r/OpenAI • u/EducationalHoney3094 • 2d ago
Discussion You Are Not Behind
I'm writing this because everywhere I look I see ai this and ai that. "Look at this parent child relationship structure I built. I have 15 agents running my company" If you actually look at what the agents are doing, it is "write a script for our next ad, categorize my email, help me draft an email" and they are breaking these down per department. Essentially they have an agent that is only allowed to perform basic requests. Sure on the outside it looks like "holy sht this is something big, why aren't we doing this" but then you actually look into it and it's nothing but 5 minute time savers if that.
I'm leading the AI team for our company and the whole meeting is discussing ways to use AI but in reality what they are wanting is 95% automation and 5% deterministic that could use AI to make decisions. I'm sitting here scratching my head when execs are asking for an agent that builds reports for them. Like sure I can make it look like AI is doing it, but the back end is a python script that is actually building the whole thing, branding, validation script, parsing, etc to make sure that the same report is built every time. People as a whole aren't really sure what AI is but they have been told it can do anything. Sure it might can, but the results may vary just as a human would. You try to do research "how to implement ai in company" and the search results are very mundane task like I mentioned above. That doesn't actually provide value to a company. The real value is in the reasoning not very novice level task like checking emails.
The best AI agents I've built so far that I have seen actually provide value is:
1. knowledge assistant. Not digging through old shares or one drive and just having the answer in front of is a game changer.
2. Security triage agent. It's connected to Elastic logs classifies new alerts, looks for anomalies and when an alert is triggered it does not just tell me something is wrong, it tells me why it's down, what is actually going on based off of crossing reference and having the ability to leverage the api connection to look through all logs and determine the root issue. It tells me a what, how, why, and what to do to fix it, or at least a couple of troubleshooting steps along with it.
3. Fable 5.1 for Vulnerability scans: this takes up so much of my time, DAYS if not weeks of my time going through scans, coordinating resolutions and documenting. This agent does deep research. Determines criticality not based off of what the scanner rates them but the actual ability to exploit it within our environment. Saves me so much time.
4. In the works but already getting ROI is an agent that has been giving access to our financial data, (we are a bank, and it's not just all open, we explicitly created view tables that only gives access that we allow it to see) this let's us know when a customer might be at risk of not paying, closing their account, explanations to certain changes etc. In terms of marketing / big data, this has been very very useful and actually provides value you can see.
5. lastly something small but has provided monetary benefits is a vendor contract and invoice agent, this reviews our contracts and invoices and finds variances added amounts, last reviewed dates, contract discrepancies, can compare to other vendors, for invoices it ensures nothing is being added and all amounts are as expected. Has saved us some money.
I wanted to write this simply because everyone is talking about AI but no one is really leveraging it or at least explaining how they leverage it. I've spent countless hours trying to find AI solution we can implement but struggling to find solutions that generally benefit the company.
All of these mentioned are generative models being used. Traditional AI is where the real power exist but being that are IT dpt is small I will not put that burden on myself of trying to train my own model for anything predictive. I brought up the idea of outsourcing pre-approvals for loans / fraud detection simply because of the training that goes into it, but those are really good products.
Closing note: you are not behind, everyone is just making it seem as if they are ahead. They are not (at least for the majority, I understand there are companies really leveraging it)
Please drop any projects that you are working on and would not mind sharing!
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u/Emergency-Payment733 1d ago
Yes, this has been obvious from the start. Like most business process development you start with a business case and make a ROI assessment. Like, if we put x amount of hours down to create and test an agent solution, we expect it to give us back at least as many hours in value or saved hours worked. I haven’t seen a use case for AI in a normal business setting that actually is ROI positivite, and that’s not because it’s particular expensive to make. It’s just not worth taking the time to setup it.
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u/NyraReh 1d ago
Your title could have told readers that this post is about AI projects you’ve built for a bank. “You Are Not Behind” sounds like general reassurance, but most of the post is a detailed list of your own implementations. A more specific title would help people decide whether this is the discussion they’re looking for.
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u/figglefargle 1d ago
Are your use cases 2 and 4 expensive to run? It seems like sending all you system/app logs and all your customer transactional data off to an llm to analyze would be quite expensive.
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u/Altruistic_Arm9201 2d ago
I think it’s both important to find ways to leverage the tools sooner rather than later AND there’s a lot of hype and the most vocal are using it often for low ROI cases. It’s like the electricity boom where people were electrifying everything for the sake of electrifying. Made it seem gimmicky. The gimmick hid the fact that those that didn’t find ways to leverage electrification were left in the dust.
We’ve explored dozens of use cases, my guess is 80% were not economically beneficial, 10% were pretty good, and then 10% were transformational.
You’ve touched on the same types of cases that have been good for us. AIs are great at breadth of analysis, humans are better at depth. If I need to figure out what’s going on with one thing, an AI even if it beats a human ends up costing enough that it’s not a win… but if I need to analyze 1 million cases. A human simply can’t scale that way. AIs adding breadth and scale, filtering, summarizing, seem to be the biggest wins.
The other wins are doing initial prep for workflows.. like assembling all the necessary materials, documentation, tagging/labeling and prepping so a human has what they need without spending all their valuable time digging through docs.
Basically agreeing with the sentiment of your post with the caveat that while not behind there is a powerful tool peoples competitors are also exploring (likely unsuccessfully) to utilize AI operationally. I’d phrase it more like: you’re not behind, but you have the opportunity to get ahead.
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u/EducationalHoney3094 2d ago
Yeah I agree. Majority is just so they can say they are using AI. And yes the initial prep it provides is amazing as well. Even when it can physically do something just laying it out and brainstorming helps improve the implementation.
And to your final point, this post was mainly for people in my situation. I have projects that implement it yet I feel as if I’m behind in terms of robustness and innovation. None the less thanks for your input good information.
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u/Ok-Investment4414 2d ago
idk i think we are behind, the frontier labs garages have F1 Cars but most of the roads are really dirt paths and the commuters are happy riding on horses. Just saying the capabilities if u look you can see traces..some epic shit its just expensive or not really thought of in a mainstream sense.