How AI Will Change the Demand for Lab Space

Artificial intelligence is having a profound impact on many industries from journalism to finance to research and design. We can also add life sciences to that list, according to participants in a virtual forum that CBRE hosted, with the general consensus being that AI’s impact will generate more automated systems in labs than in the past. With less human touch will come more efficiency and efficacy – and likely less human-caused mistakes.  

This conclusion inevitably leads to questions on what roles people will take on and the space they’ll need as robotic systems take over tasks they can perform. Here too, the participants offered some thoughts.

First, the human touch remains critical for creativity and innovation, and with more automation in the lab, humans will have more time for those pursuits.

Second, there will be more personalized medicine product volume.

Third, the amount of space needed is expected to increase when robotic systems are involved.

This trend is already apparent even without a large AI presence in the lab. A number of organizations are looking to add to their lab space, with ratios shifting to 70% lab and 30% office space or even more and maybe up to nine times greater. As offices shift to greater flexibility, this could be reflected in this sector, too, with empty spaces for remote admin teams to work and amenities added to retain talent. Furthermore, dedicated areas will remain necessary for specialized equipment in controlled environments.

There’s no definitive answer regarding the effect of AI and automation on whether most labs will be centralized or decentralized. Instead, it’s projected to be an equal division, according to the live polling during the virtual meeting and tasks handled. To date, most innovation happens in small groups. AI may make lab innovation and the data engines to fuel it more accessible to smaller groups and drive greater decentralization in the early stages. At the same time, automation may drive centralization of the development and regulatory approval phases of products.

When it comes to automation, data from the live poll indicates that this phenomenon will make labs more centralized. The cost of automated machines requires specialized, sophisticated talent to keep the automated machines running. The bottom line could be a hybrid future that balances centralized, specialized sites and decentralized standard workflows.

But will AI and automation meet the needs of organizations striving to increase the quality of science for less money and in a quicker timetable? AI may create greater accessibility to strong problem-solving tools among individuals, particularly entrepreneurs, and in small groups. And it may put the power of big data in the hands of smaller teams who may work and live where they choose versus where the company picks. Automation is expected to decentralize standard testing workflows and commodity capabilities with flexibility in locations for routine processes based on demand. However, specialized research and complex processes such as niche equipment or high security needs will remain largely centralized in main hub locations.

AI will respond to more future automation over the next decade with a rise of it in labs and integrated technologies such as more AI, MI, robotics and IoT (Internet of Things), all based on successful pilot programs that have found greater productivity and cost effectiveness.  For example, between 60% and 80% of current routine processes such as sample intakes and barcode scanning are ready for increased automation, thanks to robotics.  Processes, too, such as workflow coordination are expected to become highly automated using sensors, connectivity and algorithms. A fully automated lab may not be right around the corner or in the next space, but it is set over time to transform workflows, productivity, skill profiles and the overall footprint of most standard lab processes.