AI Time Savings Fail to Deliver ROI: Workday

AI is saving employees hours each week, but many organizations are failing to convert that time into lasting business value, according to new global research released by Workday.

According to BCG, only a small share of companies are fully prepared to capture value from AI. About 5% are “AI future-built” and see significantly higher revenue growth and cost reductions, while 35% are beginning to scale AI and generate value. In contrast, roughly 60% of companies report limited returns from AI despite heavy investment, highlighting a wide gap between AI leaders and laggards.

Research from Workday helps explain this divide. In its study, Beyond Productivity: Measuring the Real Value of AI, Workday argues that while AI tools are increasing speed and capacity, a significant share of those gains is absorbed by rework, including correcting errors, rewriting content, and verifying outputs produced by generic AI systems. As a result, productivity improvements often do not translate into better outcomes or stronger returns on investment.

“Our interaction with AI has been fundamentally reactive, limited by the "chat box" that accustomed us to requesting isolated tasks,” writes Selene Diez, CEO, Forte Innovation Consulting, on MBN.

This challenge is emerging even as AI adoption accelerates across organizations. The share of companies running processes primarily driven by AI almost doubled over the past year, and workplace use of AI has also risen sharply since 2023. Despite that expansion, a recent MIT Media Lab report also found that 95% of organizations have yet to achieve a measurable return on their AI investments.

Workday’s research shows that 85% of employees report saving between one and seven hours per week using AI. However, nearly 40% of those time savings are lost to rework, creating what Workday describes as a productivity paradox. Only 14% of employees consistently report clear, positive net outcomes from AI use.

The gap between potential and impact, the report suggests, is not driven by the technology itself but by how organizations deploy it. Many companies have introduced AI without redesigning roles, updating processes, or investing sufficiently in workforce skills, leaving employees to reconcile faster output with outdated job structures.

“Too many AI tools push the hard questions of trust, accuracy, and repeatability back onto individual users,” says Gerrit Kazmaier, President of Product and Technology, Workday. He adds that the company’s approach focuses on embedding AI into workflows so employees are not required to manually validate every output, allowing them to focus on judgment, creativity, and decision making.

“AI can enhance what a small team can accomplish, freeing people to focus on higher-value work that requires human ingenuity and creativity," writes Roberto Peñacastro, CEO, Leadsales, on MBN.

The burden of rework is not evenly distributed. Employees who use AI daily are largely optimistic about its potential, with more than 90% saying it will help them succeed, yet 77% say they review AI-generated work as carefully as, or more carefully than, work produced by humans. Younger professionals are particularly affected: workers aged 25 to 34 account for 46% of those experiencing the highest levels of AI-related rework.

“AI is reshaping work at extraordinary speed. Workers are largely energized by AI’s possibilities, but organizations must rethink how they operate or risk missing the broader value AI can deliver,” says Matt Rosenbaum, Principal Researcher, The Conference Board’s Human Capital Center.

Meanwhile, enterprises face growing pressure to deliver measurable returns from AI investments. Globant reports that by 2026, AI will function less as a tool and more as an operating system across cybersecurity, logistics, finance, and knowledge management. Yet analysts emphasize that ROI depends on governance, skills, and human judgment rather than automation alone.

The World Economic Forum estimates that nearly 40% of job skills will change by 2030, driven largely by advances in AI, data analytics, and automation. In Mexico, this transition has intensified pressure on companies that report difficulty finding candidates with job-ready technical competencies, reports MBN. Training gaps further limit the value organizations derive from AI. 

While 66% of business leaders identify skills training as a top priority, only 37% of employees facing the most rework say they have access to such training. In addition, 89% of organizations report that fewer than half of their roles have been updated to reflect AI capabilities, effectively placing new tools into legacy job designs. 

The study also highlights how companies choose to reinvest AI-driven time savings. Organizations are more likely to reinvest in technology upgrades, cited by 39% of respondents, than in employee development, cited by 30%. In many cases, time saved through AI is used to increase workload rather than to deepen skills or improve work quality.

“Businesses must invest in the humans who provide the creative spark and judgment that the models just cannot replace,” says Dan Diasio, Global Consulting AI leader, EY.

By contrast, organizations seeing stronger results treat time saved as a strategic resource. Employees who report positive AI outcomes are significantly more likely to use that time for higher-value activities such as analysis, decision making, and strategic thinking, and 79% of them report having received increased skills training.

“As CEOs, our focus should not only be on financial ROI, but on the reconfiguration of human capital,” says Diez. “The goal is to free up that 90% of time that was lost in bureaucratic and research processes to reinvest it in strategic vision and ethics.” 

The findings are based on a global survey of 3,200 full-time employees conducted in November 2025 by Hanover Research on behalf of Workday. Respondents were based in North America, Asia-Pacific, and the European Union, the Middle East, and Africa, and all worked at organizations with at least US$100 million in annual revenue and active AI use.

According to the report, the fastest way to turn AI-driven speed into sustained business value is not broader deployment, but deeper investment in people, processes, and roles that allow organizations to fully absorb the capacity AI creates.