Briefings · Workshops · Media

Sharper conversations about AI, product strategy, and adoption in healthcare.

I help healthcare leaders and investors turn AI from excitement into operating capability, and see what has to change before it becomes useful, credible, and scalable.

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Available for executive briefings, workshops, podcasts, contributed articles, private roundtables, panels, and conference talks, each grounded in operating experience rather than AI theory.

Recent stages and press

Latest
Closing keynote, CPO Summit
Product-Led Alliance · June 2026

On stage

  • Trust Debt · Sidebar · March 2026
  • Why Your Deals Stall After the First Yes · JPM Week · January 2026
  • Ship Smart: AI Risks That Kill Deals · Well Women · October 2025
  • Getting Raise Ready · Stripe & XmartLabs · November 2025

In press

Full press and speaking history

AI does not become valuable because it exists. It becomes valuable when a company knows how to operate it.

Based on the ideas behind the book
Built to Survive
Building Trusted AI Products and Organizations

As companies move from idea to scale, the questions change. Early teams need speed, focus, and product judgment. Growing companies need evidence, repeatability, culture, and operating discipline. Scaling organizations need governance, decision rights, investment choices, and trust infrastructure that can survive buyers, boards, regulators, investors, partners, and enterprise scrutiny. These sessions bring that thinking into practical conversations for healthcare leaders, AI teams, boards, investors, founders, and operators.

Forthcoming, fall 2026. Co-authored with Kimberly Bloomston, CPO at 6sense.

Best formats

Six ways to bring this into the room, scaled to the audience and the moment.

Executive briefings

Focused sessions that help senior audiences align on which AI bets are worth making, what can be claimed, how cross-functional teams decide together, and how AI becomes operating capability rather than isolated activity.

Length: 30–60 minutesBest for: executive teams, boards, investors, portfolio companies, leadership offsites

Workshops

Working sessions that move beyond the talk. Teams evaluate AI opportunities, identify adoption risks, clarify decision rights, and pressure-test whether their current approach can become useful, credible, and scalable.

Length: 60–120 minutesBest for: leadership and product teams, AI governance groups, accelerators, executive education

Private roundtables & dinners

Candid conversations for executives, investors, founders, and operators around the operating questions behind AI adoption. Fewer generic predictions, more practical discussion about what companies are trying to build, govern, sell, and scale.

Length: 90–150 minutesBest for: investor dinners, executive communities, founder groups, sponsor-hosted salons

Podcasts & interviews

A practical operator perspective on AI operating models, regulated product strategy, healthcare-market fit, product trust, enterprise adoption, and what leaders get wrong about AI in healthcare.

Best for: healthcare and AI podcasts, product leadership shows, investor and operator interviews

Contributed articles & essays

Writing on the gap between AI promise and operating reality in regulated healthcare. Practical judgment over trend commentary: what leaders need to decide and what companies need to build.

Best for: healthcare publications, investor newsletters, product and AI governance outlets

Conference talks, panels & keynotes

A clear, grounded point of view on AI and adoption in healthcare. Why promising AI initiatives stall, and what leaders need in place before AI becomes durable business value.

Length: 20–45 minutesBest for: healthtech, medtech, and innovation events, product summits, investor forums

Signature topics

Six talks, each built for healthcare leaders, AI teams, boards, and investors.

Audience takeaways

  • Why AI pilots often fail to become operational capability
  • How to separate AI activity from AI strategy
  • What an AI operating model is, and how to define decision rights across product, data, compliance, clinical, security, and commercial teams
  • How to avoid both reckless experimentation and governance theater
  • How to connect AI governance to product and business value
  • What boards should ask beyond “what is our AI strategy?”
Best for: executives, boards, investors, AI and governance leaders, product leaders, and healthcare operators

Audience takeaways

  • What responsible AI requires in a regulated clinical setting, past the policy document
  • How to validate AI when intended use, claims, and the evidence bar all move together
  • How to design governance that survives changing guidance instead of breaking with each update
  • How to monitor for drift, performance decay, and off-label use after a model is live
  • Where a moving regulatory environment creates advantage, not just exposure
Best for: healthcare and healthtech executives, AI and ML teams, regulatory, quality, and clinical leaders, and boards overseeing AI risk

Audience takeaways

  • How AI product needs change as companies move from idea to scale
  • Why trust is an operating requirement, not a brand message
  • How product decisions, culture, investment choices, and governance interact
  • What breaks when teams scale faster than their operating model
  • How to build products and organizations that survive buyers, boards, regulators, and investors
Best for: executive audiences, founder communities, product and AI leaders, startup programs, leadership offsites

Audience takeaways

  • How to evaluate whether an AI story is credible
  • Where AI claims, evidence, and data rights create hidden risk
  • Why adoption risk often hides behind product excitement
  • What to ask before investing, partnering, acquiring, or scaling
  • How to think about the first 90 days of AI value creation
Best for: investors, boards, PE/VC portfolio teams, strategic buyers, corporate development

Audience takeaways

  • How to distinguish data exhaust from a data asset
  • What makes data commercially useful, not just technically interesting
  • How to evaluate data-to-product opportunities
  • Why claims, evidence, rights, workflow, and buyer value matter early
  • How to avoid building AI features no one will pay for or trust
Best for: healthcare services companies, product leaders, medtech and diagnostics companies, data leaders, investors
Arvita Tripati, founder of Vahana Labs

Why Arvita

Arvita Tripati is a product and compliance executive, advisor, speaker, and founder of Vahana Labs. She has nearly two decades of experience across regulated healthcare technology, AI-enabled products, SaMD, diagnostics, clinical trial technology, privacy, security, data governance, and enterprise healthcare.

Her work sits at the intersection of product strategy, regulated commercialization, claims, evidence, governance, workflow adoption, culture, investment choices, and market readiness. She has helped build, govern, ship, and scale regulated products in environments where adoption depends on more than a compelling demo.

Her forthcoming book, Built to Survive: Building Trusted AI Products and Organizations, extends that work into a broader framework for building AI products and organizations that can survive scale.

Bring Arvita into the room

For executive briefings, workshops, podcasts, contributed articles, private roundtables, panels, keynotes, or investor and board sessions, reach out with the format, audience, timing, and topic area.

Discuss a session