AI value dies in the decisions between functions.

Arvita Tripati helps healthcare executives, boards, investors, and product leaders understand why promising AI initiatives fail to produce measurable value — and what leadership must change for them to survive deployment, scrutiny, and scale.

Her talks move beyond demonstrations, abstract governance principles, and predictions about the future of AI. They examine the operating decisions that determine what work disappears, what risk remains, whether the economics survive implementation, and who has the authority to act.

Building and scaling regulated healthcare technology

Across AI, diagnostics, clinical trials, connected health, and cell and gene therapy

Product, engineering, regulatory, quality, security, and privacy

Client-attributed value from an accelerated launch

The people who can kill your AI do not work in AI

Why technically successful AI fails to create enterprise value

Best for
Healthcare CEOs, boards, operating partners, investors, health-system leaders, portfolio-company executives, senior functional teams

The model performs. The pilot succeeds. Leadership announces an AI strategy. Then the initiative stalls.

Clinical, security, compliance, finance, and operations each respond rationally to risks the AI strategy failed to address. The result is a technically successful initiative whose economics and workflow cannot survive production. Arvita shows where the value gets trapped, and which operating decisions release it.

Built to Survive

Why the model can work while the product — and the organization around it — still fails

Best for
AI and product leaders, founders, enterprise buyers, CAIOs, CDAIOs, legal and risk leaders, regulated-technology teams, executive education programs

Most AI products do not fail because the technology cannot perform. They fail because the organization has not built the infrastructure required to make defensible decisions about claims, evidence, autonomy, oversight, economics, and accountability.

That trust debt accumulates quietly — an unsupported claim, a limitation Sales avoids, a governance committee with no authority — then comes due through a stalled contract, failed deployment, or an incident no one is prepared to own. Drawing on her forthcoming book, Arvita gives leaders a way to distinguish among:

Clearance is not commercialization

Why regulatory achievement does not create a market

Best for
Medtech, diagnostics, SaMD, digital therapeutics, healthtech founders, investors, accelerators, product teams, commercialization leaders

A clearance, authorization, or reimbursement code establishes permission to sell. It does not establish who will buy, why they will change their workflow, how implementation will be funded, or whether the economics work after adoption.

Regulatory chooses a pathway, Clinical builds evidence, Commercial picks a buyer, Product builds the workflow — each independently. By the time the assumptions collide, the company may have spent years pursuing a market that cannot buy the product as designed.

The objective is not a longer market-entry plan. It is knowing which market can buy, and what the company should prove before committing more capital.

Every session is built around a decision

Arvita’s talks are designed for audiences responsible for making consequential choices, not merely learning about AI. Depending on the audience, sessions may examine questions such as:

Each session is adapted to the organization, sector, and decisions facing the audience.

Attendee conversation following a healthtech session hosted at Silicon Valley Bank.

Why Arvita

Arvita Tripati is a healthcare technology operator and advisor who has spent nearly two decades making the cross-functional decisions that determine whether regulated products reach the market, clear enterprise scrutiny, and scale economically — leading product, engineering, regulatory, quality, privacy, security, and compliance functions across AI-enabled devices, clinical-trial platforms, diagnostics, connected health, and cell and gene therapy.

She has been both the vendor trying to clear enterprise scrutiny and the executive whose signature authorized technology for use — a perspective that is simultaneously commercial, operational, technical, and grounded in regulated reality.

She is the founder of Vahana Labs and co-author, with Kimberly Bloomston, of the forthcoming Built to Survive: Building Trusted AI Products and Organizations, and teaches and advises through MedTech Innovator, BioTools Innovator, Alchemist Accelerator, Redesign Health, and Plug and Play.

The pilot worked. Why didn’t the value appear?

At the CPO Summit, Arvita examined why successful healthcare AI pilots so often fail to become durable operating capabilities.

The talk can be adapted for executive, investor, healthcare-services, and regulated-product audiences.

Built to Survive

Building trusted AI products and organizations

Co-authored with Kimberly Bloomston — a practical field guide for leaders who must build, buy, deploy, commercialize, and stand behind consequential AI.

It explains how trust debt accumulates — and how to decide what must be built now, what can responsibly be deferred, and what is merely theater.