A decade of active M&A left large pharmaceutical companies with a tangled mess of disparate technology platforms and data standards. The immense difficulty of integrating these acquisitions became a primary catalyst for investing in unified, scalable data foundations and modern IT infrastructure.
Genpact carves its niche by not trying to be the world's top strategy consultancy or system integrator. Instead, it focuses on bridging the execution gap, using its deep operational expertise to design and implement practical, effective solutions for clients, thereby bringing strategy to life.
Recognizing their lag in technology adoption, pharmaceutical companies are now recruiting executives from consumer goods (CPG) and retail. These industries have a more mature approach to data and customer-centricity, and pharma aims to inject this DNA into its traditionally conservative corporate culture.
While crucial, the slow, administrative, and sometimes political process of defining "responsible AI" is becoming a deterrent for pharma companies. Aditya Gherola argues that regulators must move faster to provide clear guidelines, preventing the concept from becoming a roadblock to critical innovation in drug discovery.
Effective AI adoption isn't about force-fitting a new technology into a workflow. Leaders should start by identifying a significant business challenge, then assemble an agile team of business experts and technologists to apply AI as a targeted solution, ensuring the effort is driven by real-world value.
The pharmaceutical industry's historically high profitability created a lack of urgency for technological innovation beyond basic ERP systems. It wasn't until patent cliffs and messy M&A integrations squeezed margins that companies began seriously investing in modern data platforms and cloud infrastructure to improve efficiency.
Aditya Gherola's passion for healthcare transformation was ignited by seeing a cancer patient's family wait eight hours for a bill post-chemo. This direct exposure to how administrative inefficiency causes profound human suffering became a powerful career motivator, shifting his focus to process improvement in the sector.
While traditional AI predicts and generative AI creates, emerging "Agentic AI" takes autonomous action. For example, it could independently re-route a supply chain away from a new geopolitical conflict zone, proactively finding and negotiating with alternate suppliers—a task that previously required weeks of human re-planning.