Commentary|Podcasts|April 3, 2026

Scaling AI's Promise in Healthcare: The Time is Now

In Part 2 of our podcast video episode with ZS CEO Pratap Khedkar, he breaks down pharma's need to move beyond AI pilots to scalable impact—and how companies can "go from informing to solving" while navigating trust, regulation, and a rapidly shifting patient dynamic.

Pratap Khedkar, PhD, CEO of ZS, joined the Pharm Exec Podcast to discuss the crossroads moment facing the adoption of artificial intelligence across pharma and healthcare. Drawing from findings in a recent ZS and Healthcare Leadership Council industry report, he outlines a sector transitioning from experimentation to targeted, high-value use cases—from clinical trials and commercialization to supply chain intelligence.

Yet, scaling AI’s promise, Khedkar notes, hinges on solving two fundamental challenges: fragmented policy frameworks and a growing trust gap among patients and providers. As AI reshapes how information flows—often bypassing traditional pharma channels—Khedkar argues the industry must evolve from simply informing stakeholders to actively solving patient and physician needs.

The future, he suggests, lies in personalization at scale and a more holistic, end-to-end approach to delivering patient impact.

To watch Part 1 of Khedkar’s conversation with Pharm Exec, which explored the biopharma dealmaking landscape, supply chain resilience strategy, and China’s appeal as an R&D destination, click here.

Khedkar was elected CEO of ZS in July 2021. Prior to assuming the role, he led the firm’s global pharmaceuticals practice for nine years, as well as a practice focused on the dynamics of healthcare ecosystems. He founded and led its advanced data science capability track, which focuses on AI. Khedkar has also served on ZS’s board since 2012.


Related to this article

How QMM Can Help the C-Suite See a  $100 Million Problem Early
A passing FDA inspection tells pharma senior leadership very little about whether the next significant revenue vulnerability is already taking shape. But continuous, AI-enabled quality management maturity (QMM) has the potential to do so months before the issue reaches the realm of P&L.