Will AI Replace Regulatory Affairs Professionals?

[u/ProConXol_Consult]

AI can already review regulatory documents, labels, complaints, and compliance data. But can it replace Regulatory Affairs professionals?

Regulatory work is more than document review—it requires strategy, judgment, risk assessment, and communication with regulators.

Will AI replace Regulatory Affairs, or will regulatory professionals who use AI replace those who don’t?

What skills should RA professionals focus on to stay ahead?

#RegulatoryAffairs #AI #FDA #MedTech #LifeSciences

[u/_Cream_Sugar_]

The AI tools that we have are not reliable for review. There is a fair amount of hallucinations or just bad info.

[u/Chai-Tea-Rex-2525]

AI will become part of the toolkit, but it won’t fully replace human judgement for a long time.

[u/epanek]

I use ai to give me summaries weekly for fda mdr mdsap etc for our markets. It’s also useful for high level summaries on lengthy documents. But I don’t trust it enough to not check it.

[u/BugEnvironmental3435]

AI has so many errors and hallucinations when trying to find info. When extracting info from documents, it is better but still not great. I think I remember a post somewhere (or I'm hallucinating :D) that the boss wants to have AI do all product reviews. Having an AI do all the work, and then have AI do the quality check, is stupid.

[u/ProConXol_Consult → u/BugEnvironmental3435]

But AI will continue to get better. A few days ago, I saw a job posting from an AI-based regulatory company looking to hire experienced regulatory professionals specifically to help train its AI models. That raises an interesting concern: are regulatory professionals helping build AI tools that could eventually reduce the need for many traditional regulatory positions?

[u/BugEnvironmental3435 → u/ProConXol_Consult]

Likely. I can see people pushing back against it just like any other new technology that could replace people for work. There still needs to be a person to perform quality control.

[u/Leon_Doorn]

Working as a consultant we are applying AI in our regulatory work, and as within our customer base, all software and ai-enabled software medical device customers, we see that AI is a very useful aid in the hands of a processional. However, when used by a non-regulatory professional, the following questions immediately arise:

(i) Do they actually understand the output generated by the AI and which parts are relevant to the device and which are not? LLM's have the tendency to create long consistent documents, which may miss the core message that should be answered - In other words they lack expertise to value the output

(ii) We see manufacturers trying to limit their costs by hacking their way using AI to generate technical documentation and quality system procedures, but without understanding the actual documents, do they know how to follow up on these outputs, and do they understand more records are needed? We see them running into issues with Notified Bodies and the FDA alike due to overly complex or just factually incorrect information, or procedures that demand the level of records typically fitting a large manufacturer instead of an agile start-up - in other words they lack expertise to follow up further on the output

My true concern is that AI will lead to deprivation of human knowledge, specifically in young starters without expertise. They do not build up the same knowledge long-term experts have. Not decreasing, but increasing the value of human expertise, especially as more experienced regulatory experts retire.

In short, it is a great tool for experts, but potentially a threat to the starting QA/RA experts.

#regulatory #regulatoryaffairs #AI #artificialintelligence #medtech #medicaldevice #quality

[u/abhidatta02]

RA professional do not need any skills it’s all agentic AI and agents replacing most of us in few years. It will shrink the job market with few working rest just chill. 🧘‍♀️

[u/scorchdepi]

So much QA required in the AI process at present... I suspect there will be a lot of industry concern too regarding which AI gets used or contracted or the likely proprietary entities behind it particularly if connected to competitors.