How We Approach Upskilling

For people who are new to AI, or who have experimented with tools but want a stronger foundation, this two-hour session combines essential concepts with hands-on practice.

Participants learn what generative AI and large language models actually do, how to work effectively through a chat interface, and how to evaluate AI-generated results rather than simply accepting them.

We'll practice prompting, providing context, working with files, refining results through conversation, and applying AI tools to real workplace tasks.

Responsible use is integrated throughout the session, including privacy and sensitive information, hallucinations and accuracy, bias, intellectual property, transparency, human review, and recognizing when AI should, and shouldn't, be used.

Where your organization already has AI guidelines, an acceptable-use policy, or an approved platform, we build those directly into the session. Participants leave knowing not only how these tools work in general, but what is expected of them here, which accounts to use, and where to take a question when they are unsure.

AI can dramatically expand what an individual researcher or analyst can accomplish, but good AI-assisted research requires more than asking a chatbot a question.

This workshop explores how AI can support the full research and analysis process: developing questions, finding information, analyzing documents, comparing sources, synthesizing findings, examining spreadsheets and datasets, identifying patterns, and communicating conclusions.

Participants also learn how to recognize weak evidence, verify citations and claims, distinguish AI synthesis from source material, and maintain human judgment throughout the analytical process.

The real power of AI often emerges when it has access to the right context, not just a good prompt.

This workshop introduces Projects and related workspace features available in leading AI platforms. Participants learn how to bring together instructions, conversations, files, reference materials, and organizational knowledge so AI can support an ongoing project or body of work.

We'll also demystify retrieval-augmented generation (RAG) and explore how AI can retrieve information from collections of documents rather than relying solely on what a model already "knows."

Generative AI can support much more than drafting text. Today's tools can work across writing, images, presentations, documents, audio, video, and other forms of content.

This hands-on workshop explores how mission-driven organizations can use AI tools throughout the creative process, from brainstorming and first drafts through editing, adaptation, design, and repurposing.

The emphasis is not on producing more content simply because we can. It is on using AI tools to make communications work more effective while maintaining authenticity, accuracy, accessibility, and human judgment.

AI is increasingly able to complete multi-step tasks, work across tools and information sources, respond to triggers, and carry out recurring processes.

This introductory workshop demystifies AI agents and automations without requiring participants to be developers. Through practical examples and demonstrations, participants learn what these technologies are, how they differ from ordinary chatbot interactions, and where they might fit into organizational workflows.

Natural-language AI tools are changing who gets to build software. People can increasingly describe what they want, create a prototype, test it, identify problems, and improve it through conversation.

In this highly hands-on workshop, participants experience that process themselves.

We'll start with a small, real problem and use AI tools to create a functional prototype, such as a simple web tool, calculator, interactive resource, dashboard, form, or other lightweight application.

The emphasis is on learning by building, not learning programming syntax.

Responsible AI adoption requires more than telling employees to "be careful."

Organizations need shared expectations about which tools may be used, what information may be entered into them, when human review is required, how risks are assessed, and who is responsible for making decisions as the technology changes.

This working session helps participants develop the foundations of an organizational approach to AI governance. Rather than beginning with a generic policy template, we start with a more fundamental question:

Does the way we use AI reflect who we are as an organization?

From there, participants translate mission, values, risk tolerance, and operational realities into practical guidance.

Ethics is treated here as a decision-making tool rather than an abstract discussion. Participants work through the judgment calls that policy language alone cannot settle: where an efficiency gain would come at a cost to the people you serve, when AI use should be disclosed, what your organization is simply unwilling to automate, and whether your culture will actually support the guidance you write down.

Moving from employees experimenting with free AI tools to an organization adopting an enterprise platform introduces a new set of questions.

Should we use ChatGPT, Claude, Microsoft Copilot, Gemini, or something else? What type of account do we need? What administrative and privacy settings matter? How should the platform be configured? And how do we introduce it to staff in a way that encourages useful, responsible adoption?

This workshop walks through the organizational journey from selection to setup to launch.

Organizations often know AI could be useful but struggle to translate that possibility into concrete opportunities.

This interactive workshop starts with the work people actually do.

Participants examine workflows, recurring tasks, bottlenecks, information needs, and persistent frustrations, then evaluate where AI might meaningfully help, and where it probably won't.

Each candidate is then examined in concrete terms: what information goes in, what the tool produces, how sensitive that information is on both ends, and what the opportunity is plausibly worth. Participants work in rough estimates rather than false precision, which is enough to compare options and defend a decision to leadership or a board.

Rather than generating a giant list of AI ideas, the goal is to identify a manageable set of opportunities worth exploring.

The accelerator compresses what most organizations spread over months into a focused day or two. It works for a single organization bringing its team, leadership, or board through together, and for small cohorts of three to eight organizations convened by funders, intermediaries, or membership associations.

The hands-on learning day builds a shared foundation: what AI is, what it can and cannot do, responsible AI principles, and practical exploration of how AI and automation apply to your work.

The governance and strategy day turns understanding into action. We draft a responsible AI governance framework for your organization and begin a strategic roadmap: where AI fits, what to prioritize, what to avoid, and how to phase adoption in a way your team and stakeholders can stand behind.

Take either day on its own, or both together. The two-day version is the full path from AI literacy to actionable strategy.