Life sciences AI: Four impacts on real estate and facilities

As AI continues to facilitate scientific breakthroughs and foster creativity and collaboration among scientists, life sciences organizations must also consider new opportunities for physical spaces where therapies are discovered. Location selection, portfolio strategy, workplace design and sustainability are four focus areas directly impacted by life sciences AI advancements.

Travis McCready, Head of Life Sciences, Americas Markets at JLL and Amber Schiada, Head of Industries Research at JLL were joined by Anup Kharode, Partner, Global R&D and Clinical Transformation at PwC on a recent webinar to discuss the many ways AI is transforming the life sciences industry. For real estate and facilities, this AI evolution means opportunities for adaptive approaches to the talent landscape, location strategy and physical infrastructure. The insights are valuable to the goals of not only life sciences real estate leads, but also operations, facilities, finance, human resources, lab and scientific stakeholders as well.

The talent conundrum: Fueling AI-driven growth

AI's influence begins with the foundation of any industry: its people. Identifying and nurturing the right talent is critical as companies strive to integrate AI into their operations. As the CEO of Moderna shared, "If we had to do it the old biopharmaceutical ways, we might need a hundred thousand people today," illustrating AI's ability to amplify the productivity of thousands of people tenfold.

The importance of aligning real estate decisions with talent acquisition strategies cannot be emphasized enough. Traditional scientific hubs like Boston and the Bay Area continue to dominate due to dense concentrations of skilled scientists. Yet, emerging markets driven by computational biologists and chemists, such as Bloomington, Indiana with its robust bioinformatics programs, showcase new opportunities for growth and evolving criteria for site selection.

With the convergence of technology and science and implementation of AI, looking at markets with dense concentrations of computational biology and computational science degrees will become more and more relevant. The data science centers of excellence are evolving into the life sciences centers of excellence for tomorrow.

Reimagining places: The shift in real estate footprint

As the integration of AI into the scientific process redefines how life sciences companies approach their real estate portfolios, the site search process is increasing in complexity. AI demands not only traditional infrastructure but also advanced computing power and data center capabilities. This change necessitates a rethinking of proximity and the relationship between R&D facilities and their supporting technological infrastructure.

There is an opportunity to get ahead of data center needs early by considering how to layer technological requirements into portfolio planning. For instance, companies no longer need to co-locate large wet labs; instead, they can leverage modular, scalable spaces augmented by AI and automation. This transformation opens opportunities for new geographical markets, reducing dependency on established hubs and expanding footprints into regions rich in emerging talent.

Sustainability and automation: Enhancing facility design

As scientific innovation and talent adapt to new enabling technologies, the design of life sciences spaces must adapt as well. Automated systems and AI-powered predictive maintenance can improve energy use and operational efficiency. "Implementing AI in workplace programming and building management systems," says Amber Schiada, "offers tangible benefits, from reduced carbon footprints to operational savings."

Whether it’s access to natural light, amenities or equipment needs, successful life sciences spaces should be modernized and adaptable to ever-evolving AI tools and technologies.

Particularly in manufacturing, AI's role in continuous and self-contained processes could drastically reduce the scale of traditional scientific manufacturing facilities needed. This shift may mean less space, but more smartly designed environments, optimizing power, water and resource management infrastructures.

Insights from other sectors

The life sciences sector can glean valuable lessons from other AI-integrated industries like healthcare and finance. The banking sector has always been a leader in leveraging computational technology to advance the industry. Similarly, healthcare's move towards personalized medicine, driven by AI, aligns closely with the goal of the life sciences industry to get therapies to patients, faster. Both sectors illustrate the importance of agile, adaptive real estate strategies and the opportunity to bring lessons to the life sciences R&D space.

Evolving, not obsolete

Artificial intelligence does not render life sciences real estate obsolete; rather, it catalyzes its evolution. Real estate remains crucial, supporting an industry's shifting needs by providing adaptive, resource-efficient spaces that attract top talent and enable cutting-edge research. Focusing on talent, leveraging technology and prioritizing sustainability ensures that life sciences companies remain at the forefront of innovation.

In this dynamic landscape, making strategic location decisions and building an agile workplace that adapts to talent and technological needs is crucial. Life sciences real estate must evolve to accommodate the future needs of AI-enhanced operations, paving the way for unprecedented growth and innovation.

Ready to discuss new opportunities for physical spaces where therapies are discovered? Reach out to set up a meeting.