Nonprofits may have the most to gain from AI and the least room for mistakes. When budgets are tight, teams are stretched, and trust is everything, “move fast and break things” is not a strategy. So what does responsible AI adoption actually look like for a mission driven organization?

We sit down with Agnes Vishnevkin, COO of Disaster Avoidance Experts, to unpack where AI can create real mission value and why adoption is fundamentally a human challenge. We talk through the psychology of resistance, from distrust and misinformation to fear of being replaced and the stress of changing familiar workflows. Agnes shares what she sees work in the field: respectful change management, training that sticks, and giving people genuine ownership instead of forcing compliance.

Then we get concrete. You’ll hear how to spot quick wins, measure success beyond “hours saved,” and build cross departmental AI champions so usage spreads across the organization. We also cover AI governance basics for nonprofits handling sensitive information, including keeping a human in the loop, finding low risk use cases that require no personal data, and why enterprise AI tools matter if you care about privacy and control.

If you lead a nonprofit, advise mission driven teams, or want practical AI strategy grounded in trust, this conversation will give you a clear playbook. Subscribe to She Builds with AI, share this with a leader who’s stuck in experimentation mode, and leave a rating or review so more people can find the show.

Agnes Vishnevkin

• LinkedIn: https://www.linkedin.com/in/agnesvishnevkin

Disaster Avoidance Experts

• LinkedIn company page: https://www.linkedin.com/company/disaster-avoidance-experts
• Website: https://disasteravoidanceexperts.com/

Your AI prototype is impressive, the demo gets applause, and then production happens. Suddenly you’re dealing with weird edge cases, shifting outputs, unclear ownership, and a stack of tools that don’t quite add up to something your company can trust. We sit down with Shanea Leven, co-founder and CEO of Empromptu AI and the founder of CodeSee (acquired by GitKraken), to talk about what it really takes to move from “it works” to “it’s reliable.”

We dig into why AI is not just another SaaS feature, and how non-deterministic systems demand a different approach to engineering: clean data, system-level guardrails, monitoring, and evaluations that define what “good” means for each workflow. Shanea shares a practical way to think about accuracy across use cases and why edge case detection is where enterprise AI lives or dies. If you’re building AI agents, internal copilots, or customer-facing AI products, this is the part that decides whether you earn trust or burn it.

Then we get into the long game: the difference between renting intelligence from third-party foundation models and building an intelligent asset your company owns. We talk dependency risk, business continuity, open-weight models, and when it makes sense to fine-tune or train custom models using expert feedback and real operational workflows. Shanea also shares lessons from raising a lean pre-seed in a market obsessed with mega-rounds, plus what she’s learned as a second-time founder leading with conviction.

If this sparks new questions about your AI roadmap, subscribe, share the episode with a builder on your team, and leave a review so more people can find the show.

Stay Connected with Shanea Leven and Empromptu AI

🔗 Shanea on LinkedIn: https://www.linkedin.com/in/shaneak/

🔗 Empromptu AI: https://empromptu.ai/

AI doesn’t fail women because it’s “bad at math.” It fails when the data behind it leaves women out, flattening real lives into a default user that never had to navigate widowhood, caregiving, fragmented healthcare, or high-stakes rights decisions.

I sit down with Shubhi Rao, founder and CEO of Uplevyl, to unpack what gender data actually means in practice and why women-centered AI can’t treat women as one monolithic group. Shubhi shares how her path through software engineering, finance, and executive leadership led to a simple but uncomfortable question: if AI is powered by datasets and algorithms, where are the datasets that reflect women’s lived experiences across life stage, culture, and circumstance?

From the great wealth transfer and the hidden complexity of widowhood to the need for trauma-informed support for survivors seeking workplace rights, we explore what trustworthy AI looks like when the stakes are real. We also get concrete about privacy and safety: anonymity, minimal data retention, and clear boundaries on whether user interactions are ever used to retrain models. And we zoom out to the opportunity for women inside companies today, from process reengineering to board-level governance and risk, with practical questions to ask about sourcing, testing, accountability, and who benefits.

If you want ethical AI, responsible AI, and products that actually work for women, this conversation offers a blueprint for building, not just reacting. Subscribe to She Builds with AI, share the episode with a woman who needs a nudge to claim her seat at the table, and leave a rating or review so more listeners find these stories.

✨ Stay Connected with Shubhi Rao / Uplevyl:

🔗 LinkedIn Shubhi Rao: https://www.linkedin.com/in/shubhirao/
🔗 LinkedIn Uplevyl: https://www.linkedin.com/company/uplevyl/
🔗 Instagram Uplevyl: https://www.instagram.com/uplevyl/