The Enterprise Insights Forum is an invitation-only gathering of senior leaders from major healthcare companies—along with select investors, academics, and startup founders—that explores best practices, delivers practical tools, and disseminates useful information to industry leaders around the topic of AI/ML in healthcare. This one-day event will include a diverse series of talks, ranging from fireside chats to panels to skill-based workshops with leaders working at the forefront of healthcare innovation.


Past Speakers



The Enterprise Insights Forum is a one-day, invitation-only gathering of leaders from major healthcare companies along with select investors, academics, and startup founders. In 2018, the focus was built around Rock Health’s recent white paper on AI and machine learning in healthcare. Each year, the Forum will equip you with actionable insights and an expert network to draw upon, as the content is carefully curated with the enterprise perspective in mind.



The Forum takes advantage of the intimate size and is structured as an organized un-conference to promote candid and open discussions. You’ll have ample opportunity to engage directly with thought leaders, participate in interactive programming, and ask the tough questions that are top of mind for you and your business.


It’s not just exchanging business cards and a handshake. We’re intentionally keeping this event small and intimate to facilitate meaningful connections with your fellow business leaders, dealmakers, and startup founders. And you can leave your stuffy suit at home—from networking at lunch to a post-event reception, there’ll plenty of opportunity for some fun, too.


what attendees mastered in 2018

Attendees may not have left as an academically trained technologists (that is, unless they came as such), but they were prepared with the tools needed to tackle the most pressing challenges facing their healthcare business in the age of AI. Attendees left the room knowing how to:

  • Internally structure themselves to integrate AI solutions into their businesses

  • Think proactively about the ethical implications of AI specific to their businesses

  • Assess the startup ecosystem and separate hype from practical use cases

This event aimed to support enterprise business leaders—including those at hospitals and health systems, pharmaceutical companies, payers, and technology companies—in navigating and leveraging AI/ML solutions. Here’s a breakdown of what attendees, by type, came away with:

  • Pharma, Life Sciences, and Devices

    • How entrepreneur Iya Khalil of GNS Healthcare is making precision medicine a reality by leveraging causal machine learning for drug discovery

    • Perspective from ZS Associates’ John Piccone on working alongside pharma and med device companies using AI to bend the cost curve

    • A look into GSK’s AI-focused group from John Baldoni on how the company has set itself up for the adoption of AI and successful partnerships with startups

  • Providers

    • How entrepreneurs from leading startups, such as Fabien Beckers of Arterys, work in tandem with physicians to earn their trust and leverage algorithms actively used for patient care

    • Learnings from Dr. Robert Watcher of UCSF about how he selects the right opportunities to plug in ML solutions across his organization—and the impact it’s had so far

    • Strategy for implementing AI-powered bedside workflow tools, shared by Tom Cassels of Leidos Health

  • Payers & Self-Insured Employers

    • Guidance around the practice application of machine learning to optimize risk stratification and map your members to appropriate interventions

    • An approach to creating a framework for addressing unresolved ethical issues as a medical community, from Ian Blumenfeld of Clover Health

  • Tech

    • Thoughts from prominent entrepreneur-turned-venture capitalist Vinod Khosla on how he evaluates potential investments in the crowded AI/ML space

    • A case study from renowned mathematician Gunnar Carlson of tech companies’ role in supporting enterprises in automating previously manual processes using machine learning

    • A playbook of how tech companies are becoming “AI-first”—and why so many are entering the healthcare space

  • Academia

    • How private-public-academic partnerships are addressing the elephant in the room: the need for robust, well-structured, clean data sets to train models

    • An explanation of the gaps and limitations of startups and enterprise companies—and the opportunity for academia to plug in and accelerate the advancement of algorithms, data sets, and full-stack solutions

    • First-hand accounts of creating successful partnerships with startups—such as Brandon Ballinger of Cardiogram and UCSF’s joint effort to study DeepHeart, a deep neural network intended to predict cardiovascular risk



Tuesday, June 19th, 2018 | w San francisco

8:00AM–9:00AM: Breakfast & Networking 

9:00AM-9:35AM: Opening Remarks

9:35AM-10:10AM: Fact Or Fiction: What Algorithms Will Do For Healthcare (And When)

While the singularity is nowhere in sight, we are inching ever closer to a world in which more jobs are being replaced or augmented by machines. Industry sentiment ranges from praise to skepticism—some in healthcare are bullishly telling medical students to avoid radiology altogether while others are questioning the level of validation pursued by AI/ML companies. In this session, leaders will take the stage to voice their views on these divergent paths in the AI space.

Robert Wachter, MD, Professor and Chair of the Department of Medicine at UCSF
Vineeta Agarwala, MD, PhD, Venture Partner at Google Ventures

10:10AM-10:50AM: Is AI Ready For Its Bedside Debut?

A bounty of new studies suggests machine learning algorithms are more effective at diagnosis than physicians are, but machines are not diagnosing real patients—yet. Providers are fairly asking some tough questions of these tools as they relate to care delivery—are they effective, will I get paid, and does this put me at greater risk for malpractice? We’ll discuss these implementation hurdles and lay out the timeline for today’s solutions to fully realize the opportunity they represent for patients and providers—lower costs, faster service, and better treatment.

Fabien Beckers, PhD, CEO & Co-founder of Arterys
Tod Davis, Associate Director for Data Science at Cedars-Sinai
Aashima Gupta, Global Head - Healthcare Solutions at Google Cloud Platform at Google
Sameer Badlani, MD, Chief Health Information Officer & VP at Sutter Health

11:00AM-11:40AM: AI Has The Power To Turn Pharma On Its Head—But Will It?

Everyone is talking about AI/ML’s potential for drug discovery, clinical trial management, and precision medicine. What’s less clear is how—and to what degree—these advancements will have ripple effects across the industry and for patients. Will pharma bend the healthcare cost curve? Which beyond the pill solutions will they embrace? We’ll explore just how big of an impact AI/ML use cases are having on pharma’s current business models—and what could be upended altogether.

John M. Baldoni, Senior Vice President, In silico Drug Discovery at GSK Pharma R&D
Iya Khalil, Co-founder, Chief Commercial Officer & EVP of GNS Healthcare
Bruce Palsulich, Vice President of Product Strategy at Oracle Health Sciences Global Business Unit
John Piccone, Principal at ZS Associates
Rebecca Robbins, Business Reporter at STAT News

11:40AM-12:20PM: Exploring The Inherent Tensions Of AI In Health With IDEO. Where Do You Stand?

Coffee or tea? Black/white or grey? Transparency or privacy? In this exercise, we’ll explore provocative “this or that” questions together by physically moving around the room to show, quite literally, where we stand on each tension. Along the way, we’ll discover each other’s beliefs, hopes, and fears as they relate to AI in health, and come to better understand the unique perspective we bring to the table, too.

12:20PM-1:20PM: Lunch

1:20PM-2:00PM: Emerging Ethical Issues For Healthcare In The Age Of AI

Despite all their promise, algorithms trained on data which itself may contain unforeseen omissions or biases can result in subtly—and perhaps dangerously—biased predictions. In this session, experts will open a discussion around how to approach a framework for addressing unresolved ethical issues as a community. We’ll explore the specific ethical issues algorithms pose, including: what margin of error will be allowed for computers in healthcare and what rights do patients have with regards to the data and algorithms involved in their care?

Ian Blumenfeld, Chief Data Scientist at Clover Health
Kirsten Ostherr, Professor of Digital Health & Media Studies at Rice University
Hanne Tidnam, Editorial Partner at Andreessen Horowitz

2:00PM-2:40PM: Forging Partnerships For Impact Across Academia, Startups, And Enterprise

With many of the brightest machine learning minds in academia, how can breakthrough algorithms and applications translate into real business value for startups and enterprise organizations? This panel will explore the opportunities for academics and industry leaders to form critical partnerships, share access to data sets, and accelerate validation.

Brandon Ballinger, Co-founder of Cardiogram
Gunnar Carlsson, Co-founder & President of Ayasdi
Marta Gaia Zanchi, Founding Director of Stanford Byers Center for Biodesign
Karley Yoder, Director of Product Management, Artificial Intelligence at GE Healthcare

2:45PM-3:25PM: How Enterprise Can Prepare For An AI-First World

Clinical AI/ML applications have the potential to create massive savings to the US healthcare system, but it’s not as simple as flipping the “AI on-switch.” How can enterprises evaluate their readiness to embed AI/ML solutions into their business lines? Enterprise leaders will offer deep insight into (1) the key indicators that a company is (or isn’t) ready to enter into a pilot or full commercial contract with an AI/ML startup, (2) the internal collaborations and communication channels that need to be established and how, and (3) how to be an acquirer that continues to spur—and avoid killing—the innovation in an AI/ML startup acquisition.

Kay Eron, Vice President & General Manager at Philips Neuro
Sanji Fernando, Vice President & Head of OptumLabs Center for Applied Data Science
Todd Pierce, Member Board of Directors at Dignity Health & Rock Health
Megan Zweig, Director of Research at Rock Health

3:25PM-4:05PM: The Enterprise Playbook For Identifying Breakthrough Innovation

It has never been more crucial for enterprise to identify which startups are both optimally using AI/ML and ready to scale within healthcare. Yet the path forward for effective integration between startup technology and enterprise business lines is overwhelming—leaders must decide which type of contract is most helpful in managing “readiness risk,” disentangle the different validation signals—from the FDA to academic studies— to assess a startup’s potential to scale, and evaluate compatibility with their own internal data stack and workflows. Investors and enterprise leaders will discuss how companies should navigate the AI/ML startup space in order to differentiate between hype and real business value.

Rowan Chapman, Head of Johnson & Johnson Innovation, California
Christine Lemke, Co-founder & President of Evidation Health
David Rhew, MD, Chief Medical Officer & VP and GM of Enterprise Healthcare of Samsung
Bill Evans, CEO & Managing Director of Rock Health

4:15PM-4:45PM: Fireside Chat With Vinod Khosla

Vinod Khosla, a self-proclaimed “technology optimist” and prominent entrepreneur-turned-venture capitalist, has hardly been one to keep his thoughts on algorithms and healthcare to himself. His views on technology’s role in transforming the human aspect of medicine have sparked responses across the industry—especially from physicians themselves. We’ll sit down with Vinod to delve into how he evaluates the AI/ML healthcare startup space as an investor, his advice to enterprise leaders to stay nimble and innovative, and what he views to be the biggest promises of AI/ML in healthcare.

Vinod Khosla, Founder of Khosla Ventures
Christine Cassel, MD, Visiting Professor at UCSF

4:45PM-5:00PM: Closing Remarks

5:00PM-7:00PM: Networking Reception


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