AI Resources
AI is arriving in organizations faster than most people have had time to think about what they actually want from it. The resources on this page are designed to support that thinking from the ground up and the top down.
They are organized around the premise that the most important AI questions are not technical. They are human. What does your organization need its people to be able to do? Where is technology serving that intention, and where is it getting in the way? What judgment, relationship, and accountability cannot be delegated to a tool, regardless of how capable that tool becomes?
Use what is useful here. Bring your own context to everything you read. And if you want a thought partner for what comes next, please
contact us for a no-pressure consultation.
AI Vocabulary Reference Series
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Tier 1 - FoundationsList Item 1
The language of orientation
This reference introduces the foundational vocabulary of AI: what things are, how they work at a basic level, and why they matter.
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Tier 2 - PractitionerList Item 2
The language of doing
This reference builds on foundational AI vocabulary (Tier 1), for people who are actively using AI tools and want to work with them more effectively, intentionally, and safely.
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Tier 3 - GovernanceList Item 3
The language of organizational decision-making
This reference is for organizational leaders who are shaping AI strategy, governance structures, and policy. It assumes familiarity with foundational concepts (Tier 1).
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Tier 4 - ProcurementList Item 4
The language of procurement and infrastructure
This reference is for those involved in selecting, contracting, or managing AI vendors and infrastructure, including procurement, legal, IT, finance, and senior HR leaders. It assumes familiarity with foundational concepts (Tier 1) and governance vocabulary (Tier 3).
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Tier 5a - Privacy & Security
The language of data protection and operational risk
This reference introduces terms related to the privacy and security risks that emerge when AI tools enter organizational workflows, risks that are distinct from traditional data security and often invisible until they create real exposure. It is for HR leaders, people managers, and operational leaders who need to understand what responsible AI use requires. It assumes familiarity with foundational AI concepts (Tier 1).
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Tier 5b - Workforce Bias
The language of systemic impact
This reference introduces terms related to the systemic consequences of AI adoption, for workforces, for equity, and for the integrity of knowledge itself. It is for senior leaders thinking about organizational strategy, mission alignment, and the broader societal implications of AI. It assumes familiarity with foundational AI concepts (Tier 1) and governance vocabulary (Tier 3).
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Full Series (zip file)
Download the full series as a single zip file
AI Prompting Reference Series
The prompts in this series are starting points. Customize the bracketed fields for your organization, and review all AI-generated content for accuracy, tone, and alignment with your voice before use.
Effective use of AI depends on what cannot be automated: human judgment, discernment, and wisdom; authentic relationships built on trust; organizational context that only you hold; and accountability that belongs to people, not tools. Use these resources to accelerate your work, not to replace the thinking that makes it credible.
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Prompting Basics Part 1 - Reference Card
Prompting Basics Part 2 - Master Tips Sheet
Prompting Basics Part 3 - Practice Worksheet w/ Answer Key
Prompt Use Cases & Examples for:
- Human Resources
- Learning & Development
- Communications & Marketing
- Development & Fundraising
- Finance & Operations
- Legal & Compliance
- Programs & Grantmaking
- Strategy & Planning
- Executive & Board
AI Platform Cheatsheets & Tools
AI Platform Cheatsheets
Understanding what each AI platform can actually do — and how it behaves differently from others — is practical foundational knowledge for anyone using these tools in organizational work.
The most current and well-maintained free reference for this is Conor Grennan's AI Mindset cheatsheet series. Grennan is the former Chief AI Architect at NYU Stern and one of the more rigorous voices documenting platform capabilities from a behavioral and workflow perspective. These are tool capability references, not vendor marketing, and are updated frequently as platforms change. They are free to access without registration.
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ChatGPT Capabilities Cheatsheet — AI Mindset
Claude Capabilities Cheatsheet — AI Mindset
Microsoft Copilot Capabilities Cheatsheet — AI Mindset
Google Gemini Capabilities Cheatsheet — AI Mindset
Gemini (in-depth) Cheatsheet — AI Mindset
He also has cheatsheets for Deepseek (alternative to foundation Western model pricing), Grok (live access to X-hosted public conversation), Meta Llama (consumer-facing AI on all Meta platforms), Midjourney (image generation), and Runway (video and image production), accessible at the bottom of each cheatsheet above.
Note: Platform capabilities change frequently. Verify current features, pricing, and access on each platform's official site before making adoption decisions.
Additional AI-based Tools Worth Checking Out
Conor also hosts a tool to estimate how much time you could realistically save each week by using AI:
AI Efficiency Calculator
And, if you want to understand what's under the hood of all this tech, here's his succinct explanation of
how Large Language Models (LLMS) like ChatGPT, Claude, and Gemini work.
AI Case Studies & Playbooks
The resources in this section are selected for independence, rigor, and relevance to mission-driven organizations. None are produced by AI vendors or consulting firms with a commercial interest in your adoption decisions. All are free and open access.
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Beyond the Playbook: The Human and Organizational Work AI Cannot Do Aurorae Group, LLC · 2025
The most cited research on AI productivity comes from controlled experiments. The findings are real, but they do not tell the whole story. Two rigorous studies tracking AI deployment across tens of thousands of workers in actual organizations reveal a consistent and important gap between what AI can do and what organizations typically gain from it. This brief examines that gap, what research reveals about why it exists, and what it means for leaders making decisions about AI adoption.
[Download: Beyond the Playbook (PDF)]
Source studies referenced in this brief:
Shifting Work Patterns with Generative AI — Microsoft Research / NBER, 2025- Large Language Models, Small Labor Market Effects — Humlum & Vestergaard, University of Chicago / University of Copenhagen, 2025
Playbooks & Implementation Guides
The Enterprise AI Playbook: Lessons from 51 Successful Deployments Stanford Digital Economy Lab · March 2026 · Free PDF · Empirical research across 51 real enterprise AI implementations. Documents what distinguishes organizations that achieve measurable results from those that don't. Strong on workflow integration, executive sponsorship, and failure patterns.
NIST AI Risk Management Framework (AI RMF 1.0) National Institute of Standards and Technology · 2023 · Free PDF · The federal government's voluntary framework for trustworthy AI governance. Non-sector-specific and designed for organizations of any size. The definitive starting point for any organization building AI policy.
NIST Generative AI Risk Management Profile (AI 600-1) National Institute of Standards and Technology · July 2024 · Free PDF · Extends the AI RMF specifically to generative AI tools — ChatGPT, Claude, Gemini, Copilot. Covers governance, content provenance, pre-deployment testing, and incident disclosure.
NIST AI RMF Playbook National Institute of Standards and Technology · Living document · Free online Companion to the AI RMF with suggested actions organized by function. Use as many or as few as apply to your context.
Empowering Education Leaders: A Toolkit for Safe, Ethical, and Equitable AI Integration U.S. Department of Education · October 2024 · Free PDF · Covers AI policy development, federal legal requirements, data privacy, civil rights, and digital equity. Directly applicable to education-focused nonprofits and the organizations that fund them.
Building for Production: A Playbook for Enterprise-Ready Generative AI Solutions Stanford Law School · August 2025 · Free · Practical framework for use case prioritization, risk management, and responsible AI deployment. More technical in orientation — useful for organizations with internal technology capacity.
The Gen AI Playbook for Organizations Harvard Business Review · November–December 2025 · May require subscription · Winner of the 2025 HBR Prize. Offers a framework for deciding which tasks are best automated, handled with human-AI collaboration, or kept human-led. Grounded in academic research from Harvard Business School and NYU Stern.
Nonprofit & Philanthropic Sector Research
Inspiring Action: Identifying the Social Sector AI Opportunity Gap Stanford HAI & Project Evident · February 2024 · Free PDF · The first national survey of AI use, interest, and readiness among nonprofits and philanthropic organizations. Essential context for any education or social sector organization building an AI strategy.
AI With Purpose: How Foundations and Nonprofits Are Thinking About and Using Artificial Intelligence Center for Effective Philanthropy · 2025 · Free · Creative Commons licensed The most representative comparative study of AI use across foundations and nonprofits to date. Covers grantmaking strategies, internal adoption, equity considerations, and the gap between funder understanding and grantee needs.
Closing the Nonprofit Funding Gap in the Age of AI The Bridgespan Group · 2025 · Free · Examines what funders can do to support grantees — from technology tools to governance capacity to staff training. Useful for both funders and funded organizations navigating the AI investment conversation.
Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations U.S. Department of Education · 2023 · Free PDF · The foundational federal report on AI in education. Establishes the principle that humans must remain in the loop and that AI should supplement, not replace, educators. Prerequisite reading for education-focused nonprofits.
Workforce & Organizational Research
Workforce Intelligence: AI and the Future of Work MIT Sloan Management Review · 2025 · Free PDF · Synthesizes current research on how AI is reshaping workflows, redefining roles, and creating new demands on organizational leaders. Accessible for a general professional audience.
MIT Work of the Future Initiative Massachusetts Institute of Technology · Ongoing · All publications free · Multidisciplinary research examining how AI and automation affect workers, firms, and labor markets. Consistently centers the human dimension of technology adoption.
U.S. Workers and AI in the Workplace Pew Research Center · February 2025 · Free · Nationally representative survey of how U.S. workers are actually experiencing AI — who uses it, attitudes toward it, and what they think it means for their future.
How Are Americans Using AI? Evidence from a Nationwide Survey Brookings Institution · February 2026 · Free · Comprehensive analysis of actual AI adoption patterns across sectors, firm sizes, occupations, and demographics.
The Effects of AI on Firms and Workers Brookings Institution · July 2025 · Free · Synthesizes academic research on AI's actual labor market impacts. Distinguishes between task-level automation and full job displacement — a nuanced read that challenges both hype and panic narratives.
Research-Based Implementation Studies
These studies document AI deployed in real workplaces with real workers. They provide the evidentiary foundation that makes organizational AI decisions credible rather than speculative.
Shifting Work Patterns with Generative AI Dillon, Jaffe, Peng & Cambon · Microsoft Research / NBER · 2025 · Free · Longitudinal field evidence from Microsoft's Copilot rollout across a large knowledge worker population over 13 months. Documents how work patterns shifted in practice and why broader organizational transformation requires more than tool access.
Large Language Models, Small Labor Market Effects Humlum & Vestergaard · University of Chicago / University of Copenhagen · 2025 · Free · Links representative adoption surveys to actual administrative labor records across 25,000 workers in 7,000 workplaces, covering 11 occupations including HR, legal, teachers, and accountants. Finding: no significant impact on earnings or recorded hours in any occupation, even for intensive users. Average time savings: 2.8% of work hours. Essential reading for any organization that wants to understand the gap between AI's potential and its organizational reality.
Ready to harness the power of AI for your business? Contact us today to schedule a consultation and discover how we can assist you in navigating the AI landscape.