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.

  • FartsWithAnAccent@fedia.io
    link
    fedilink
    arrow-up
    97
    arrow-down
    1
    ·
    edit-2
    4 months ago

    They tried implementing AI in a few our our systems and the results were always fucking useless. What we call “AI” can be helpful in some ways but I’d bet the vast majority of it is bullshit half-assed implementations so companies can claim they’re using “AI”

    • speeding_slug@feddit.nl
      link
      fedilink
      English
      arrow-up
      7
      ·
      4 months ago

      To not even consider the consequences of deploying systems that may farm your company data in order to train their models “to better serve you”. Like, what the hell guys?

      • FartsWithAnAccent@fedia.io
        link
        fedilink
        arrow-up
        32
        arrow-down
        1
        ·
        4 months ago

        Looking like they were doing something with AI, no joke.

        One example was “Freddy”, an AI for a ticketing system called Freshdesk: It would try to suggest other tickets it thought were related or helpful but they were, not one fucking time, related or helpful.

        • Hackworth@lemmy.world
          link
          fedilink
          English
          arrow-up
          15
          arrow-down
          1
          ·
          4 months ago

          Ahh, those things - I’ve seen half a dozen platforms implement some version of that, and they’re always garbage. It’s such a weird choice, too, since we already have semi-useful recommendation systems that run on traditional algorithms.

        • MentallyExhausted@reddthat.com
          link
          fedilink
          English
          arrow-up
          7
          ·
          4 months ago

          That’s pretty funny since manually searching some keywords can usually provide helpful data. Should be pretty straight-forward to automate even without LLM.

          • FartsWithAnAccent@fedia.io
            link
            fedilink
            arrow-up
            5
            arrow-down
            1
            ·
            4 months ago

            Yep, we already wrote out all the documentation for everything too so it’s doubly useless lol. It sucked at pulling relevant KB articles too even though there are fields for everything. A written script for it would have been trivial to make if they wanted to make something helpful, but they really just wanted to get on that AI hype train regardless of usefulness.

        • rottingleaf@lemmy.world
          link
          fedilink
          English
          arrow-up
          1
          ·
          4 months ago

          It’s bloody amazing, here I am, having all my childhood read about 20/80, critical points, Guderian’s heavy points, Tao Te Ching, Sun Zu, all that stuff about key decisions made with human mind being of absolutely overriding importance over what tools can do.

          These morons are sticking “AI”'s exactly where a human mind is superior over anything else at any realistic scale and, of course, could have (were it applied instead of human butt) identified the task at hand which has nothing to do with what “AI”'s can do.

          I mean, half of humanity’s philosophy is about garbage thinking being of negative worth, and non-garbage thinking being precious. In any task. These people are desperately trying to produce garbage thinking with computers as if there weren’t enough of that already.

    • The Menemen!@lemmy.world
      link
      fedilink
      English
      arrow-up
      4
      ·
      4 months ago

      It is great for pattern recognition (we use it to recognize damages in pipes) and probably pattern reproduction (never used it for that). Haven’t really seen much other real life value.