Abstract Study question Can integration of a robotic system for semen analysis reduce operational failure modes and eliminate risk in the IVF laboratory? Summary answer A robotic system for semen analysis reduces operational failure modes and eliminates severe risks including those associated with reduced patient experience and increased patient stress. What is known already Recently, the ever-evolving field of IVF has experienced a rise in innovations to boost laboratory performance. Considering the lack of robust evidence in some of them, decisions on implementation are often based on opinion and product cost. Currently, an approach to assess risk, time and effectiveness has not been fully described. IVF is not error-free (Sakkas et al., 2018), hence all new technology coming into the laboratory ought to reduce risk of errors happening. Study design, size, duration Failure mode effects analysis (FMEA) was carried out on the workflow integration into an IVF centre (>500 cycles per annum) to evaluate the possible procedural risks of manual semen analysis compared to a digitalised pathway. Possible sources of error were identified, and the Risk Priority Number (RPN), a product of likelihood, severity and detection of incidence was associated with each risk, as previously described by Rienzi et al., 2015. Participants/materials, setting, methods Using a systematic decision-making approach to quantify the value of incorporating the use of a robotic system (Mojo AISA) for semen analysis. Main results and the role of chance Five process phases were identified for conventional specimen analysis. There were eight associated process steps and 29 failure modes, among which 13 risks were given a moderate (RPN 15-50, i.e. data entry errors, incorrect count and sperm classification) and three were severe RPNs (RPN>50), resulting in reduction in efficacy of treatment. Protocol using the robotic system resulted in a reduction of process phases to four and failure modes to 16, with four moderate and none severe RPNs. Implementation of the robotic system improved workflow by optimising time in motion for the IVF specialist and further reducing active time by at least 30%. Limitations, reasons for caution FMEA is a proactive method to identify potential incidents and help to develop strategies to mitigate risks. Ultimately, this forms part of a scheme for responsible development. The likelihood of incidences and time analysis were estimated based on clinical experience. Risks inherent to sample handling remained present. Wider implications of the findings The robotic system has the potential to eliminate risks that exist when manually inputting data to electronic medical records, whilst offering support to IVF specialists. Trial registration number not applicable