According to the M365 Copilot monitoring dashboard made available in the trial, an average of 72 M365 Copilot actions were taken per user.
“Based on there being 63 working days during the pilot, this is an average of 1.14 M365 Copilot actions taken per user per day,” the study says. Word, Teams, and Outlook were the most used, and Loop and OneNote usage rates were described as “very low,” less than 1 percent and 3 percent per day, respectively.
Yeah that probably won’t have the intended effect…this basically just shows that AI assistants provide no benefit when they’re not used and nothing else.
I’m not a programmer, so it’s got nothing to offer me. Mostly my job is to write documentation for propriety software and hardware, stuff the AI knows nothing about, not everyone in the world can mak use of AI, and it doesn’t require a PhD and 30 days of constant usage to work that out.
I’m not saying AI specifically is useful, just that people in general tend to resist change in their work methods regardless of what they are.
I also work with a lot of proprietary knowledge, chemical and infrastructure in my case, and AI still can be useful when used properly. We use a local model and have provided it with all our internal docs and specs, and limited answers to knowledge from these, so we can search thousands of documents much faster, and it links to the sources for it’s answers.
Doesn’t do my job for me, but it sure as shit makes it easier to have a proper internal search engine that can access information inside documents and not just the titles.
Then maybe it’s not useful for you. That doesn’t mean AI isn’t useful for a number of other roles.
I’m a software developer and find its code generation to be awful, but I also find that it’s great at looking up technical information. Maybe I’m looking for a library to accomplish a task, and I want to compare features. Or maybe I’m having trouble finding usage examples for a relatively niche library. Those are task the AI is great at, because it can look at tons of blog posts, stack overflow questions, etc, and generate me something reasonable that I can verify against official docs.
If my workflow was. mostly email and internal documentation, yeah, AI wouldn’t be that useful. If my workflow relies on existing documentation that’s perhaps a little hard to find or a bit poor, then AI is great. Find the right use case and it can save time.
“Regular office work” is a pretty broad category. Yeah, it’s probably not useful in retrieving records for someone or processing forms, but it should be useful for anything that requires research.
I don’t know much about copilot, but some quick research shows it uses GPT-5 for the chat feature. I assume that’s what’s meant by the average queries in the article.
We have it on our system at work. When we asked what management expected it to be used for they didn’t have an answer.
We have a shell script that ingests a list of user IDs and resets their active directory passwords, then locks the account, then sends them an email telling them to contact the support desk to unlock the account. It a cron job that runs ever Monday morning.
Why do a need an AI for when we can just use that? A script that can be easily read understood and upgraded, with no concerns about it going off-piste and doing something random and unpredictable.
So yeah, they don’t use it, because it won’t work.
Well yeah, AI shouldn’t replace existing, working solutions, it should be used in the research phase for new solutions as a companion to existing tools.
Having been part of multiple projects introducing new software tools (not AI) to departments before, people are usually just stubborn and don’t want to change their ways, even if it enables a smoother work-flow with minimal training/practice. So yeah, basically people are so set in their ways,it is often hard to convince them something new will actually make their job easier.
The devil is in the details… what you describe screams to me what I call the “new boss syndrome”. New boss comes in and they feel the need to pee on everyone to mark their territory so they MUST bring in some genius change.
99% of the time, they are bringing in some forced change for the sake of change or something that worked on their previous place without taking into consideration the context.
I do not know anyone who prefers to work harder… either the changes proposed make no sense (or it’s too complex for people to understand the benefit) or the change is superfluous. That is usually where resistance to change comes from.
In all your software deployments did you blame the users for not getting it or did you redesign the software because it sucked (according to your users)?
That’s not what I’m asking. You designed or built something for some users. They didn’t like it, or didn’t use it as you expected. Was your response to change the software or blame the users for not using it correctly?
That depends on the issue. Sometimes it’s a lack of training, sometimes it’s obtuse software. That’s a call the product owner needs to make.
For something like AI, it does take some practice to learn what it’s good at and what it’s not good at. So there’s always going to be some amount of training needed before user complaints should be taken at face value. That’s true for most tools, I wouldn’t expect someone to jump in to my workflow and be productive, because many of the tools I use require a fair amount of learning to use properly. That doesn’t mean the tools are bad, it just means they’re complex.
I’ve occasionally been part of training hourly workers on software new to them. Having really, really detailed work instructions and walking through all the steps with themthe first time has helped me win over people who were initially really opposed to the products.
My experience with salaried workers has been they are more likely to try new software on their own, but if they don’t have much flexible time they usually choose to keep doing the established less efficient routine over investing one-time learning curve and setup time to start a new more efficient routine. Myself included - I have for many years been aware of software my employer provides that would reduce the time spent on regular tasks, but I know the learning curve and setup is in the dozens of hours, and I haven’t carved out time to do that.
So to answer the question, neither. The problem may be neither the software nor the users, but something else about the work environment.
Yeah that probably won’t have the intended effect…this basically just shows that AI assistants provide no benefit when they’re not used and nothing else.
People probably tried it, found out that it’s crap and stopped using it.
Its hardly possible to actually test it properly in relation to your work and changes in productivity with a single query per day. It
I’m not a programmer, so it’s got nothing to offer me. Mostly my job is to write documentation for propriety software and hardware, stuff the AI knows nothing about, not everyone in the world can mak use of AI, and it doesn’t require a PhD and 30 days of constant usage to work that out.
I’m not saying AI specifically is useful, just that people in general tend to resist change in their work methods regardless of what they are.
I also work with a lot of proprietary knowledge, chemical and infrastructure in my case, and AI still can be useful when used properly. We use a local model and have provided it with all our internal docs and specs, and limited answers to knowledge from these, so we can search thousands of documents much faster, and it links to the sources for it’s answers.
Doesn’t do my job for me, but it sure as shit makes it easier to have a proper internal search engine that can access information inside documents and not just the titles.
Then maybe it’s not useful for you. That doesn’t mean AI isn’t useful for a number of other roles.
I’m a software developer and find its code generation to be awful, but I also find that it’s great at looking up technical information. Maybe I’m looking for a library to accomplish a task, and I want to compare features. Or maybe I’m having trouble finding usage examples for a relatively niche library. Those are task the AI is great at, because it can look at tons of blog posts, stack overflow questions, etc, and generate me something reasonable that I can verify against official docs.
If my workflow was. mostly email and internal documentation, yeah, AI wouldn’t be that useful. If my workflow relies on existing documentation that’s perhaps a little hard to find or a bit poor, then AI is great. Find the right use case and it can save time.
Case in point, as per the article, AI is pretty useless for regular office work
“Regular office work” is a pretty broad category. Yeah, it’s probably not useful in retrieving records for someone or processing forms, but it should be useful for anything that requires research.
not sure there is any research done by people using office suite…
it sounds like you are conflating LLM in general with the crappy copilot that MS offers with the office suite
an LLM could be useful for research of large (large) datasets… Copilot would not be
I don’t know much about copilot, but some quick research shows it uses GPT-5 for the chat feature. I assume that’s what’s meant by the average queries in the article.
We have it on our system at work. When we asked what management expected it to be used for they didn’t have an answer.
We have a shell script that ingests a list of user IDs and resets their active directory passwords, then locks the account, then sends them an email telling them to contact the support desk to unlock the account. It a cron job that runs ever Monday morning.
Why do a need an AI for when we can just use that? A script that can be easily read understood and upgraded, with no concerns about it going off-piste and doing something random and unpredictable.
So yeah, they don’t use it, because it won’t work.
Well yeah, AI shouldn’t replace existing, working solutions, it should be used in the research phase for new solutions as a companion to existing tools.
so you think they may be useful but people just like to work harder? or perhps, they tried and saw no benefit at all and moved on?
Having been part of multiple projects introducing new software tools (not AI) to departments before, people are usually just stubborn and don’t want to change their ways, even if it enables a smoother work-flow with minimal training/practice. So yeah, basically people are so set in their ways,it is often hard to convince them something new will actually make their job easier.
The devil is in the details… what you describe screams to me what I call the “new boss syndrome”. New boss comes in and they feel the need to pee on everyone to mark their territory so they MUST bring in some genius change.
99% of the time, they are bringing in some forced change for the sake of change or something that worked on their previous place without taking into consideration the context.
I do not know anyone who prefers to work harder… either the changes proposed make no sense (or it’s too complex for people to understand the benefit) or the change is superfluous. That is usually where resistance to change comes from.
In all your software deployments did you blame the users for not getting it or did you redesign the software because it sucked (according to your users)?
I was one of the users, these are my observations with my colleagues reactions, and sometimes also myself.
That’s not what I’m asking. You designed or built something for some users. They didn’t like it, or didn’t use it as you expected. Was your response to change the software or blame the users for not using it correctly?
That depends on the issue. Sometimes it’s a lack of training, sometimes it’s obtuse software. That’s a call the product owner needs to make.
For something like AI, it does take some practice to learn what it’s good at and what it’s not good at. So there’s always going to be some amount of training needed before user complaints should be taken at face value. That’s true for most tools, I wouldn’t expect someone to jump in to my workflow and be productive, because many of the tools I use require a fair amount of learning to use properly. That doesn’t mean the tools are bad, it just means they’re complex.
Are you the person (alt) I was asking this of?
No. Is that a problem?
I’ve occasionally been part of training hourly workers on software new to them. Having really, really detailed work instructions and walking through all the steps with themthe first time has helped me win over people who were initially really opposed to the products.
My experience with salaried workers has been they are more likely to try new software on their own, but if they don’t have much flexible time they usually choose to keep doing the established less efficient routine over investing one-time learning curve and setup time to start a new more efficient routine. Myself included - I have for many years been aware of software my employer provides that would reduce the time spent on regular tasks, but I know the learning curve and setup is in the dozens of hours, and I haven’t carved out time to do that.
So to answer the question, neither. The problem may be neither the software nor the users, but something else about the work environment.
Worth noting the average includes the people who did use it a lot too.
So you can conclude people basically did not use it at all.