KPMG's extensive research into AI use across eight industries, finds that unlike sectors still experimenting or struggling to scale the tech, life sciences organisations 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 organisations to fully realise 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 organisations can take a value-based approach to AI that helps to accelerate innovation, unlock new growth opportunities, and maximise the impact of their AI investments.
Reimagining life sciences
Key insights
- Sector insights
- Measuring ROI
- Value creation
- Quotes
A sector out front
92%
state their organisations are clear on which AI technologies and capabilities should be invested in.
97%
report having achieved operational improvements through the adoption of AI.
69%
have a clear strategic vision of the role AI will play over the next five years.
ROI on AI initiatives in life sciences
31%
of leaders report a high/very high ROI, while 51% report a moderate ROI, and
18% report a negative/even/low ROI.
Measuring ROI
Measuring their AI ROI is a top adoption challenge for leaders in life sciences.
68%
report significant stakeholder pressure to prove the ROI of AI.
Operating model adaptability is key to driving AI-enabled value creation
x 2
organisations 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.
29%
functional and agile models.
12%
functional or matrix models.
Realising value from your AI transformation journey
In addition to providing robust research, the Intelligent Life Sciences report also shares actionable insights into how organisations can take a value-based approach to AI that helps them to accelerate innovation, unlock new growth opportunities, and maximise the impact of their AI investments.
Through this report, we introduce the three phases of AI value — a framework that can help those in life sciences to enable their teams, embed AI into workflows, and evolve their organisations into AI-powered, ecosystem-driven enterprises.
Click on each of the phases to find out more.
Enable
The Enable phase focuses on enabling people and building AI foundations. Organisations 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 customisation.
Embed
The Embed phase integrates AI into workflows, products, services, value streams, robotics, and wearables, delivering greater value. A senior leader drives 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 modernisation, while enterprise-wide data enhances operations.
Evolve
The Evolve phase evolves business models and ecosystems, using AI and frontier technologies like quantum computing and blockchain to solve large sector-wide challenges. AI orchestrates seamless value across enterprises and partners. Emphasising ethics and trust with real-time security, this phase uplifts human potential with broad and deep workforce training, fostering a creative, innovative and value-driven future.
Get in touch
- Tim Plenderleith
- Georgie Aley
