AI productivity paradox: Workers lose 37% of time savings fixing AI mistakes and low-quality output

6 ways to stop cleaning up after AI - and keep your productivity gains

37% of time saved through AI is lost to fixing low-quality output.Employees say they do not receive enough AI training.Needed: more investment in people and job redesigns. AI giveth, and AI taketh away, especially when it comes to productivity. Also: Is AI's war on busywork a creativity killer? What the experts say That's the lesson being learned among employees and executives responding to a new survey by Workday. While AI is delivering productivity gains, those gains are being partially washed away when technologists or employees need to go back to implementations to fix mistakes, rewrite content, or double-check outputs. At least 37% of time savings gained through AI are lost to fixing low-quality output, according to the survey's authors, which included the experiences of 3,200 practitioners. Often, AI practitioners and advocates are flummoxed as to how deeply an AI application should go for the task at hand. "Don't build an agent when a basic chat will do," development guru Corey Noles explained in a recent webcast. All too often, people will spend an inordinate amount of time attempting to build a complex AI system when a simple prompt may do the trick. It takes some level of expertise and training to understand the difference and the best approaches. Also: The AI complexity paradox: More productivity, more responsibilities It's the ultimate AI productivity paradox, the Workday authors argue. The speed gained through AI's time savings "doesn't always translate into better outcomes." At least 85% of employees report saving one to seven hours per week using AI. However, the follow-up rework required washes out the savings -- to the tune of an average 1.5 weeks a year spent fixing AI outputs, the survey analysts estimate. Only 14% of employees consistently achieve net-positive outcomes from AI use, they add. Also: Your colleagues are sick of your AI workslop In addition, it's noted that the most prolific AI users often carry the highest burden, spending disproportionate time verifying and correcting output. More than 90% of employees who use AI every day believe it will help them succeed, the survey also shows. Most, 77%, review AI-generated work just as carefully as work done by humans, if not more. At the root of the problem, they say, is that roles, skills, and processes haven't caught up with the new ways of working and doing business brought on by AI. Here are their recommendations on reducing the afterwork washing out AI productivity gains: Also: Worried AI will take your remote job? You're safe for now, this study shows The organizations realizing the greatest value from AI "treat saved time as a strategic resource," the Workday team states. "They reinvest in upskilling their teams, improving collaboration, and strengthening judgment-driven work. The biggest opportunity is helping employees learn how to use AI effectively -- especially in areas that require judgment, creativity, and decision-making."

Cleaning up "AI workslop" is costing businesses hundreds of hours a week

AI training should be compulsory, and processes should be standardized Despite the perceived productivity benefits, many businesses are spending time and money cleaning up "AI workslop," suggesting the tech generates a lot of unnecessary noise, new research has claimed. Data analysis and visualizations (55%), research and fact-finding (52%), long-form reporting (52%) and writing and marketing content (44-46%) are some of the most common areas where AI tools might not be as effective as companies once hoped. Even though 92% agree AI improves their overall productivity, only 2% say that AI outputs need no revision. Three in five (58%) spend more than three hours per week revising outputs, with more than one-third (35%) spending more than five hours and 11% spending over 10 hours every week tidying up generated content. The research from Zapier adds that AI generally lacks accuracy, context or usefulness despite appearing polished on the surface. And it's not just perception that's down - many have experienced rejected work (28%), security or privacy incidents (27%), customer complaints (25%) and compliance or legal issues (24%). Zapier's data indicates two potential solutions - firstly, AI models must continue to be improved to improve the quality of responses. But in the meantime, workers should be upskilled to handle AI in its current format, and not what it should be. "The companies seeing the best results aren't the ones avoiding AI," Senior AI Automation Engineer Emily Mabie explained. "They're the ones who have invested in training, context, and orchestration tools that turn AI from a sloppy experiment into a managed process." Nearly all (94%) of trained workers say AI boosts productivity, but only 69% of untrained workers agree. As a result, only 1% of trained workers say their productivity has dipped. Looking ahead, the report calls for AI training to be compulsory for all workers that handle it, prioritizing high-risk teams and tasks in the first instance. Companies can also help employees by providing prompt templates and formalizing reviewing processes. "The solution isn't fewer tools, it's better infrastructure," Mabie concluded.

AI speeds up work and creates more of it

Why it matters: The promise of AI is that it makes work more productive, but the reality is proving more complex and less rosy. Zoom in: For employees, AI is both speeding up work and creating more of it, finds the report conducted by HR software company Workday last November. * 85% of respondents said that AI saved them 1-7 hours a week, but about 37% of that time savings is lost to what they call "rework" -- correcting errors, rewriting content and verifying output. * Only 14% of respondents said they get consistently positive outcomes from AI. * Workday surveyed 3,200 employees who said they are using AI -- half in leadership positions -- at companies in North America, Europe and Asia with at least $100 million in revenue and 150 employees. Reality check: The report did not specify which AI products respondents were using or which companies built them. Zoom out: "There is a big productivity paradox," Gerrit Kazmaier, president of product at Workday, tells Axios. * The most frequent users of AI, he says, are the ones investing the most time in reviewing and correcting what it produces. * The findings line up with other studies that call AI productivity gains into question -- from MIT and Harvard Business Review. * The term "workslop" has caught on for a reason. Friction point: Typically, the better someone gets at using a technology, the more efficient they become. But with AI, as you get more proficient, you start to understand more about the ways in which the tech can go wrong, Kazmaier says. * He points to people who might run the same prompts across multiple AI models -- and check the outcomes against each other. The big picture: CEOs and employers are super eager to reap the productivity benefits of AI -- particularly so they can bring down labor costs. * But for now, AI is mainly being used as an excuse to conduct layoffs that are due to other factors, says Rob Hornby, co-CEO of consultancy AlixPartners. * In a survey, also out Wednesday from his firm, 95% of CEOs said they expected to conduct layoffs in the next five years because of AI. That's likely more hope than reality. CEOs aren't yet seeing productivity gains from AI, he says. Yes, but: There are some productivity benefits to AI in some specific niche areas, like some types of low-level commoditized writing, he says. But overall, "we're having a tough time proving out real productivity benefits," Hornby says. * Plus: AI tools are rapidly getting better at doing real-world work, so the problem could soon resolve itself. Anthropic's new tool designed to automate rote office tasks was created in less than 1.5 weeks and the code was written entirely by AI. Between the lines: Incorporating and using a new technology effectively simply takes a lot of time -- ask anyone who lived through the advent of the Internet. * It takes time for employees to learn new tools, for employers to integrate them and for businesses to build products that actually make them useful. * Workday and other enterprise tech firms are trying to sell AI-based software products to solve that latter piece. The bottom line: AI is creating a productivity paradox -- speeding up work, while quietly adding more of it.

Workers spend hours hours fixing AI mistakes, study says

Artificial intelligence is saving workers time, but a large share of those gains is being erased by the effort required to fix AI-generated mistakes, according to a new study. The report by Workday $WDAY, based on a November survey of 3,200 employees across North America, Europe, and Asia, found that 85% of respondents said AI saved them between one and seven hours a week. However, Workday said roughly 37% of that time is lost to "correcting, clarifying, or rewriting low-quality AI-generated content," creating what the company described as an "AI tax on productivity." "For every 10 hours of efficiency gained through AI, nearly four hours are lost to fixing its output," the report said. As a result, "productivity gains alone are not translating into better outcomes for most organizations," it said. Only 14% of employees surveyed said they "consistently achieve net-positive outcomes from AI use," according to the study. The burden is not evenly distributed, with the most frequent AI users often spending the most time reviewing and correcting its output. Highly engaged employees lose an average of about 1.5 weeks a year to rework, Workday found. "There is a big productivity paradox," Gerrit Kazmaier, president of product at Workday, told Axios. The report said the problem is structural rather than behavioral. AI has been "layered onto roles that were never updated to accommodate it," forcing employees to reconcile faster output with unchanged expectations around accuracy and accountability. Nearly 9 in 10 organizations said fewer than half of their roles have been updated to include AI-related skills. The study also found a disconnect between leadership priorities and employee experience. While 66% of leaders cited skills training as a top investment priority, only 37% of employees most exposed to AI-related rework said they had increased access to training. Workday said organizations seeing sustained gains from AI are those that reinvest productivity savings into workforce development and clearer role design. "Paying a high tax on AI efficiency is not inevitable," the report said. "It is the cost of implementing AI without investing in the humans who use it."