AI is reshaping both scientific innovation and business operations in life sciences
KPMG's extensive research into AI use across eight industries, finds that unlike sectors still experimenting or struggling to scale the tech, life sciences organizations have embedded AI deeply into their operations — from R&D and clinical trials to supply chains and commercial functions. For many, AI is not just a tool, but a core part of how they work.
The challenge is no longer whether AI can deliver value, but how companies can reshape their organizations to fully realize its potential. The Intelligent life sciences report explores how leading life sciences firms are making this transition — adapting their operating models, breaking down silos, and fostering AI-driven agility. This report also offers actionable insights into how organizations can take a value-based approach to AI that helps to accelerate innovation, unlock new growth opportunities, and maximize the impact of their AI investments.
Life Sciences companies have emerged as advanced adopters of AI, embedding it across R&D, clinical trials, and commercial operations. Yet despite clear momentum, generating consistently high returns on AI investments remains a challenge. Data fragmentation—silos, inconsistent formats, and privacy constraints—continues to be a critical barrier. This report explores how leading firms are bridging the AI value gap, adapting operating models, and taking a value-based, scalable approach to AI that delivers measurable outcomes.
At-a-glance insights:
A sector out front
92% state their organizations are clear on which AI technologies and capabilities should be invested in
69% have a clear strategic vision of the role AI will play over the next five years
97% report having achieved operational improvements through the adoption of AI
Respondents also say that AI is also having a high degree of impact in:
- Supply chain and logistics
- IT
- R&D
Despite promising results proving value of the tech remains elusive
ROI on AI initiatives in life sciences
Operating model adaptability key to driving AI-enabled value creation
The KPMG research finds that organizations who use a combination of functional and agile models are twice as likely to achieve high ROI compared to those with traditional functional or matrix-based structures.
How can life sciences companies help to ensure that AI serves as a catalyst for meaningful transformation?
In addition to providing robust research, the Intelligent life sciences report also shares actionable insights into how organizations can take a value-based approach to AI that helps them to accelerate innovation, unlock new growth opportunities, and maximize the impact of their AI investments.
Through this report, we introduce the three phases of AI value — A framework that can help life sciences organizations to enable their teams, embed AI into workflows, and evolve their organizations into AI-powered, ecosystem-driven enterprises.
Enable
The Enable phase builds AI foundations. Organizations appoint a responsible executive, create an AI strategy, identify high-value use cases, boost AI literacy, align with regulations and establish ethical guardrails. AI pilots are launched across functions, while cloud platforms and pre-trained models are leveraged with minimal customization.
Embed
The Embed phase integrates AI into workflows, products, services, value streams, robotics and wearables, helping to deliver greater value. Senior leaders drive enterprise-wide workforce redesign, re-skilling and change, embedding AI into operating models with a focus on ethics, trust and security. AI agents and diverse models are deployed, supported by cloud and legacy tech modernization, while enterprise-wide data enhances operations.
Evolve
The Evolve phase elevates business models and ecosystems, using AI and frontier technologies like agentic and blockchain to solve sector-wide challenges. AI orchestrates seamless value creation across enterprises and partners. Emphasizing ethics and trust with real-time security, this phase uplifts human potential. AI is embedded in the culture of the organization. The workforce, upskilled with deep training, fosters a creative, innovative and value-driven future.
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