Despite 96% of C-suite executives expecting AI to boost productivity, employees say it has increased their workload, hampered productivity and caused job burnout, research shows.
The new global study, in partnership with The Upwork Research Institute, interviewed 2,500 global C-suite executives, full-time employees and freelancers. Results show that the optimistic expectations about AI's impact are not aligning with the reality faced by many employees. The study identifies a disconnect between the high expectations of managers and the actual experiences of employees using AI.
Despite 96% of C-suite executives expecting AI to boost productivity, the study reveals that, 77% of employees using AI say it has added to their workload and created challenges in achieving the expected productivity gains. Not only is AI increasing the workloads of full-time employees, it’s hampering productivity and contributing to employee burnout.
I mean if it's easy you can probably script it with some other tool.
"I have a list of IDs and need to make them links to our internal tool's pages" is easy and doesn't need AI. That's something a product guy was struggling with and I solved in like 30 seconds with a Google sheet and concatenation
No arguments from me that it's better if people are just better at their job, and I like to think I'm good at mine too, but let's be real - a lot of people are out of their depth and I can imagine it can help there. OTOH is it worth the investment in time (from people who could themselves presumably be doing astonishing things) and carbon energy? Probably not. I appreciate that the tech exists and it needs to, but shoehorning it in everywhere is clearly bollocks. I just don't know yet how people will find it useful and I guess not everyone gets that spending an hour learning to do something that takes 10s when you know how is often better than spending 5 mins making someone or something else do it for you... And TBF to them, they might be right if they only ever do the thing twice.
I think the actual problem here is that if the product people can’t learn such a simple thing by themselves, they also won’t be able to correctly prompt the LLM to their use case.
They said, I do think LLMs can boost productivity a lot. I’m learning a new framework and since there’s so much details to learn about it, it’s fast to ask ChatGPT what’s the proper way to do X on this framework etc. Although that only works because I already studied the foundation concepts of that framework first.
I think the actual problem is that they won't know when they've got something that compiles but is wrong... I dunno though. I've never seen someone doing this and I can only speculate tbh. I only ever asked ChatGPT a couple of times, as a joke to myself when I got stuck, and it spouted completely useless nonsense both times... Although on one occasion the wrong code it produced looked like it had the pattern of a good idiom behind it and I stole that.
It also helps you getting a starting point when you don't know how ask a search engine the right question.
But people misinterpret its usefulness and think It can handle complex and context heavy problems, which must of the time will result in hallucinated crap.
And are those use cases common and publicized? Because I see it being advertised as “improves productivity” for a novel tool with myriad uses I expect those trying to sell it to me to give me some vignettes and not to just tell my boss it’ll improve my productivity. And if I was in management I’d want to know how it’ll do that beyond just saying “it’ll assist in easy and menial tasks”. Will it be easier than doing them? Many tools can improve efficiency on a task at a similar time and energy investment to the return. Are those tasks really so common? Will other tools be worse?