Laboratory automation can range from adding an autosampler to creating a facility that operates with little human intervention. This wide spectrum makes it difficult for laboratories to determine how much automation they need and where it will produce the greatest return.
During a discussion at ASMS 2026, Agilent leaders explore the gap between what automation can achieve and what laboratories can implement.
Working Within Existing Laboratories
Many laboratories want to automate more processes but operate in facilities that were not designed for robotics, connected instruments, or automated sample movement. Limited space, aging equipment, incompatible systems, and gaps in staff expertise can all slow adoption.
“Today’s biggest implementation gap involves automation,” explains Warren Potts, Vice President and General Manager Gas Phase Division at Agilent Technologies. “Many laboratories want to move forward, but their infrastructure, the age of their facilities, and their understanding of automation can limit what they can achieve.”
Large-scale projects can demand substantial capital and several years of planning. Some organizations have built separate facilities because their existing laboratories could not accommodate the desired technology.
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Full automation does not suit every laboratory, however. “Automation covers everything from adding an autosampler to operating a fully autonomous laboratory,” notes Potts. “Laboratories need to determine what will work best for their circumstances. Otherwise, they risk investing in technology that does not deliver the expected value.”
The appropriate level depends on sample volumes, location, staffing, turnaround requirements, and the laboratory’s business model. For instance, a high-throughput contract laboratory may benefit from extensive automation. In contrast, Geoff Winkett, General Manager/Vice President Spectroscopy and Vacuum Division at Agilent Technologies, offers the example of a remote mining laboratory that may gain more from automating just a few targeted steps.
Online analysis and closed-loop control could extend automation beyond the laboratory by connecting measurements with manufacturing or processing systems. This approach could reduce the delay between collecting a sample and acting on the result.
“Online analysis and closed-loop control are areas where the technology has moved ahead of implementation,” observes Iris Mangelschots, Vice President and General Manager, Liquid Phase Division at Agilent Technologies. Wider adoption will require organizations to connect analytical instruments with data platforms, validated methods, and process controls.
Establishing a Practical Role for AI
AI could help laboratories analyze data, develop methods, predict problems, and manage routine operations. Contract laboratories may see particular value because faster analysis and reporting can increase sample capacity while reducing the cost per result.
Customers are still determining which models suit their operations and how much they should invest, according to Winkett. “Laboratories are taking different approaches to AI, but it has clear potential to change how they analyze data and manage their operations.”
Trust remains a central concern. “Supervised AI will remain important for some time,” predicts Mangelschots. “Laboratories need guardrails and validation to ensure the results are accurate and trustworthy.”
AI performance also depends on the information supporting it. “Data quality matters more than data quantity,” Mangelschots adds. “Training a model with the right data will produce a stronger output.”
The risk of overreliance also warrants attention. If scientists defer too readily to AI-generated methods or conclusions, they may weaken the critical thinking that drives innovation. Human oversight should extend beyond checking whether an output is correct. Scientists must also understand the assumptions and data behind it.
Automation succeeds when it addresses a defined laboratory problem. By matching investment to operational needs, laboratories can improve throughput and consistency without pursuing a level of automation their facilities cannot support.
