Kenneth Glad
Workplaces are looking more closely at what new applicants can do on their own. The conversation is shifting toward practical ability, clear reasoning and reliability.
A young candidate who knows how to use AI may still struggle with the daily basics of professional work such as writing a clear memo, checking a source, explaining a decision in a meeting or spotting a flawed conclusion.
That tension is now entering hiring discussions. The Financial Times reported that one New York finance professional said his firm had become less drawn to applicants whose strongest selling point was AI familiarity, and more interested in candidates with broader analytical training.
“We want critical thinking, not just AI,” the financier said.
The issue is not whether AI belongs in offices. It’s already a part of the office work. The harder question is whether some graduates have treated it as a substitute for the slow skills employers still need, including interpretation, precision and accountability.
Classrooms show the strain
The same unease has been building in higher education. Futurism reported that instructors have raised alarms about students leaning on chatbots for coursework and then struggling when asked to discuss ideas without digital assistance.
The New Yorker quoted Troy Jollimore, an ethics professor at California State University, Chico, warning in 2025 that “massive numbers of students are going to emerge from university with degrees, and into the workforce, who are essentially illiterate.”
For managers, that warning has practical consequences. A polished document matters less if the person submitting it cannot defend an argument, identify what is missing or revise it after criticism.
This is where literacy and AI use collide. A worker may generate paragraphs quickly, but still fail at the human parts of the task: deciding what matters, understanding tone, checking accuracy and knowing when an answer is incomplete.
Productivity remains uncertain
The business case for AI is also under pressure. In an interview with The Register, Forrester vice president and principal analyst JP Gownder said productivity data has not yet shown the broad gains many technology boosters predicted.
“You begin to get the picture that information technology isn’t measured always in as linear a way into productivity as people assume,” he said. “It just isn’t there.”
Gownder also questioned whether many generative AI projects are producing measurable financial value:
“A lot of generative AI stuff isn’t really working.”
Automation may still remove jobs in the years ahead, but the lesson for employers is becoming more complicated. Speed is useful only when someone can judge whether the work is correct.
Sources: Futurism, Financial Times, The New Yorker, The Register
