The Talent You're Filtering Out: Neurodiversity as Engineering Advantage

Engineering runs on exactly the cognition many teams unintentionally screen out: deep focus, pattern recognition, unconventional problem-solving. The exclusion is rarely malicious—it's baked into "normal" defaults for how we interview, run meetings, assign work, and define "culture fit." This session moves past awareness and tokenism to redesign the defaults themselves. We'll show how small, low-cost changes to communication and collaboration unlock neurodivergent talent while making teams sharper for everyone. Inclusion here isn't accommodation—it's an engineering advantage most competitors leave on the table. You'll leave with specific changes to make your team's norms work with more kinds of minds, not against them.

The Nonprofit AI Playbook: From Strategy to Implementation

A practical roadmap for nonprofit leaders implementing AI. This session provides a step-by-step playbook covering strategy, assessment, vendor selection, change management, and success metrics. Learn from real nonprofit case studies what works, what doesn't, and how to avoid costly mistakes. Get frameworks for building your AI roadmap.

The Homogeneity Tax: What Exclusion Is Actually Costing You

Inclusion is usually pitched as the right thing to do. That framing loses budget fights. This session makes the harder, sharper case: homogeneity is a tax you're already paying—in blind spots, groupthink, slower innovation, and the exit of people quietly pushed out through hiring and interview practices designed to protect the status quo. We'll expose where bias hides in "objective" processes and put a number on what sameness costs. Rather than aspirational values, you'll get a diagnostic and a set of repeatable practices that make teams demonstrably smarter. Fairness is the mechanism; better decisions and stronger products are the return.

The GOS Framework: Governance, Operations, and Strategy for Data-Driven Nonprofits

The GOS Framework provides a holistic blueprint for nonprofits building data maturity. Governance sets guardrails, Operations enable capability, and Strategy drives mission impact. This session breaks down each pillar with practical examples, showing how nonprofits can evolve from data-reactive to data-driven organizations. Learn implementation timelines and success metrics.

The AI Audit for Good: A 6-Hour Blueprint to Put People First and AI to Work

Stop going AI-first. Start going human-first.

The winners of the AI era won't be the fastest adopters; they'll be the wisest. In this hands-on 6-hour workshop, you'll build a real AI business blueprint using the "AI Audit for Good": a candid, blame-free assessment that turns your team's honest bottlenecks into your clearest opportunities.

Whether you're a solopreneur or leading a hundred people, you'll use your own data to design a human-centered, responsible AI roadmap, complete with a rollout timeline and an estimated ROI that shows the hours you'll give back to your people for relationships, deals, and growth.

Come curious. Leave with a blueprint ready to execute.

Scaling Impact: How Government Organizations Can Leverage AI for Better Service Delivery

Government agencies serve millions but often operate with outdated systems. This session explores how public sector leaders can leverage AI to improve service delivery, reduce costs, and enhance citizen experience. Learn case studies of successful government AI implementation, governance considerations, and how to navigate public sector constraints and opportunities.

People First, AI Second, Impact Always: The Case Against "AI-First"

"AI-first" has become a badge of honor. It should be a warning label. A company that puts the model before the human building trains itself to solve problems no one has; shipping impressive technology that misses the person it was meant to serve. This session argues that the AI only works because of people, and that human-centered product thinking isn't a nicety, it's how you avoid confidently building the wrong thing. We'll cover how to keep customer reality upstream of technical possibility, and how to know your product actually fits. You'll leave with a mental model that turns "people first" from a slogan into a design discipline.

Nobody Resists Change. They Resist Being Changed.

Most technology rollouts don't fail on the technology—they fail on the human beings expected to absorb them. The usual response is more training and better tooling, which misses the point entirely: people don't resist change, they resist being changed without agency or trust. This session treats adoption as a people problem first and a tooling problem second. We'll unpack why initiatives snap back to old habits, how to build genuine buy-in across skeptics, and how to sequence change so it holds. You'll leave with a playbook for leading technology and process change that produces lasting adoption instead of expensive, well-documented frustration.

Human Capital x AI Capital: Building AI Agents That Serve People First

In this session, Beth Griffith will show how governments, public sector agencies, nonprofits, NGOs, and mission-driven organizations can use AI agents to increase capacity, improve service delivery, reduce operational burden, and strengthen decision-making while keeping people, trust, and guardrails at the center.

Drawing on her work in renewable energy, workforce development, small-business growth, and community-centered technology adoption, Beth will introduce a practical framework for building “human-first agentic systems.” Attendees will explore how to identify the right use cases, design accountability checkpoints, protect against harm, and align AI tools with organizational mission, workforce needs, and public good.

This session is for leaders who want more than automation. It is for builders who want AI systems that expand human potential, protect dignity, and help organizations serve people better.

Human Capital x AI Capital: Building AI Agents That Serve People First

Discover how to design and deploy AI agents that prioritize human dignity and effectiveness. This session explores practical strategies for implementing AI systems in organizations—from government agencies to nonprofits—that augment rather than replace human capability. Learn how to balance automation with accountability, measure impact on real communities, and build governance structures that keep humans central to decision-making. Perfect for leaders, technologists, and innovators ready to put people first in the AI age.

Governing AI for Good: GOS Implementation in Nonprofit Operations

Governance, Operations, and Strategy (GOS) frameworks are essential for nonprofits implementing AI. This session explores practical governance structures that ensure ethical AI use while maintaining nonprofit values. Learn how to establish oversight committees, create implementation timelines, and measure success through community impact metrics. Perfect for nonprofit leaders, program directors, and board members seeking to harness AI responsibly.

Governance, Lineage, and Trust for AI-Ready Data

In the era of AI and machine learning, data governance, lineage tracking, and trust mechanisms are critical for building responsible, transparent, and reliable data systems. This session explores how organizations can implement robust governance frameworks, establish clear data lineage, and build trust throughout their AI-ready data infrastructure. We'll discuss best practices for data quality assurance, compliance, metadata management, and how to ensure accountability in AI-driven decision making.

Governance by Design: Building Ethical AI Systems for Social Sector Organizations

Ethics aren't an afterthought—they're a prerequisite. This session explores how to design governance structures that embed ethical AI principles from the ground up. Learn frameworks for responsible AI deployment, risk assessment, stakeholder engagement, and compliance in social sector contexts. Discover how leading organizations are building trustworthy AI systems.

From Strategy to Action: Responsible AI Leadership That Isn't Cookie-Cutter

Too many districts fall for shiny-object syndrome—buying flashy AI tools their staff never asked for, then wasting scarce budget on solutions that don't fit. This Campus/Expert Perspective reframes responsible AI adoption as a leadership discipline. Before implementing anything, leaders must interview their own people: teachers, paraprofessionals, curriculum and program developers. From there, do the recon and research, then build a governance and implementation framework tailored to your institution's readiness, policies, and goals. Not every strategy-to-action path fits every organization. Kids love cookies, but AI can't be cookie-cutter. Attendees leave with a practical approach to stakeholder-informed, ethically governed, sustainable AI adoption.

Data to the Block: Using Community Data to Advance Environmental Justice, Food Access, and Economic

Detroit has the data. Detroit has the community wisdom. The opportunity is learning how to bring both together to drive better outreach, stronger programs, and measurable impact in environmental justice and economic justice communities.

In this hands-on session, participants will explore how data can identify food deserts, energy burdens, climate risks, workforce gaps, and outreach opportunities across Detroit neighborhoods. Attendees will learn a simple community impact mapping framework they can use to turn raw data into action.

Data Pipelines for Impact: Engineering Solutions for Community-Based Organizations

Community organizations are data-rich but tools-poor. This technical session shows how to build efficient, low-cost data pipelines that CBO teams can operate. Learn practical engineering for collecting, cleaning, and analyzing community data at scale. Explore open-source tools, cloud options, and automation strategies that nonprofits can actually afford and maintain.

Data Governance as Equity: Using Data for Nonprofit Impact

Data equity is a social justice issue. This session explores how nonprofits can use data governance to advance equity and serve vulnerable populations. Learn frameworks for ethical data collection, community data stewardship, disaggregating data by race and other factors, and measuring impact on marginalized communities. Discover how good governance practices ensure data benefits those it's meant to serve.

Culture Is Infrastructure: Why Your Best Engineers Leave Before They Quit

Every org claims culture matters, then treats it as a perk instead of infrastructure. But culture is the operating system your delivery runs on—and when it's broken, your best people disengage months before they resign, taking their discretionary effort with them. This session reframes culture as an engineering concern with measurable outputs: velocity, retention, and speed-to-market. We'll dissect the specific rituals and leadership behaviors that separate teams that compound from teams that churn, and why healthy culture is a competitive moat rivals can't copy. You'll leave able to read the signals others miss and intervene before your strongest people go quiet.

Community Data Trusts: Building Trustworthy AI and Data Systems for Public Good

Data trusts are emerging models for communities to own and control their data while enabling beneficial use. This session explores how community data trusts work, why they matter for equitable AI, and how nonprofits and government can implement them. Learn from pioneering projects building community power through data stewardship.

Beyond Cookie-Cutter: Agentic AI for Truly Personalized Learning

Budget cuts are forcing educators to do more with less, yet no two learners, teachers, or classrooms are alike. This hands-on session explores how agentic AI can move schools beyond one-size-fits-all approaches toward genuine specialization and optimization. We'll examine practical, human-centered ways AI can shorten lesson-plan and study-material creation, support students on IEPs along with their parents, paraprofessionals, and teachers, and analyze learning and teaching styles to suggest best-fit implementation. Attendees will leave with a framework for designing responsible AI agents—complete with guardrails—that elevate educators and personalize learning for every child without sacrificing trust, dignity, or accountability.

AI-Powered Program Evaluation: Measuring Nonprofit Success with Data

How do nonprofits measure what matters? This session demonstrates AI-powered approaches to program evaluation and impact measurement. Learn how machine learning can help identify outcomes, track progress, detect patterns in client success, and communicate impact to funders. Discover tools and techniques to replace tedious manual tracking with intelligent systems that scale.

AI Won't Make You a Better Engineer. It'll Make You a Better Colleague.

The AI productivity conversation is stuck on code completion, and it's aiming too low. The real leverage is in the work we never automated because we assumed it was "soft": communication, feedback, planning, preparing for the hard conversation. This session shows how to use AI as a thinking partner for the human skills that actually determine whether teams succeed—and where handing that judgment to a model quietly backfires. You'll leave with concrete workflows you can use Monday, a clear line between augmentation and abdication, and a more honest map of where AI raises your ceiling versus where it erodes your edge.

AI Wasn't Built With You in Mind. Let's Fix That Together.

You have heard that AI is going to change everything, and you have also noticed that almost none of the people explaining it look like you, run a business like yours, or serve the community you serve. That gap is not an accident, and it is not permanent.

Most AI training is written for people who already have an IT department, a marketing budget, and time to experiment. This session is not that. It is a plain language, no jargon introduction to what AI and Copilot tools actually do, built for small business owners, nonprofit leaders, and community organizations who have been talked at instead of taught.

We will walk through what these tools can realistically do for a business your size, why "AI is going to replace you" is the wrong fear (the real risk is being priced out by someone who learned this before you did), and the first three steps to bring AI into your work without hiring anyone new or buying anything expensive.

You do not need a technical background. You need a seat at the table, and this is it.

Target audience: small business owners, nonprofit leaders, solopreneurs, and community organization staff who are brand new to AI. No technical background needed.

What you will need: a laptop is what you will use to follow along and save the three step starter framework. A phone is fine to bring too, but plan on a laptop. Bring a charger if you have one, and bring your biggest AI question, we will make room for it.

Diversity Training Won't Save You From Biased AI. Here's What Will.

Your team finished the unconscious bias training. Checked the box. Then the new AI hiring tool quietly filtered out candidates from the same zip codes your inclusion strategy spent three years trying to recruit from. Nobody meant for that to happen. That is exactly the problem.

Most organizations still treat "responsible AI" and "diversity, equity, and inclusion" as two departments that have never had a real conversation. That gap is where bias lives now: not in a training slide, but in the model nobody audited, the agent nobody assigned a human owner to, the vendor contract nobody asked the hard questions of.

This session is for people who are past DEI 101 and ready for the harder, less comfortable work: building AI governance that actually protects the people your equity commitments were meant to protect. We will cover how to bias-test an AI system before it ever touches a hiring, lending, or service decision, why every AI agent needs a named human owner instead of a policy binder, and the exact procurement questions that expose a vendor's blind spots before you sign.

Bring your hardest AI equity question. We won't pretend it has an easy answer, but we'll build you a real one.

People First. AI Second. Impact Always.

Target audience: DEI leaders, HR and people leaders, and responsible AI or compliance practitioners who are past DEI 101 and ready to connect equity work to AI governance.

What you will need: a laptop to save the bias testing checklist and procurement questions we walk through. A phone is fine to bring too, but a laptop is what you will actually use. A charger is smart, outlets in session rooms can be limited. No software, accounts, or installs required.

Nobody Told You AI Governance Was Your Job Too. It Is. Here's Where to Start.

Somebody on your team connected an AI assistant to the inbox, the customer list, or the grant files over a weekend, because it was useful and nobody said not to. No policy got written. No one is officially in charge of watching it. That is not carelessness. That is what happens when "AI governance" sounds like a Fortune 500 problem instead of a Tuesday afternoon problem.

Here is the truth nobody at the big conferences says out loud: governance is not firewalls and hundred page compliance binders. It is a small number of very human questions, asked before something goes wrong instead of after. Who owns this AI system. What is it allowed to touch. What happens the moment it is wrong.

This is a beginner level, no jargon session built for nonprofits, small businesses, and community organizations without a dedicated IT or security team. You will leave with a simple ownership framework (every AI agent gets a named primary and backup human, not a policy nobody reads), a short list of guardrail questions to ask before connecting any AI tool to real data, and language you can bring to your board or your funders that does not require a compliance consultant to translate.

Small does not mean exempt. It means this conversation cannot wait for someone else to have it first.

Target audience: nonprofits, small businesses, and community organizations without a dedicated IT or security team who are using or considering AI tools.

What you will need: a laptop to capture the ownership framework and guardrail question list. A phone is fine to bring too, but a laptop is what you will actually use. No existing governance policy or technical background needed. A charger is smart, outlets can be limited.

You Bought Copilot. Your Team Is Still Drowning. Here's Why.

Your company bought the Copilot licenses. Ran the training. The adoption dashboard even looks good. And your team is still working nights, still drowning in the same email threads, still asking whoever is nearest for help getting through a to-do list that never gets shorter. Something is not adding up, and it is not the AI.

Here is the uncomfortable truth: AI does not fix a broken workflow. It makes a broken workflow faster at being broken. Most organizations skip the one step that actually determines whether AI pays off: figuring out where the time is really going before they hand anyone a new tool.

This session walks through the productivity audit we use with our own clients before any AI rollout: how to find the real bottleneck (it is rarely the task people complain about loudest), how to match the right AI capability to that specific bottleneck instead of throwing Copilot at everything, and how to set an ROI expectation leadership will actually believe because it is honest.

You will leave with the audit framework itself, ready to run on your own team this week.

Target audience: business owners, operations leads, and team managers already using Microsoft Copilot or similar AI tools who are not seeing the productivity gains they expected.

What you will need: a laptop is the most useful thing to bring, you will fill out the productivity audit framework for your own team on the spot. A charger is smart, session room outlets can be limited. No software or accounts required.

You're Optimizing AI for the Wrong Number. It's Costing You Your Best People.

Leadership rolls out AI with a straight face and says this is about productivity, not headcount. The team hears it anyway: do more, faster, before we find out we do not need as many of you. So your best people, the ones with options, start quietly updating their resumes while your adoption dashboard looks fantastic in the board deck.

Most executives are optimizing AI for the wrong number. Hours saved and licenses activated tell you nothing about whether your organization is actually stronger a year from now. The number that predicts a real, lasting return is capacity per person and how much institutional knowledge you keep in the building, because AI does not replace expertise. It amplifies whoever is still in the room. If your best people leave, you have simply built a faster path to mediocrity.

This is an expert level session on human capital through AI capital: how to design an AI rollout that grows the capacity of the people you already have instead of spooking them toward the door, which internal metrics actually predict long term ROI (they are not the ones in your Copilot usage report), and how to have the retention conversation with your leadership team before it becomes an exit interview.

People First. AI Second. Impact Always.

Target audience: executives, senior leaders, and HR or people leaders who are rolling out AI across their organization and want adoption to succeed without losing their best talent. This is an expert level, strategy focused conversation; no technical AI background needed.

What you will need: a laptop to capture the retention metrics framework and follow up on the resources shared. A phone is fine to bring too, but a laptop is what you will actually use. A charger is smart, outlets can be limited.