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6 ways to stop cleaning up after AI - and keep your productivity gains
Publish Time: 16 Jan, 2026
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Key takeaways

  • 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.

The ultimate AI productivity paradox

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.

How to protect AI productivity gains

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:

  1. Invest in people: Companies are more likely to put AI savings back into technology (39%) than into employee development (30%). "Instead of using time saved to build skills, many simply increase workload (32%) -- leaving employees to navigate AI on their own." Those companies that reinvest their AI gains into their people "outperform those that reinvest primarily in technology, achieving stronger outcomes and more sustainable value."
  2. Ramp up AI-related training: While 66% of leaders cite skills training as a top priority, only 37% of employees experiencing the highest amount of rework say they're getting access to it. Training is part of that all-important investment in people that needs to be made. More than 54% of struggling users report their required skills haven't been updated.
  3. Update job roles: Jobs are still stuck in 2015, the survey's authors state. "AI has been layered onto roles that were never updated to accommodate it." In most organizations (89%), fewer than half of roles have been updated to reflect AI capabilities. "Employees are left to reconcile faster output with unchanged processes or systems, with unchanged expectations around accuracy, judgment, and accountability."
  4. Rethink how AI productivity is measured: Don't just assume that five hours saved in a task means five hours of additional productivity. "Evaluate productivity in terms of value created -- accounting for both time saved and time lost to rework," the study urges. "In practice, this means prioritizing outcome-based measures over speed."
  5. Update roles to reflect AI-enabled work: Don't just drop AI processes into people's workloads. "Many employees are using advanced tools within job structures that were designed before AI adoption." What is needed is an effort to update roles and job descriptions to clarify where AI is expected to assist and where human judgment is essential.
  6. Use AI-enabled time to strengthen human connection: Leaders in AI adoption "explicitly authorize employees to use saved time for activities that improve collaboration, learning, and strategic thinking -- not just increased task volume."

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."

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