By Gabriella Ryan, M.S. Senior Application Scientist, Omni International (a Revvity company)
If you work anywhere near diagnostic microbiology and infectious diseases right now, you don’t need a market report to tell you what 2026 feels like.
You’ve got a post-pandemic baseline of respiratory testing that never really went back to “normal,” a steady stream of STIs and hospital-acquired infections, sepsis pathways built around hours not days, and a public health system that suddenly cares about wastewater and surveillance again. Meanwhile, the infectious disease IVD market keeps creeping upward toward the mid-20s billions in annual revenue, even with COVID testing dialed down.
On paper, that looks like growth.
On the bench, it feels like volume, complexity, and pressure.
And the uncomfortable reality is this: the labs that will cope best are not necessarily the ones with the flashiest panels or newest sequencer. They’re the ones that got serious about automation at the front end—accessioning, specimen processing, sample prep—before all this landed on them.
Let’s walk through where diagnostic microbiology and infectious diseases actually sits in 2026, and why front-end sample prep automation is starting to look less like a nice-to-have and more like a survival mechanism.
The “COVID era” didn’t really end. It just stopped being a single-topic show.
Respiratory testing now lives in a world where SARS-CoV-2 is one line item next to influenza, RSV, atypical pathogens, and whatever else is circulating this season. Multiplex respiratory panels are no longer exotic—they’re baked into many hospital and critical-care workflows.
On top of that, you’ve got:
Every one of those trends translates, in the lab, into more tests per patient, broader panels per workup, and higher expectations for turnaround time. The infectious disease diagnostics market growing into the mid-$20B range by 2026 isn’t an abstraction—it’s your daily workload getting denser.
The toolbox for diagnostic microbiology and infectious diseases in 2026 is the most powerful it’s ever been—and easily the most demanding.
Culture isn’t going away; it’s now sitting next to:
It’s an impressive tower of technology. The catch is that every layer assumes something very basic:
The sample that shows up at its input is correctly identified, properly processed, and reasonably clean.
That assumption is exactly where many labs are weakest.
On the operations side, we’re not exactly overstaffed heroes.
Multiple reports and commentaries point to an ongoing shortage of laboratory professionals, including microbiologists, driven by burnout, demographics, and a thin pipeline of new graduates.
Labs centralize to handle regional testing volumes, which looks great on a slide deck but in practice means fewer sites doing more work around the clock.
At the same time, infectious disease diagnostics isn’t becoming simpler. It’s:
So you’ve got a workload defined by volume and complexity, landing on teams that are, at best, flat in headcount and, at worst, chronically short. Automation in clinical labs is being pitched—correctly—as one of the only realistic ways to reconcile staffing, budget, and demand.
But when people say “lab automation,” they usually picture tracks, analyzers, and digital plate readers.
The painful truth? A lot of labs have automated the shiny parts and left the front end almost entirely manual.
Every infectious disease sample has a life before it touches a panel or a plate.
It’s collected, labeled, transported, accessioned, sorted, possibly aliquoted, sometimes homogenized or diluted or “cleaned up,” then finally handed off to an analyzer or culture workflow. Each of those steps is a chance to introduce variability, error, or delay.
We have the scars to prove it:
When you’re dealing with a handful of samples, skilled techs can muscle through this. When you’re dealing with hundreds or thousands, at high consequence, this pre-analytical chaos is exactly what overwhelms the lab.
You can have the best syndromic panel in the world. If the sample feeding it is poorly processed, your “cutting-edge” test just turned into an expensive coin flip.
When we talk about “front-end automation” in diagnostic microbiology and infectious diseases, we’re not talking about a single magic machine. We’re talking about a set of moves that standardize and de-risk the earliest phases of the workflow.
That often includes:
None of this removes the need for expertise. What it does is remove the need for experts to spend their day opening tubes, wrestling viscous samples, and repeating the same physical actions hundreds of times.
In a world where experienced microbiologists are in short supply, that trade is not optional. It’s the only way some labs will stay viable.
It’s easiest to see the impact if you imagine two different versions of the same year.
In the first lab, everything front-end is manual. Respiratory season hits hard. Syndromic panels are firing all day, blood cultures are popping positive, and the phone never stops ringing. Techs are accessioning, de-capping, aliquoting, and pre-processing everything by hand or relying on lysis buffer + enzymes and heated incubations to do the heavy lifting—stool, sputum, NP swabs, BALs, tissues—before anything ever gets near an instrument. Every sick day or vacancy translates directly into backlogs. Every subtle variation in prep shows up later as odd results, repeat testing, and fights over what to trust.
In the second lab, the panels and analyzers are the same. The difference is that, for high-volume workflows, the first half hour of a sample’s life looks different. Specimens hit an automated processor that barcodes, sorts, and inoculates. Complex matrices are loaded into high-power homogenization systems that standardize homogenization, lysis, and, most importantly, process every sample the same way. The techs are still there—but they’re supervising and troubleshooting, not physically touching every single sample.
Both labs are slammed. Both are dealing with the same respiratory surge, the same sepsis alerts, the same AMR reality. But one is spending most of its energy putting out fires that started at the front end. The other is pushing more of its people’s time into interpretation, stewardship, method development, and the kind of work that actually moves patient care forward.
Multiply that difference across an entire year, and you’ve essentially created two separate tiers of capability.
There’s a lot of excitement around AI in clinical microbiology—image analysis for plates, smear interpretation, blood parasite detection, resistance prediction, and outbreak surveillance.
Those tools are genuinely promising. They can absolutely extend what a short-staffed team can do and improve consistency in interpretation.
But there’s a catch that doesn’t get talked about enough:
AI amplifies whatever you feed it.
If your front end is chaotic—variable sample quality, inconsistent processing, unreliable metadata—AI will happily systematize that chaos. You’ll get beautifully organized nonsense. On the other hand, if your pre-analytical and sample prep steps are standardized and traceable, AI becomes a force multiplier instead of a very fancy error generator.
That’s another way of saying: buying “AI for microbiology” without shoring up your front end is like putting a racing engine in a car with bald tires and no brakes. Impressive specs, terrible actual performance.
Put bluntly: busy.
The infectious disease diagnostics market is growing, but the growth is subtle and sustained rather than crisis-spiky, which means this pressure isn’t going away next quarter. Automation in microbiology and lab medicine is maturing fast; manufacturers are pouring resources into integrated systems because they can see the same staffing and demand curves you can.
For labs, the choice isn’t “do we want automation?” It’s where they put it first.
If all the investment goes into back-end shine—new panels, new analyzers, clever AI—but the front end stays manual, the lab will stay stuck in the same pattern: constantly working at the edge of capacity, vulnerable to every vacancy and every surge, bleeding time and money on pre-analytical fixes and repeat tests.
Labs that bite the bullet and automate at the front end—accessioning, specimen processing, and sample prep, including messy things like homogenization for complex matrices—will still be busy. They’ll still have staffing headaches, they’ll still be asked to do too much with too little.
But they’ll be a step ahead:
In 2026, diagnostic microbiology and infectious diseases is not a calm place to be. It’s high-throughput, high-stakes, and not getting simpler any time soon.
The labs that are going to thrive in that environment are the ones that realized early that the battle isn’t won on the analyzer. It’s won in the first 10–30 minutes after a specimen hits the door—and they designed their automation strategy accordingly.