What if we could free the human lab professional from manual (and tedious) routines? What if we could redirect said professional to higher-value work? Sounds like a dream, right? Sounds like our lab won’t need that lab information system (LIS) upgrade after all, right?
Well, experience tells a different story: rather than simply replacing roles, lab automation is splitting them into two distinct pathways – and that shift demands thoughtful planning, especially when your LIS system must keep pace.
So, let’s see what we can actually achieve with lab automation in today’s healthcare and medical laboratory landscape, shall we?
Two Lab Automation Paths Emerge
In many labs, the arrival of automation doesn’t remove people – it divides the workforce into two groups. One group takes on automation-adjacent work: managing robotic loaders, calibrating instruments, and overseeing workflows. The other ground is dedicated to the traditional manual lane: dealing with non-routine samples, troubleshooting anomalies, and ensuring quality when machines falter.
However, newer data paint a clear picture of how lab automation is reshaping the lab workforce. A 2024 survey found that 39% of laboratory professionals rank limited staffing as their greatest challenge. While 52% of respondents admitted concerns that automation might threaten jobs, an overwhelming 95% believed that automation could improve patient care.
So, basically, lab professionals want automation, and they want it yesterday. And guess what? They’re right.
Because these findings underscore two key realities:
- The volume and complexity of testing continue to rise amid staffing shortages and burnout
- Automation amplifies output per person and changes what those people spend their time doing.
For labs implementing data transformation, the shift focuses less on reducing staff numbers and more on making sure their staff are packed with different skills. These skills enable effective oversight, exception handling, workflow optimization, and data-driven decision-making.
Why the Split Happens
Here’s the thing about lab automation: it transforms everything, rather than just speed things up. When you flip the switch on a new automated system, sample volumes explode, data piles up, and suddenly your old infrastructure starts creaking.
Because the real question is: can legacy LIS systems add more automation capabilities to keep up with the times? Every year, labs spend significant resources working around the limitations of legacy systems. Much too often, we encounter labs that suffer from digital inefficiencies, which (if solved) can reduce overall lab productivity by up to 20%. We’re talking about incompatibility, limited scalability, compliance risks, and so much more. Lab automation solves these issues – but legacy systems are simply not built for this level of modernization.
However, there’s a twist machines can’t handle alone. While automation crushes repetitive work, it creates new challenges:
- Unusual samples
- Protocols that don’t quite fit
- Instruments throwing curveballs
And for labs who implement AI solutions…? Well, they can tell you all about AI hallucinations.
Those moments still need a human brain. Someone who can actually think through what went wrong and fix it. And that’s because automation doesn’t eliminate work; it just shifts who does it.
However, the staff member who’s “babysitting” an automated loader isn’t doing the same job as someone carefully pipetting assays by hand. They need different training, different instincts, and different ways to measure success. And that leads us to tackle the following conclusion – The split between automation and manual work isn’t just organizational, because it cuts right through your team.
The LIS and the Lab Automation Split
If your LIS is still configured for the “traditional” technician doing manual work, that is a proven risk. Because two things are now happening:
First, Routine tasks are automated, thus freeing up time and budget… But only if the system captures the upstream/downstream flow, sample metadata, and links to exceptions. And then, oversight tasks increase, which means the LIS must support not just “normal run” but divergence, re-routing, validation, and audit trails.
So basically, what happened is that lab automation didn’t make tech teams smaller – it made them more differentiated. And now your LIS has to keep up. And you saved zero budgets.
The Opportunity to Adopt Lab Automation
Here’s the positive: when you treat automation not as “remove humans” but as “reshape human roles”, you unlock value. When paired with training and system readiness, automation will boost productivity and morale. You should shift your skilled lab staff into oversight, advanced troubleshooting, and data-driven decision-making.
Because that is exactly where a modern LIS adds value – automation isn’t a standalone investment. The investment must include the workflow redesign, up-skilling of people, and the lab information system to glue it all together. Like LabOS, for example.
Your lab professionals and staff are not disappearing; they’re evolving. And your LIS? Well, naturally – it must evolve with them.
➡️ GO FOR IT
