EY-Parthenon & Microsoft charts path to enterprise adoption at BioAsia 2025
EY-Parthenon and Microsoft have released their latest report, 'Artificial Intelligence at the Helm: Revolutionizing the Life Sciences Sector,' at BioAsia 2025, outlining a strategic adoption framework to help organisations scale AI effectively.
The EY – Microsoft report introduces an AI Maturity Framework that categorises pharma organisations into three stages of AI adoption:
- Foundational – Organisations experimenting with AI but lacking large-scale implementation.
- Innovative – Companies integrating AI into select functions but not yet fully optimized.
- Transformational – Businesses leveraging AI enterprise-wide, driving competitive differentiation.
Organisations may operate at different maturity levels across various functions, reflecting the diverse pace of AI integration within the industry.
Suresh Subramanian, National Lifesciences Leader, EY-Parthenon India, said, “AI is no longer a futuristic concept—it is fundamentally reshaping the life sciences sector. From accelerating drug discovery to optimising clinical trials and revolutionising manufacturing, AI is driving efficiencies across the entire pharma value chain. However, successful adoption requires more than just experimentation. Our AI Maturity Framework provides a structured roadmap to help organisations move from fragmented AI initiatives to enterprise-wide transformation. Organisations that proactively invest in AI maturity today will be the industry leaders of tomorrow.”
Trupen Modi, Sr Industry Executive, Pharma and Life Science, Microsoft added, “Technology plays a pivotal role in enhancing healthcare and advancing life sciences, driving innovations that improve patient care, support clinicians, streamline research and foster better health outcomes. Advances in AI are optimising manufacturing and supply chain processes, ensuring efficiency and reliability. AI is also reshaping the regulatory landscape by automating document analysis, streamlining submissions for regulatory approval, and monitoring compliance. This reduces time to market and improves accuracy. Microsoft’s contributions to the health and life sciences industry span innovations in data and AI to ground-breaking research initiatives that are transforming and empowering clinicians and researchers.”
The EY – Microsoft report identifies three key categories of challenges hindering AI adoption within pharma organisations:
- Ethical concerns, such as algorithmic bias and transparency in AI decision-making, remain a key challenge. In pharmaceutical development, biases in AI models could lead to treatment protocols favouring certain demographic groups, compromising the goal of truly personalised medicine.
- Technical challenges related to data privacy, security and complex regulatory compliance. Navigating evolving regulations is critical for AI integration, requiring a strategic and informed approach.
- Operational barriers include a shortage of AI-skilled professionals and resistance to change. AI is automating repetitive tasks and bringing operational efficiencies across all roles. As AI automates repetitive tasks, professionals must shift toward more strategic, AI-augmented roles.
However, the EY- Microsoft report emphasises that these challenges should be seen as opportunities for developing robust AI adoption strategies in the life sciences industry. As per the report, 75 per cent of CXOs in India’s life sciences industry confirmed that AI has significantly contributed to cost reduction and customer satisfaction.
To progress along this maturity curve, the report outlines five critical pillars for successful AI integration:
- AI-first business and operating models that embed AI-driven decision-making across functions.
- Technology stack enhancements to support large-scale AI deployment and innovation.
- Comprehensive AI-ready data strategies ensure security, compliance, and accuracy.
- Workforce readiness for AI, addressing change management and interdisciplinary skill development.
- Risk and compliance frameworks ensuring AI governance, transparency, and cybersecurity.
As per the EY-Microsoft report, AI is enabling breakthroughs across multiple functions in life sciences:
- Pharmaceuticals & Biotechnology: AI is accelerating R&D processes by identifying drug targets, predicting molecular interactions, and enhancing toxicity assessments. It is also transforming clinical trials through AI-driven patient recruitment, trial planning, and improving production quality, predictive maintenance, etc. in manufacturing and supply chains.
- Medical Technology (MedTech): AI is revolutionising device design by leveraging real-world data and generative design techniques. It also enables predictive maintenance of medical devices, reducing downtime and extending product lifespan.
- Academic Medical Centers (AMCs): AI is enhancing medical education through immersive, mixed-reality training and data-driven research by automating literature reviews and optimising grant funding allocation.
