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CEOs Say AI Is Making Work More Efficient. Employees Tell a Different Story.

ended 22. January 2026

In 2025,  a swathe of industry executives proclaimed the productivity benefits of artificial intelligence, yet a growing body of evidence suggests the reality inside workplaces looks very different. 

A Wall Street Journal survey of 5,000 white-collar workers (published 21 Jan 2026) finds a striking gap between what C-suite leaders report and what most employees experience. 

Role
 		   Excited (%)                Anxious/Overwhelmed (%)        
Workers*        
 		~30   ~70
Managers        
 		~50   ~50
Directors        
 		~65   ~35
Vice Presidents     
   		~70   ~30
C-suite        
 		~75   ~25

Source: WSJ *Not managerial

While many executives claim AI tools save them eight or more hours of work per week, the majority of non-management staff say they save little to no time at all.

This disconnect isn’t simply a matter of perception, it is also performance-related. Employers are investing heavily in generative AI and positioning it as a core driver of efficiency and future growth; yet for many workers, the experience is a mix of basic assistance and added overhead. 

Staff commonly use AI for tasks like search and draft generation, but they often spend significant portions of their days correcting errors, reworking outputs or teaching the tools context, a burden some commentators have dubbed the “AI tax” on productivity.

Beyond time savings, workers express feelings of anxiety and overload around AI integration, while executives tend to report excitement and confidence in the technology’s potential. 

Economists and labour researchers point to similar patterns outside this survey. Recent industry analyses show that AI adoption often introduces new forms of cognitive labour and cleanup work, tasks that are undervalued in corporate ROI models but felt keenly by employees. A separate survey of enterprise AI users found that workers spend several hours per week correcting poor AI outputs, particularly in fields like data analysis and writing, where context and nuance matter greatly.

We want your views:

  • Worker Impact: In your organisation, how has AI affected your actual day-to-day workload. Has it saved time, created extra tasks, or both? Is that the same for all employees or does seniority make a difference.
  • Trust & Transparency: Do you feel you have enough information about when AI is used in your role and how it affects expectations and outcomes? If not, what would true transparency look like?
  • Human-AI Collaboration: Where has AI genuinely augmented your work versus where has it added correction, oversight, or rework, and how has that shaped your sense of value and agency?
  • Incentives & Design: Have the systems and incentives in your workplace encouraged responsible use of AI (e.g., clear accountability, meaningful oversight)? If not, what changes would help?
  • Fairness & Wellbeing: Have you seen or felt any unfair outcomes from AI deployment (e.g., uneven workload, bias, unrealistic performance expectations)? How has that affected morale or equity?
  • Ethics & Purpose: What ethical concerns about AI in your work matter most to you, from authenticity and trust to autonomy and job meaning,  and what should organisations do about them?

2 responses from the Newspage community

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Colette Mason
AI Ethics Consultant at Clever Clogs AI
The broader corporate enthusiasm for AI’s promise has collided with sobering financial realities: a global survey of nearly 4,500 CEOs finds only a small minority have realised both cost savings and new revenue from their AI investments to date, showing that profitability gains remain elusive amid widespread hype. If AI is to deliver real productivity, organisations must address deeper factors than tool deployment alone, including the incentives that shape work, how humans and machines collaborate, and what workers actually experience on the ground. The frustrations, adaptation burdens, and uneven benefits reported by workers reveal that the future of work will not be defined by automation alone but by how responsibly and transparently organisations bring AI into everyday tasks. Leadership on AI must shift from celebrating technological possibility to building systems that align incentives with human centred use and measurable outcomes that matter to workers and organisations alike.
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Rohit Parmar-Mistry
Founder at Pattrn Data
This survey finally puts a number on the 'AI tax' that most employees have been paying for years.

I’ve spent over a decade watching C-suite executives get seduced by boardroom demos that promise to slash hours off the work week. But the reality on the ground is starkly different. For many workers, AI hasn’t replaced their workload it has just replaced 'doing the work' with 'fixing the machine’s mistakes.'

The disconnect exists because leaders measure AI success by adoption rates, while workers measure it by frustration levels. When a VP hears 'AI generated this report in seconds,' they see efficiency. The employee who has to spend 45 minutes fact-checking that report for hallucinations sees a burden.

We are currently drowning in 'automation theatre' implementations that look futuristic but require constant human babysitting. Until companies stop treating AI like a magic button and start treating it like a junior employee that needs supervision, this productivity gap will only widen.