Image the scene. You’re at your desk, deadline looming, and also you determine to let AI deal with the primary draft. You kind a immediate. The result’s flawed. You attempt once more. Nonetheless not proper. Ten minutes later you’re no nearer, and the clock is ticking. Finally you shut Copilot and do it the previous means, the best way that takes longer, however at the least it really works.
If that sounds acquainted, you’re not alone. And in accordance with Forrester VP and Principal Analyst JP Gownder, it’s turning into one of many fundamental productiveness issues within the trendy office.
“I need you to place your self into the place, I do know I’ve personally, of: I attempt a immediate and it fails. I attempt one other immediate and it fails,” he instructed UC At this time. “At that second, I’ve a choice to make. Both I can preserve messing round with Copilot with no precise assure that I’m going to get it to do what I need, or I can provide up and do it the previous means. What we’re seeing is numerous abandonment behaviour, as a result of individuals are both losing time and by no means getting a solution, or just abandoning the software. And once they abandon the software, they fall off the educational curve fully.”
Watch the total interview: Why AI Literacy Is Hurting Productiveness: Forrester’s JP Gownder
The numbers behind the issue
Gownder’s feedback come alongside Forrester’s second AIQ report. AIQ stands for Synthetic Intelligence Quotient, a measure of worker readiness to succeed with AI instruments at work. The findings make uncomfortable studying for any organisation that has invested closely in enterprise AI.
Regardless of greater than 80% of firms having deployed at the least some AI instruments, simply 16% of staff throughout the US, UK, Germany, France and Australia achieved a excessive AIQ rating in 2025, up from 12% in 2024. Gownder is obvious that the tempo of progress is nowhere close to matching the tempo of deployment.
Solely 51% of organisations prepare non-technical employees on generative AI in any respect. Simply 23% train immediate engineering. And solely 37% of staff really feel assured adapting to AI-driven methods of working, a determine that has barely shifted yr on yr. As UC At this time has beforehand reported, practically half of all AI licences go unused, costing massive enterprises a mean of $80.6 million yearly — and the AIQ information helps clarify why.
“For many staff, the price to that particular person of utilizing a software like Copilot or Gemini is commonly increased than the time financial savings they obtain on the opposite finish,” Gownder explains. “As a result of they’re studying by doing, and that studying is gradual, painful, and taking place with out practically sufficient assist.”
A brand new downside: AI slop
Past the abandonment cycle, Gownder identifies a second productiveness drain rising in workplaces. He calls it AI slop.
“Work slop, AI slop that folks ship round at work is turning into an enormous downside,” he says. “Individuals don’t need to learn it, in order that they don’t learn it. It’s all these folks producing all this content material that’s filling folks’s inboxes after which they don’t learn it. That’s unfavourable productiveness proper there.”
The image is one in all expertise creating new inefficiencies as quick because it guarantees to take away previous ones, not as a result of the instruments are dangerous, however as a result of the folks utilizing them haven’t been given what they should use them effectively.
The accountability hole
That is the place organisations are basically getting it flawed. There’s a widespread assumption in enterprise AI rollout that the instruments will largely communicate for themselves, that staff will discover, experiment, and naturally enhance. Forrester’s analysis suggests in any other case, and the implications are falling on the workforce.
“Workers aren’t chargeable for buying these abilities on their very own,” Gownder says. “You because the employer are chargeable for cultivating a studying and engagement surroundings that can equip them with the talents, understanding and ethics they should succeed. That is your accountability as a frontrunner. It’s not one thing you simply push all the way down to the workers and say, good luck.”
The answer, he argues, isn’t extra on-line coaching modules. Organisations have to rethink how they assist AI adoption, constructing steady, hands-on, peer-based studying that places the worker moderately than the expertise on the centre. Forrester’s analysis discovered that social studying is at the least twice as efficient as formal coaching on the subject of elevating AIQ in observe.
“This looks like a really techno-focused train,” he says. “It’s a human-focused train. We have to make investments extra in folks as we roll out AI, not much less.”
For the organisations nonetheless ready to see a return on their AI funding, that could be an important line in the entire report.
