The life sciences sector is undergoing significant transformation as artificial intelligence (AI) continues to influence drug discovery, clinical trials, and precision medicine. With the AI market in pharmaceuticals projected to reach US$16.49 billion by 2034 and AI-driven medical devices expected to grow to US$97.07 billion by 2028, the challenge lies in achieving widespread implementation across the industry.
EY-Parthenon and Microsoft have jointly released a new report, “Artificial Intelligence at the Helm: Revolutionizing the Life Sciences Sector,” at BioAsia 2025. The report offers a strategic AI Maturity Framework designed to help organisations integrate AI effectively across all business functions.
The framework categorises organisations into three stages of AI adoption. The foundational stage includes companies experimenting with AI without scaling their initiatives. The innovative stage features businesses that are integrating AI into select functions but are yet to achieve full optimisation. The transformational stage represents organisations that are using AI across their operations, leading to competitive differentiation. Organisations may operate at different maturity levels across various functions, reflecting the uneven pace of AI adoption within the sector.
Suresh Subramanian, National Lifesciences Leader at EY-Parthenon India, noted the growing influence of AI in the sector, stating, “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, Senior Industry Executive, Pharma and Life Science at Microsoft, highlighted AI’s role in advancing healthcare. He said, “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 Artificial Intelligence (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.”
The report outlines several barriers slowing AI adoption within pharmaceutical organisations. Ethical concerns remain a central issue, particularly around algorithmic bias and transparency in AI decision-making. In pharmaceutical development, biases in AI models could lead to treatment protocols that favour certain demographic groups, compromising the aim of personalised medicine. Technical challenges, including data privacy, security concerns, and complex regulatory requirements, also hinder AI integration. The evolving regulatory landscape requires companies to adopt a strategic and informed approach. Operational barriers, such as a shortage of AI-skilled professionals and resistance to organisational change, further slow adoption. As AI automates routine tasks, professionals need to shift towards more strategic roles augmented by AI capabilities.
Despite these challenges, the report positions them as opportunities for organisations to strengthen their AI strategies. According to the findings, 75 per cent of CXOs in India’s life sciences sector have reported that AI adoption has led to cost reductions and improved customer satisfaction.
To support organisations in progressing through the AI maturity curve, the report outlines five critical pillars for successful integration. It recommends embedding AI-driven decision-making across all business operations through AI-first models. Enhancing the technology stack is necessary to enable large-scale AI deployment and foster innovation. Developing AI-ready data strategies is essential for ensuring security, regulatory compliance, and data accuracy. Preparing the workforce for AI integration through change management and interdisciplinary skill-building is also vital. Additionally, establishing strong risk and compliance frameworks ensures governance, transparency, and cybersecurity in AI usage.
The report details how AI is facilitating advancements across multiple areas in the life sciences sector. In pharmaceuticals and biotechnology, AI is expediting research and development by identifying drug targets, predicting molecular interactions, and enhancing toxicity assessments. Clinical trials are also evolving through AI-driven patient recruitment and trial planning, while manufacturing and supply chains benefit from predictive maintenance and improved production quality. In medical technology, AI is influencing device design by using real-world data and generative design methods. It is also enhancing predictive maintenance, reducing downtime, and extending product lifespans. Academic medical centres are leveraging AI to improve medical education through immersive, mixed-reality training, while also using data-driven research tools to automate literature reviews and optimise grant funding allocation.
The report concludes that AI adoption is not optional but a strategic necessity for the life sciences industry. Organisations must assess their current AI maturity level and develop structured roadmaps for integration to drive innovation, operational efficiency, and long-term growth.