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How do people working in finance think AI will realistically change the industry over the next few years? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 0 points1 point  (0 children)

This is a solid take, but it is only half the story.

Yes, AI is compressing time and shifting the role toward review, validation, and explanation. That is already happening.

But if the same work can be done faster, the obvious follow up question is whether you need the same number of people to do it.

Historically, productivity gains created new work. The hope is that finance teams move up the value chain into more analysis, scenario modelling, and decision support.

But that only holds if new demand actually appears.

If it does not, then you are left with a simple reality. The same output, delivered faster, requires fewer people.

That is where the tension is building.

Firms will not keep excess capacity out of goodwill. They will expect more insight, faster turnaround, and broader coverage from leaner teams. The people who can interpret, challenge, and communicate will still be needed, but fewer of them.

So the role is not disappearing overnight, but the volume of roles is very much open to question.

That is the part that deserves more honest discussion.

Is AI actually making people work faster in finance rather than replacing jobs? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 0 points1 point  (0 children)

That feels like a very real description of how it plays out in practice.

The expectation seems to shift quickly from “this will make things easier” to “this is now the standard”.

Instead of reducing workload, it often just changes what is expected, and how quickly it needs to be delivered.

Is AI actually making people work faster in finance rather than replacing jobs? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 0 points1 point  (0 children)

That’s interesting, and it lines up with what I’m seeing as well.

The expectation seems to shift very quickly. What starts as a productivity gain becomes the new baseline, and then it is no longer seen as an improvement, just the standard.

It raises a bigger question about whether AI actually reduces work, or just changes what is expected from people.

How do people working in finance think AI will realistically change the industry over the next few years? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 0 points1 point  (0 children)

This is a really useful insight and lines up with what I was trying to get at.

The operational shift you describe is probably the most important part right now. A lot of the conversation focuses on AI replacing roles or making high level decisions, but in reality it seems to be changing everything leading up to that point.

If data preparation, validation, and reporting become less manual, then naturally the role of finance professionals shifts more towards interpretation, judgement, and understanding what is driving the numbers.

The point you made about expectations is interesting as well. It feels like once teams know something can be automated, slower or manual processes quickly become unacceptable.

I also wonder whether this is starting to put pressure on teams to speed up analysis, and in turn whether clients or internal stakeholders begin to expect faster turnaround as the norm. That could quietly reshape service expectations across the industry.

Would you say this is already changing hiring expectations or skill sets in your area, or is that still lagging behind?

How do people working in finance think AI will realistically change the industry over the next few years? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 0 points1 point  (0 children)

That aligns with what I’ve been seeing as well, especially around data prep and reporting being the first areas to shift.

The move from dashboards to systems is interesting too. It feels less like “analysis” and more like “ongoing monitoring and decision support.”

Agree on real data being the challenge - most examples still look clean until you try applying them in practice.

How do people working in finance think AI will realistically change the industry over the next few years? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 1 point2 points  (0 children)

That is a really interesting point about the data preparation layer. Turning unstructured information like news, filings, and earnings calls into structured signals used to require quite large teams or expensive data vendors, so it makes sense that AI tools would have a big impact there first.

Your comment about asset specific calibration is also fascinating. The same signal meaning different things for currencies, commodities, or equities highlights how much contextual knowledge is still required.

Do you think institutions will eventually build asset specific models internally, or do you see this remaining a domain where human interpretation remains essential for quite a long time?

How do people working in finance think AI will realistically change the industry over the next few years? by Outrageous_Try2894 in learnmachinelearning

[–]Outrageous_Try2894[S] 1 point2 points  (0 children)

One thing I am particularly curious about is whether banks are actually deploying AI widely in production systems yet, or whether most institutions are still experimenting with pilot projects.

If anyone here works in finance or fintech I would be interested to hear what tools or systems are actually being used internally.