Towards Healthcare
AI in Lab Automation Market Trends and Regional Growth Factors

AI in Lab Automation Market Data-Driven Decision-Making in R&D

The AI in lab automation market is growing due to the increasing demand for high-throughput testing and improved accuracy in diagnostics. Additionally, AI enhances efficiency by automating repetitive tasks and enabling faster data analysis. 

  • Insight Code: 5743
  • No. of Pages: 150+
  • Format: PDF/PPT/Excel
  • Published: June 2025
  • Report Covered: [Revenue + Volume]
  • Historical Year: 2021-2022
  • Base Year: 2023
  • Estimated Years: 2024-2033

About The Author

Deepa Pandey is a focused and detail-oriented market research professional with growing expertise in the healthcare sector, delivering high-quality insights across therapeutic areas, diagnostics, biotechnology, and healthcare services.

She began her research career at Precedence Research, where she contributed to a wide range of healthcare industry studies, helping build a strong foundation in market intelligence and strategic research. Currently, Deepa plays a critical role at Towards Healthcare, while also extending her research capabilities across Statifacts, supporting cross-industry intelligence initiatives with a focus on healthcare.

Her ability to distill complexity into clarity has made her a trusted contributor to both internal teams and external clients across the healthcare value chain. By combining professionalism with an evolving depth in healthcare research, Deepa consistently adds value to projects that demand critical thinking, market precision, and industry-specific knowledge. Her contributions help organizations navigate the complexities of regulated markets and make data-backed growth decisions.

FAQ's

AI in Lab Automation is booming as labs adopt smart tech to boost accuracy, speed, and efficiency from 2024 to 2034.

North America is currently leading the AI in lab automation market due to advanced healthcare infrastructure.

The AI in lab automation market includes 5 segments: by process type, by application, by automation type, by end-user, and by region.

Some key players include Thermo Fisher Scientific, Danaher, PerkinElmer, Siemens Healthineers, and Agilent Technologies.

AI helps automate repetitive tasks, enhances data interpretation, predicts experimental outcomes, and reduces errors, allowing researchers to focus on critical decision-making and innovation.

Major challenges include high initial costs, data security concerns, the need for skilled professionals, and integration with legacy systems.

Key trends include the due to the increasing demand for high-throughput testing and improved accuracy in diagnostics.