun up tailored materials to work from. The profile of the time investment in the work just flips.