r/CIO

We run claims intake through an agent that reads documents and routes them. It has been live since January and it handles about 3000 files a week.

In March the provider went down mid morning. Our agent did not fail over because there was no fallback configured and nobody had decided who owned that. The team assumed the platform group had it and the platform group assumed the vendor did. Four hours of manual intake and two people working late to clear the backlog. The postmortem found we had budgeted for a second provider in the original business case and quietly dropped it during procurement.

What we changed is boring. There is a named owner for provider redundancy and a quarterly test where we cut the primary and watch what happens. The first test failed too. How are you handling provider outages when the workflow is customer facing?

We have people building small AI automations around spreadsheets, docs, email, Slack, and internal tools.

Individually they seem harmless. But six months later, who owns them, who knows what data they touch, and who shuts them down when the employee leaves?

For CIOs dealing with this already, are you tracking AI tools centrally or still handling them case by case?

VP of IT Ops here. We are currently planning for roadmaps, budgets and headcount for 2027. Last year we had a big increase in our employee count (~15% from ~3500 --> ~4000). We're also expecting to grow another 8% this year. Nevertheless, we have not been getting any additional hc this year. For next year's planning we're also not getting any headcount. Naturally, with increased # of employees, the amount of tasks has increased for my teams. We're focussing on automating our repetitive tasks and get rid of all the toil, but I feel like we're drowning. The CTO of the company understands our pains, but 'has to make tough decisions, because we have to keep innovating for our customers'. We're having issues to keep up with all the requests and supporting our employees. He is suggesting focussing more on automation and building agents. But as we're barely can keep the light on, we don't have time to focus on building this. As leaders we have to stand with the choices made and also bring the message across to the teams. Simultaneously, I have trouble with the fact that we're planning to grow even further and not getting additional headcount for my team. Anyone else having these issues and if so, what do you do?

Hello you all,

I would like to discuss AI governance. So with new regulations everywhere I would like to know how companies are approaching it.

AI developers, have you already started including data governance or is it something a different person does after you finish developing your model (AI governance specialists)

I would like to specifically ask how this varies between big companies and small/medium scale enterprises. Because I think not everyone has the resources to hire specialists, I believe.

If you are already trying to be compliant, what kind of frameworks do you use to ensure compliance or do you have an in-house built compliance framework ?

Now my question is specifically towards the EU devs, what is your approach to be compliant since it's mandatory to have conformity assessments in 2027.

For general deva, what do you think of the following job positions, AI governance expert, AI and the law expert, technical governance expert, AI alignment expert, AI ethics professional, AI red-teaming professional. Is this something you already heard or is it something new to you ?

If you have any opinion towards AI governance, please share.

something I've noticed over the last few months and want to double check with other CIOs.
we set up an AI governance committee early this year like everyone did. legal, security, a couple of business leads, me. the idea was policy and principles, deciding which use cases we're comfortable with.
what it's turned into is a buying queue. almost every agenda item is someone who wants to purchase an AI tool, and we spend the meeting asking the same questions every time. where does the data go, does the vendor train on it, who approved the budget, does it overlap with something we already pay for. more often than I'd like, the answer to that last one is yes
talking to peers, a few of them describe the same drift. the committee that was meant to set direction ends up doing vendor intake, badly, once a month
my theory is the committee isn't the problem. there's no front door for AI purchases, so the committee became one by default. the questions we ask are intake questions, and if they got answered before a request reached us we could go back to the policy work we were set up for
the other possibility is that this is just what AI governance looks like once it's real, and I should stop fighting it.
curious which one it is for you. did your committee end up doing procurement's job too?

As the title says, I’m trying to understand what most people are paying for their MSP delivered service desk. This would be standard L1 through L2, worth M365 app support with some kind of AI deferment tool included. I’ve received pricing that’s all over the map and am trying to figure out what I’m missing, around 2000 end users.

Source links back to the ledger? An audit trail? A human sign off? Curious what the minimum bar is for people actually presenting to boards.