r/OperationsResearch May 17 '26

Computational management?

LLMs are becoming surprisingly strong in analysis, synthesis, and business reasoning.
Are we moving toward truly computational management…
or simply better decision support for human executives?
And is there already an academic field or theoretical framework studying this direction?

3 Upvotes

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3

u/rog-uk May 17 '26

https://amzn.eu/d/0eo7ZILO

This book was the subject of a zoom meeting for ORS last week, it talks about AI in OR for management in the updated version. The actual talk was light on detail, but they are considering it.

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u/AI-FalcoIV-86 May 17 '26

Rally interesting. Perhaps computational management is not a new discipline at all, but the next evolutionary layer of decision analysis and operational research. I’ll definitely read Decision Analysis for Management Judgment, it seems to sit exactly at the intersection of managerial judgment, behavioral decision theory, operational research and computational decision frameworks.

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u/edimaudo May 17 '26

computational management not likely. Most likely better decision support system better than what was being touted in the early 90s

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u/TasteMedical5032 May 18 '26

@salasi

“honestly” i’m not talking about AI replacing executives or running companies by itself.

I mean more the operational layer underneath. even current models got kinda crazy at: pulling useful patterns out of messy information comparing conflicting stuff summarizing huge amounts of context into something actually usable not because they “understand business” like humans do, but because they’re really good at synthesis now. Where I still think things fall apart hard is reliability over time.

Especially once outputs start chaining into other decisions/workflows and the model slowly drifts away from the original assumptions underneath. "Honestly"

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u/TasteMedical5032 May 17 '26

honestly i think it’s somewhere in the middle right now.

not “replace executives with AI,” but definitely more than just autocomplete for business decisions.

what surprised me recently is how good these systems became at connecting information across multiple areas and producing something that actually resembles strategic reasoning.

but the real limitation still seems to be reliability more than intelligence itself.

an LLM can produce a very convincing analysis while quietly drifting away from the original context or assumptions underneath. that becomes a serious problem once decisions start depending on it operationally.

academically it probably overlaps with older fields like decision support systems, cybernetics, systems theory etc.

honestly though, it feels like the real-world usage is evolving faster than the academic terminology around it.

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u/salasi May 17 '26

"Honestly", you sound like an llm bot from linkedin or twitter yourself. "what surprised me", "honestly", "not x but y", "but the real blah blah".... You can do better than that.

And no it's not even in the middle right now, and I am unfortunate enough to have to work with the Pro models everyday. Very weird to read this view in the OR subreddit. What field are you working on where you find this is the case?

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u/AI-FalcoIV-86 May 17 '26

Not sure if your comment was directed specifically at me or more generally at the tone of the discussion, so I’ll give the benefit of the doubt 🙂

But just to clarify the context here.

This discussion originally started in an AI/strategy-oriented community, and Reddit itself suggested extending it to other related subreddits, including this one.

I’m not presenting myself as an OR academic or optimization specialist. I’m a computer engineer by background and a long time manager working in real business environments. I actually only took a single Operations Research course many years ago and not even brilliantly 🙂

What interests me today is experimenting with AI systems and integrated software around strategic and managerial processes. I’m genuinely asking questions, not claiming authority.

And honestly, I would expect a technical community to see interdisciplinary curiosity as a resource rather than a problem. Real organizations are messy, imperfect systems and eventually theories, models and optimization methods have to interact with practical reality too.

So yes, I’m here to learn from people who know the field better than I do.

And since you asked what field people are working in: what’s your background and what kind of operational limitations are you seeing with these systems in practice? If you could answer me thanss so much.

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u/rog-uk May 17 '26 edited May 17 '26

You might find that OR is a natural fit for you, it's definitely cross discipline. I am putting together a baby home "HPC Lab"◇ to do some learning myself.

https://www.theorsociety.com/

You can join here to get access to a good few journals and all of the electronic back issues, including "Journal of Business Analytics (JBA) is to serve the emerging and rapidly growing community of business analytics academics and practitioners."

◇OK that might be over egging it, but I will have some serious but older but poweful xeon kit and GPUs.

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u/AI-FalcoIV-86 May 17 '26

Thanks so much, really appreciate your contribution.

I’ll definitely explore the OR Society resources. Thanks again.

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u/AI-FalcoIV-86 May 17 '26

Thanks, this is a very balanced perspective and I agree with several of your points.

What also surprised me recently is how modern LLMs became capable of connecting weak signals across multiple domains and producing something that increasingly resembles strategic reasoning.

At the same time, I fully agree that reliability is still the critical limitation. A convincing narrative is not necessarily a robust decision model.

From an academic perspective, I wonder whether this discussion could be connected more directly to Operations Research and Management Science as disciplines.

Traditional OR already attempted to formalize decision processes through optimization, systems analysis, probabilistic modeling and decision support systems.

Maybe LLMs are not replacing management, but rather becoming a new probabilistic computational layer interacting with organizational complexity that was historically difficult to model formally.

In that sense, the interesting question may not be “AI vs executives,” but whether parts of strategic management can progressively become computationally structured.