Save Full Article Here | Written By: Dr. Helen V. Bennett, Director of Scientific Strategy at PAA
Recent industry discussions at SLAS, Society for Laboratory Automation and Screening, underscored a defining shift in laboratory automation strategy. While no single technology dominated the conversation, a clear priority emerged: laboratories are increasingly seeking cohesive, end-to-end automation solutions rather than managing complex multi-vendor integrations.
Today’s labs have more options than ever. Instruments, consumables and software platforms can technically be integrated across multiple suppliers. But as laboratories scale operations, many are finding that integration designs do not always translate into seamless performance in practice. Third-party connections can introduce feature limitations, fragmented troubleshooting, and additional validation overhead, particularly in regulated or high-throughput settings.
In contrast, more unified automation ecosystems where hardware, software and workflow control are designed to operate together, tend to deliver smoother performance, more robust error handling and simplified service support. Scaling becomes more predictable, and operational complexity is reduced.
As a result, the conversation has shifted beyond individual instruments or software capabilities. The focus now is on customer experience, scalability and workflow cohesion, building automation infrastructures that minimize manual intervention, simplify expansion and improve the speed and accuracy of troubleshooting.
This evolving mindset sets the stage for a new era in laboratory automation: one defined not by isolated components or fragmented integrations, but by strategically designed ecosystems built to scale with science.
Laboratory Automation in 2026: From Advantage To Absolute Necessity
Laboratory automation has crossed a critical threshold. What was once a differentiator is now a baseline requirement for laboratories seeking speed, scalability, compliance and scientific resilience.
Across biopharma, diagnostics and analytical sciences, automation is evolving from isolated task execution to fully integrated, digitally orchestrated laboratory ecosystems.
A rapidly expanding market
The global laboratory automation market continues strong, sustained growth:
- The market is valued at approximately USD 7–9 billion in 2026 and is forecast to reach USD 15–18 billion by the early 2030s.
- Reported growth rates range from ~6.5 % to over 9 % CAGR, driven by demand for high-throughput workflows, AI-enabled systems and scalable automation architectures.
- Software-led automation, including orchestration platforms, workflow engines and digital integration layers, is one of the fastest-growing segments, outpacing hardware alone.
This growth reflects a structural shift: automation is no longer about doing tasks faster, but about enabling science to scale reliably.
What laboratories are automating today
Modern laboratories are automating entire workflows, not just individual steps, particularly in high-volume, data-intensive applications where speed, consistency and traceability are critical.
High-throughput screening (HTS)
Automation underpins compound screening, target validation and assay development, with robotic liquid handling, plate movement, incubation and detection integrated into continuous, unattended workflows. Orchestrated HTS platforms enable rapid scaling from pilot studies to large screening campaigns while maintaining reproducibility.
Stem cell and cell-based screening
Highly sensitive, multi-step workflows such as stem cell culture, differentiation, feeding, passaging and phenotypic screening are increasingly automated. Precision liquid handling, environmental control and scheduling software reduce variability and support long-running, complex experimental timelines.
Next-generation sequencing (NGS) sample preparation
Automation now routinely covers DNA/RNA extraction, normalization, library preparation, indexing and QC. Modular automation platforms allow labs to adapt workflows across different kits and protocols while orchestration software ensures traceability, error reduction and compliance across high sample volumes.
Immunoassays and ELISA workflows
End-to-end ELISA automation, from sample dilution and reagent addition to washing, detection and data capture, improves throughput, reduces hands-on time and delivers consistent, audit-ready results in regulated and research environments.
Sample handling and logistics
Automated labelling, storage, retrieval and robotic transport between instruments minimize manual intervention and support continuous workflow execution across multi-instrument laboratories.
Integrated analytical pipelines
Robotics link directly with chromatography, spectroscopy, high content imagers and other analytical platforms, enabling automated sample preparation, analysis and result consolidation within unified digital workflows.
End-to-end digital orchestration
Centralised orchestration software coordinates instruments, robots, assays and data systems, managing scheduling, exception handling, data capture and compliance logging across complex, multi-application environments.
Together, these applications demonstrate how laboratory automation has evolved into connected, application-driven ecosystems, capable of supporting diverse scientific workflows at scale, from discovery through development and quality control.
Hot Topics Defining Laboratory Automation
Intelligent automation
AI and machine learning are embedded into automation platforms, enabling adaptive workflows that learn, optimize and predict, transforming automation from rule-based execution into intelligent scientific infrastructure.
Modular, scalable systems
Labs are moving away from rigid, monolithic automation. Demand is growing for modular platforms that can be deployed incrementally, reconfigured as workflows change and scaled without disruption.
Open, connected ecosystems
Interoperability is now essential. Modern automation platforms must integrate seamlessly with existing instruments, LIMS/ELN systems and enterprise data environments, eliminating automation silos.
Sustainability and efficiency
Automation is increasingly linked to sustainability goals, reducing reagent waste, energy consumption and rework while improving overall operational efficiency.
A transformed workforce
Automation is reshaping, not replacing, scientific roles, freeing researchers from repetitive tasks and enabling greater focus on insight, innovation and experimental design.
Why Modular Automation And Orchestration Is Important
As laboratories scale in complexity, orchestration becomes the differentiator. Hardware alone is no longer sufficient.
Modular, scalable automation platforms, likes those offered by PAA, combined with powerful orchestration software and deep workflow automation expertise, enable laboratories to:
- Build automation progressively, aligned to real scientific needs
- Integrate diverse instruments into cohesive, audit-ready workflows
- Adapt rapidly to new assays, methods and regulatory demands
- Future-proof laboratory operations in a fast-evolving market
The Bottom Line
In 2026, laboratory automation is not about owning robots, it’s about owning the workflow. Organizations that invest in modular, orchestrated and intelligent automation today are building the foundation for faster science, better data and sustainable growth tomorrow.
Let’s innovate together — partner with PAA to elevate your science!
Sources: Automation Magazine (2026 Robotics Trends); Genetic Engineering & Biotechnology News (Biopharma Digitalisation & Intelligent Automation); Pharma Focus Europe (Next-Generation Laboratory Automation Technologies); Chromatography Online (Automation & Digitalisation in Analytical Laboratories); Mordor Intelligence, Grand View Research and MarketsandMarkets (Global Laboratory Automation Market Analysis & Forecasts); Society for Laboratory Automation and Screening (SLAS); Nature Methods / Nature Reviews Drug Discovery.