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 improper. You attempt once more. Nonetheless not proper. Ten minutes later you’re no nearer, and the clock is ticking. Ultimately you shut Copilot and do it the outdated means, the best way that takes longer, however no less than you understand it really works.
If that sounds acquainted, you’re not alone. And in line with Forrester VP and Principal Analyst JP Gownder, it’s changing into one of many important 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 advised UC In the present day. “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round with Copilot with no precise assure that I’m going to get it to do what I need, or I can provide up and do it the outdated means. What we’re seeing is a variety of abandonment behaviour, as a result of individuals are both losing time and by no means getting a solution, or just abandoning the device. And after they abandon the device, they fall off the training curve fully.”
Watch the complete 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 corporations having deployed no less than 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 evident that the tempo of progress is nowhere close to matching the tempo of deployment.
Solely 51% of organisations prepare non-technical workers 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 12 months on 12 months. As UC In the present day has beforehand reported, almost half of all AI licences go unused, costing massive enterprises a median of $80.6 million yearly — and the AIQ knowledge helps clarify why.
“For many staff, the associated fee to that particular person of utilizing a device like Copilot or Gemini is commonly larger 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 almost sufficient help.”
A brand new drawback: 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 individuals ship round at work is changing into a giant drawback,” he says. “Individuals don’t wish to learn it, so that they don’t learn it. It’s all these individuals producing all this content material that’s filling individuals’s inboxes after which they don’t learn it. That’s adverse productiveness proper there.”
The image is one among expertise creating new inefficiencies as quick because it guarantees to take away outdated ones, not as a result of the instruments are dangerous, however as a result of the individuals utilizing them haven’t been given what they should use them effectively.
The duty hole
That is the place organisations are basically getting it improper. 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.
“Staff aren’t answerable for buying these expertise on their very own,” Gownder says. “You because the employer are answerable for cultivating a studying and engagement setting that may equip them with the talents, understanding and ethics they should succeed. That is your duty as a frontrunner. It isn’t one thing you simply push all the way down to the workers and say, good luck.”
The answer, he argues, is just not extra on-line coaching modules. Organisations must rethink how they help AI adoption, constructing steady, hands-on, peer-based studying that places the worker relatively than the expertise on the centre. Forrester’s analysis discovered that social studying is no less than twice as efficient as formal coaching in terms 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 individuals as we roll out AI, not much less.”
For the organisations nonetheless ready to see a return on their AI funding, which may be crucial line in the entire report.
