My job revolves around numbers. Cycle counts, pregnancy rates, turnaround times, revenue per treatment. Numbers are honest, comparable, and they fit neatly into dashboards. And since artificial intelligence has arrived in almost every corner of our working lives, we get those numbers faster, in finer detail, and in real time.
And yet, in many conversations over recent months, something has been missing. Not the number. The person behind it.
This is not a product article. It is an attempt, as the CEO of a company that builds software for fertility clinics, to say something uncomfortable out loud: in reproductive medicine, we have learned to measure almost everything. How the people who produce those results every day are actually doing is something we rarely measure. And when we do, we look too late.
Faster, Better, More. And Who Actually Does It?
Expectations placed on fertility clinics have grown in recent years. Patients compare success rates online before booking a first appointment. Owners and investors expect growth. Regulators demand seamless documentation. And AI promises to accelerate all of it at once: embryo assessment, scheduling, billing, reporting.
I believe most of this is right and important. Anyone working in reproductive medicine carries responsibility for one of the most vulnerable moments in another person's life. Nothing may be lost, mixed up, or left undone. Efficiency here is not an end in itself. It is patient safety.
But I am watching a shift. The question "How do we handle more cycles?" is asked almost every time. The question "How is the embryologist who performs them doing?" almost never. Yet the second question is the precondition for the first.
A fertility clinic is not a machine you speed up by raising the clock rate. It is a team of highly specialized people: embryologists, nurses, physicians, patient coordinators, billing staff. Every one of these roles is hard to fill and even harder to replace. When an experienced embryologist leaves, a clinic does not lose a position. It loses years of experience, well-rehearsed routines, and often trust within the team.
AI will not replace these people. But it can do two very different things with them: it can give them time back. Or it can keep raising the pace until the time saved disappears straight into more volume. Which of the two happens is not decided by technology. It is decided by leadership.
What 3,011 Reviews Reveal About Our Industry
That this is more than a gut feeling is shown by a recent analysis. Fertility Bridge published an analysis by Q Engage that examined 3,011 public employee reviews on Glassdoor and Indeed across 122 U.S. fertility practices, covering September 2010 through June 2026. The article is worth reading: Sharply Divided: Fertility Employees' Satisfaction Drops .75 in 7 Years.
The key figures that gave me pause:
- The sector-wide average employer rating fell from 3.52 stars in 2018 to 2.73 stars in 2025, the lowest point in the entire period analyzed, after four consecutive years of decline.
- 41.6 percent of employees give their employer only one or two stars. 27.2 percent of all reviews are one-star reviews.
- Management is cited in 61.5 percent of negative reviews, more often than pay, hours, and benefits combined.
- Leadership rates the same workplace 0.84 stars higher on average than frontline teams do.
- Embryology, nursing, and patient coordination sit at or below the sector average. Finance and billing teams score lowest of all.
For me, the last figure but one is the most important. A 0.84-star gap means the people responsible for the working atmosphere see a different organization than the people working in it. Not out of ill will. But because the signals that reach them are numbers. Cycles, rates, revenue. And none of those numbers shows how the people behind them are actually doing.
These are U.S. data, from a different healthcare system and a different market structure. I would not transfer them one-to-one to Europe. But I recognize the mechanics behind them from many conversations with clinics across the German-speaking region: staff shortages, growing documentation requirements, rising throughput, and a team that carries all of it until it no longer can.
What This Means for Us
I am deliberately not writing this as a software vendor who wants to sell a solution. Software does not fix a leadership problem. When a team is burned out, no new module will help.
Still, as a manufacturer we carry responsibility at one very concrete point: the tools that embryologists, nurses, and coordinators work with for eight hours every day shape how those eight hours feel. A system that demands double entry, scatters findings across three different programs, and costs sleepless nights before every audit is not neutral. It is a stress factor that is never named in a review, yet resonates in many of them.
That is why, at MedITEX, we have for some time been asking ourselves a different guiding question than before. Not only: what more can the software do? But: what less does the team have to do because of it? Less searching, because laboratory, clinic, and administration work in one system. Less retyping, because devices and practice systems are connected directly. Less uncertainty, because electronic witnessing prevents mix-ups instead of documenting them afterwards. Fewer weekends before the audit, because quality management and registry exports run alongside daily work.
And when we talk about AI in MedITEX, we apply exactly this yardstick: does it give the team time back, or does it merely raise the pace? We want the first. Whether we achieve it is not for us to judge, but for the people who work with it. That is why we listen to them, in support, at our annual user meeting, in every project. One recent example: more and more clinics in the German-speaking region asked our support team for a simpler way to handle billing with statutory health insurers. That request went straight to development, and we have now built it.
A request to everyone who runs a clinic: read the article. Then ask not your dashboard but your team how they are doing. The answer will not show up in any KPI. But it will decide whether the KPIs still hold next year.
