Healthcare systems worldwide are increasingly using artificial intelligence to improve care and reduce costs. During the recent AI Impact Summit in New Delhi, the Ministry of Health and Family Welfare introduced a national strategy to use AI in medicine “that works for every patient, in every region, regardless of income, language, or geography.” To better understand how these technologies could improve accessibility and affordability in healthcare, we spoke with Sachin Bajpai, an esteemed healthcare AI professional with international experience working with major medical organizations through companies including PwC, Deloitte, and CitiusTech.
Bajpai believes that one of the biggest opportunities for AI lies in medicine and healthcare. “AI systems can analyze medical and behavioral patterns early, allowing healthcare providers to identify high-risk patients before their conditions become critical or require expensive emergency and intensive care,” states Sachin.
One example of this approach came from a unique predictive AI system Bajpai developed while working at PwC, one of the world’s largest professional services firms with operations in more than 150 countries. The model focused on elderly patients covered through U.S. government-supported insurance programs and identified people at risk of requiring costly skilled nursing facility care – one of the most expensive forms of long-term treatment. Sachin’s original system analyzed patient patterns early enough for healthcare providers to intervene before conditions escalated. During a six-month pilot program involving more than 300,000 patients, the model identified around 20,000 high-risk cases and reduced medical spending by nearly $10 million. The program later expanded across 21 U.S. states.
Bajpai’s approach is especially valuable in countries with large populations and overstretched healthcare systems, such as India. “The earlier healthcare providers can identify risk, the more effectively they can intervene,” he says.
Beyond prediction, AI could fundamentally change how healthcare systems manage resources. “Having spent many years in India, I know hospitals and doctors often work under enormous pressure because of the sheer number of patients they see every day,” Bajpai points out. “AI can reduce some of that operational burden, improve coordination, and give medical professionals more time to focus on patient care.”
Much of Sachin’s work has focused on solving exactly these large-scale operational challenges. Before joining the Fortune 500 consulting firm, he led the development of a cloud-based clinical reporting platform at CitiusTech, a global healthcare technology company. The solution later earned certification from the National Committee for Quality Assurance (NCQA), allowing healthcare providers to use the platform for official quality reporting in the U.S. healthcare system. The product expanded to a portfolio of 15 customers within less than two years.
He later joined PwC, where he currently leads healthcare AI and data transformation initiatives as Managing Director. Over nearly a decade, Bajpai worked with PwC on expanding the company’s healthcare AI operations; it has grown 10 fold professionals across the U.S., India, China, Poland, and Mexico. During his tenure, the company’s healthcare AI solutions received major industry recognition, including Microsoft Partner of the Year awards.
Still, Bajpai notes that technology alone will not solve healthcare challenges. “For AI to work effectively in medicine, both doctors and patients need to trust the systems they use,” he explains. Building that trust requires more than technical accuracy – it depends on transparency, regulatory compliance, data security, and a clear understanding of how AI-generated recommendations are produced and validated in clinical settings.
But as AI adoption accelerates, how do we decide which technologies we can actually trust? This is where experienced specialists like Sachin Bajpai become especially important.
During his career, the organizations Bajpai has worked with have regularly invited him to review medical technology systems and large-scale AI solutions, as well as advise healthcare clients and startup founders on technical strategy, scalability, and long-term system performance.
What is more, working across healthcare AI projects for many years has given Bajpai a close view of how differently medical environments operate from one region to another. “Healthcare systems in India operate across different languages, regions, and levels of infrastructure,” Sachin argues, “and developers need to train AI models on diverse and representative data so the systems can work reliably at scale.”
Despite these challenges, Sachin Bajpai believes our country is well-positioned to become one of the world’s most important markets for practical healthcare AI solutions, thanks to its strong engineering talent and rapidly growing digital infrastructure.