u/Opposite-Chicken9486

Still cant believe i did this. we rolled out this new ai agent setup a couple months ago for tier 1 tickets. supposed to auto resolve simple stuff like password resets and basic app crashes cutting average resolution time from 45 minutes down to under 5 per early reports. whole point was compressing time to value on every employee request management loves the dashboards showing slas green across the board.

was tweaking permissions yesterday because some high priority incidents were getting stuck in queue. agent was too aggressive on p2s so i wrote a quick bulk update script that pulled back a few hundred open tickets from last week across a couple of categories. tested on staging first everything fine. but i was rushing end of day friday brain dead from back to back meetings and hit the prod endpoint instead.

script ran in 90 seconds marked every matching ticket as resolved with canned note from agent 'instant intervention complete user notified'. art plummets overnight from 12 minutes average to 2.3 minutes. looks amazing at first glance until you dig in. 80% reduction but now 800 tickets show resolved with zero human touch including around 60 serious cases like broken payroll access and crm outages.

morning meeting cto pulls up the metrics dashboard screaming about how art never looked this good but finance director is furious because their month end reports are gone. service desk phones melting down employees calling back saying their issues vanished. slas technically hit but audit trail shows my id did bulk closure on everything. scrambling to reopen without triggering false alerts or double counting stats.

team is pissed i bypassed qa manager wants post mortem asap and now legal asking about compliance since some were security tickets. we can recover most data but the embarrassment is killing me. has anyone nuked their core metrics like this with ai overrides and how bad does this blow up usually??

Run a mid size digital agency. past six months every enterprise client has asked for the same thing. real time data piped directly into their internal dashboards, not a PDF report we send on Fridays

our current setup is manual exports, some light automation, and a lot of time spent reformatting data that should just flow automatically, the gap between what clients want to see and what our tools can push out automatically is becoming a retention problem. two clients this quarter mentioned it in renewal conversations. looked into API solutions that pull web intelligence, app data and market share into custom dashboards but the implementation lift on most of them is higher than expected

how are you getting live digital intelligence data into client dashboards without rebuilding your entire reporting stack.

Okay, so heres the thing. 

Losing a deal because we didnt catch a key update in time is literally the worst feeling ever. Ive had moments where a lead seemed super interested, and then out of nowhere, they went radio silent. I check in a few days later and realize there was a signal i missed, maybe they checked out a product page, or their team was talking about a similar solution, and if id caught it, we couldve moved faster and kept that deal alive.

The worst part is, sales moves so fast, and theres always something happening. By the time i catch up, it feels like im always behind, and sometimes its too late to close the deal. I need a way to keep up with sales signals in real time, so i can act fast and not miss anything important. 

I dont want to keep losing deals because of missed opportunities. 

Does anyone else deal with this?

If you spend enough time in it support, you start noticing something uncomfortable, a huge portion of the job is just repeating the same fixes over and over again. It doesn't matter if you are in a small internal it team or a large msp setup, the patterns stay the same. The environment changes, the users change, but the actual work often doesn't.

Typical examples:

Reinstalling the same software packages across different machines.

Manually restarting services on one endpoint at a time instead of doing it centrally.

Applying identical fixes for users who are all reporting the same issue.

Running the same diagnostic steps daily just to confirm known problems.

Remoting into multiple devices just to perform basic maintenance tasks.

Individually, none of these tasks feel like a big deal. But when you multiply them across dozens or hundreds of endpoints, they become a major time sink. The frustrating part is that most of this work is predictable. You already know what the fix will be before you even connect to the machine. You are just executing it manually because there is no automation layer or centralized execution in place.

Over time, this creates a strange inefficiency where:

Skilled technicians spend hours doing low level repetitive work.

Real issues get delayed because time is spent on routine fixes.

The overall workload grows without increasing complexity.

Teams feel busy all the time but not necessarily productive.

At some point, it stops feeling like troubleshooting and starts feeling like repetitive maintenance at scale. and that is where the real question comes in. How much of it support today is problem solving… versus just repeating the same manual fixes that could already be standardized or automated?

In most IT environments, Tier 1 support is basically the same few tickets over and over again.

My password is not working.

My laptop is slow.

I can't access email.

VPN isn't connecting.

Can you reset my account?

Now imagine that layer gets handled by AI instead of humans. The idea is pretty simple.

AI triages incoming tickets, suggests fixes instantly, and auto resolves the common ones without escalating everything to tier 2/3. In practice, that means,

Faster first response.

Fewer repetitive tickets hitting engineers.

Less context switching for the support team.

Tier 2/3 focusing only on real issues instead of password resets.

The promise is basically, remove the copy paste IT workload layer entirely. But in reality, I wonder if we are getting full automation… or just shifting the same problems into slightly smarter triage. Are we close to AI replacing tier 1 support, or are we just making the first layer faster without really reducing the workload underneath?

Generative engine optimization is completely different from regular SEO and nobody really talks about how messy the day to day process is

i've been manually running prompts through ChatGPT, Perplexity and Gemini every week to check if our pages show up in answers. some weeks we're in there, some weeks we're not and i have no idea why it changes. zero consistency

got a few wins early on but i can't replicate them because i don't understand what triggered them. was it the content structure, the citations, the way the topic was framed. no clue

tried a couple of tools that claimed to have GEO features. most of them just bolted an AI monitoring tab onto an existing SEO dashboard and called it done. citation tracking is there but it's basic. nothing that tells me why i won or lost a specific answer, no prompt analysis, no AEO breakdown of what content structure gets you recommended vs ignored

is anyone doing this properly in 2026 or are we all just guessing and hoping our content shows up.

We support 620 employees across 3 locations (hq + 2 satellite offices) and our weekly ticket volume sits around 140-160. Leadership keeps pointing to that number saying it's stable and under control.

But the reality on the ground feels completely different. If I break it down, probably 60-70% of tickets are repetitive. Password resets, onboarding/offboarding checklists, access requests to the same 6-7 core systems, permissions randomly breaking after updates. None of it is technically complex, but it's constant and never ending.

We have 5 people on the team and even our most senior guy, who used to focus on infra and improvements, is now spending half his week clearing tickets and following up on basic requests. What's worse is the interruptions. Someone starts working on something meaningful, gets pulled into 3 small tickets, loses context, and the day is gone.

Morale has dropped noticeably over the last quarter. No one complains loudly, but you can tell people are just going through the motions.

We have tried:

Pushing more self service.

Documenting common requests.

Limiting what gets escalated but it hasn't really changed the day to day.