Perform routine medical laboratory tests for the diagnosis, treatment, and prevention of disease. May work under the supervision of a medical technologist.
10-Year Growth
+1.7%
Annual Openings
22,600
Typical entry: Bachelor's degree
14 of 15 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Conduct blood tests for transfusion purposes and perform blood counts.
AI: Fully automatable - By 2025 many clinical laboratories use automated analyzers, robotic sample handling, and software for CBCs and transfusion testing that can perform these tests end-to-end under standard conditions.
Conduct chemical analyses of body fluids, such as blood or urine, using microscope or automatic analyzer to detect abnormalities or diseases and enter findings into computer.
AI: Fully automatable - Automated clinical analyzers and laboratory information systems already perform many chemical analyses of body fluids and automatically record results, enabling end‑to‑end automation in routine testing contexts.
Analyze the results of tests or experiments to ensure conformity to specifications, using special mechanical or electrical devices.
AI: Fully automatable - AI and control software can automatically analyze test data against specifications and flag nonconformance, and such QC/acceptance workflows are widely automatable with current devices and software.
Cut, stain, and mount tissue samples for examination by pathologists.
AI: Fully automatable - Histology workflows (microtomy, automated staining, and coverslipping) are widely automated and can be run end-to-end by instruments and control software in many labs by 2025.
Test raw materials, processes, or finished products to determine quality or quantity of materials or characteristics of a substance.
AI: Fully automatable - Quality control testing of materials and products is commonly automated with instrumentation, robotics, and AI/ML analysis pipelines that can fully perform routine testing workflows by 2025.
Analyze and record test data to issue reports that use charts, graphs, or narratives.
AI: Fully automatable - AI systems in 2025 can analyze laboratory data, generate charts/graphs and draft narrative reports automatically, though human oversight is often retained for clinical sign-off.
Inoculate fertilized eggs, broths, or other bacteriological media with organisms.
AI: Partial - Robotic liquid-handlers and automated plate inoculation systems can handle broths and many media, but delicate procedures like inoculating fertilized eggs and variable organism handling remain only partially automatable in practice by 2025.
Set up, maintain, calibrate, clean, and test sterility of medical laboratory equipment.
AI: Partial - Some calibration, cleaning protocols, and sterility testing are partially automated and supported by AI guidance, but comprehensive setup, maintenance and sterile technique still require human technicians.
Obtain specimens, cultivating, isolating, and identifying microorganisms for analysis.
AI: Partial - Automation and AI enable high-throughput culturing, isolation workflows, and identification (e.g., MALDI‑TOF, sequencing, image analysis), but obtaining some clinical specimens and handling nonstandard samples still require human intervention, so capability is partial.
Prepare standard volumetric solutions or reagents to be combined with samples, following standardized formulas or experimental procedures.
AI: Partial - Robotic liquid handlers and AI can prepare standard solutions and reagents in many settings, but routine reagent preparation often remains manual and requires human verification and oversight.
Examine cells stained with dye to locate abnormalities.
AI: Partial - AI image analysis can screen and flag stained cells and even detect many abnormalities, and some tools are approved as aids, but full autonomous diagnostic replacement of a human microscopist/pathologist is not yet general practice in 2025.
Perform medical research to further control or cure disease.
AI: Partial - AI can accelerate literature review, data analysis, hypothesis generation, and in silico modeling, but cannot fully carry out the creative, wet‑lab experimental design and execution responsibilities required for autonomous medical research in 2025.
Collect blood or tissue samples from patients, observing principles of asepsis to obtain blood sample.
AI: Partial - As of 2025, automated guidance and robotic venipuncture systems exist but are not widely reliable or accepted enough to fully replace a trained phlebotomist performing aseptic sample collection, so AI can only partially perform this task.
Supervise or instruct other technicians or laboratory assistants.
AI: Partial - AI can generate training materials, monitor performance, and provide supervisory recommendations, but cannot fully assume human managerial, legal, and interpersonal responsibilities for supervising staff as of 2025.
Consult with a pathologist to determine a final diagnosis when abnormal cells are found.
AI: Not automatable - Consulting with a pathologist to reach a final diagnosis requires human clinical judgment, responsibility, and interactive professional communication that AI cannot legitimately perform on its own as of 2025.