AI's Productivity Promise Falls Short, New Study Reveals

AUSTIN, TX – March 11, 2026 – The corporate world has widely embraced artificial intelligence as the next frontier in productivity, but a new report suggests the promised gains are largely an illusion, consumed by a hidden tax of verification and review. According to a study released today by Foxit Software, the time employees spend fact-checking and correcting AI-generated content often negates any time saved, creating a significant disconnect between executive perception and the daily reality for workers.

The report, titled "The State of Document Intelligence," surveyed 1,400 executives and desk-based users across the U.S. and U.K. and found that while a staggering 89% of executives believe AI has made them more productive, their net time savings amount to a mere 16 minutes per week. For the end-users on the front lines, the situation is even more stark: they report a net loss of 14 minutes weekly.

These findings challenge the prevailing narrative of AI as a simple plug-and-play solution for efficiency, exposing a more complex and nuanced relationship between human workers and their new digital counterparts.

The Validation Burden: AI's Hidden Workload

The core of the issue lies in what the report calls the "validation burden." While AI tools can generate reports, summaries, and other documents in seconds, the output often requires meticulous human oversight. Executives in the study estimated that AI saves them 4.6 hours per week, but they then spend 4 hours and 20 minutes validating those outputs. Similarly, end-users believe they save 3.6 hours, only to spend 3 hours and 50 minutes reviewing the work.

"AI accelerates creation, but it introduces new layers of review, fact-checking and correction," said Evan Reiss, senior vice president of marketing at Foxit Software, in the press release. "Work is not disappearing. It is being redistributed."

This pattern of perception versus reality holds true across different markets. U.S. respondents, on average, experienced a net time loss of 10 minutes per week. Their counterparts in the U.K. fared slightly better but still saw only a marginal gain of two minutes. The data suggests that as organizations rush to integrate AI into document workflows, they are inadvertently creating a new, time-consuming task: babysitting the algorithm. This reality stands in contrast to other research, such as a report from the Federal Reserve Bank of St. Louis, which found that heavy AI users could save four or more hours per week, suggesting that proficiency and frequency of use may eventually lead to more significant gains.

A Chasm of Trust and Awareness

Beyond the numbers, the study reveals a deep-seated chasm in confidence and awareness between the C-suite and the cubicles. The primary barriers to deeper AI adoption are not technical but human-centric: 36% of all respondents cited data privacy and security, followed closely by trust in AI output (34%) and concerns over accuracy (25%).

This trust deficit is sharply divided by seniority. While 60% of executives claim to be "highly confident" in AI-generated outputs, only a third of end-users feel the same. The gap widens further when looking at extreme confidence, with one in four executives describing themselves as "extremely confident," compared to just one in ten end-users. This creates a risky dynamic where executive overconfidence could clash with frontline caution within the same workflow.

This disconnect extends to the future of work itself. The report found that 68% of executives acknowledge that AI adoption has already triggered restructuring or headcount changes within their organizations. Furthermore, 72% cite retraining and upskilling as a top priority. Despite these significant shifts happening at the leadership level, the message appears lost in translation. Only 12% of end-users reported being "very concerned" about their job security in the face of AI, indicating a profound awareness gap that could leave many employees unprepared for the changes ahead.

Redefining Success: From ROI to Return on Employee

As companies grapple with the true impact of AI, many are realizing that traditional metrics are insufficient. The study highlights a pivotal shift in how businesses evaluate technology investments, with "Return on Employee" (ROE) emerging as a critical counterpart to the long-standing "Return on Investment" (ROI). An overwhelming 93% of organizations surveyed now track ROE dimensions.

Unlike ROI, which focuses on financial gains, ROE measures the human impact of technology. It captures improvements in employee capability, job satisfaction, confidence, and overall well-being. This human-centric framework acknowledges that the success of AI is not just about automating tasks but about augmenting human potential. Industry analysts at firms like Gartner have noted this trend, defining ROE as applying AI to boost personal productivity and engagement, even if it doesn't yield a direct, immediate financial return.

This shift suggests that leading organizations are beginning to understand that sustainable AI adoption requires investing in their people. The ultimate value of AI may not be found in how many hours it saves, but in how it empowers employees to be more skilled, confident, and engaged in their work. Both executives and end-users in the study agreed on the importance of preserving human problem-solving skills, with over-reliance on AI for decision-making ranking as a top concern for both groups.

Building a More Trustworthy Future

The path forward, as suggested by the research, is not to abandon AI but to build it better. The future of document intelligence will hinge less on adding more features and more on improving accuracy, enabling seamless integration, and fundamentally reducing the validation burden that currently plagues users.

"The success of document intelligence relies as much on human confidence as on technical performance," Reiss noted. "Accuracy, transparency and clear human-in-the-loop design are the foundations of trust and therefore the foundations of adoption."

In response, technology providers are beginning to embed intelligence more thoughtfully into existing systems. The goal is to create AI assistants that don't just generate content but also "show their work" by providing citations and explanations, operating within the secure, familiar software employees already use. By designing AI to support and enhance human judgment rather than replace it, companies can begin to close the trust gap, reduce the verification workload, and unlock the true, collaborative potential of a human-AI workforce.