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Workday has released new global research showing that AI productivity gains are real but frequently diluted before they can make a difference to the bottom line.
The report says that employees are reclaiming time through automation, only for large portions of that capacity to be absorbed by rework, double-checking and patching-up generic outputs and avoid so-called "AI slop". In short, AI productivity is running ahead of job design, skills and workflows.
“While AI is delivering productivity gains, many organizations aren't fully capturing its value,” says the report.
Employees are saving meaningful time with AI tools, but too much of that capacity is being spent “fixing mistakes, rewriting content, and double-checking outputs from generic tools - leaving significant value on the table.”
The research, titled Beyond Productivity: Measuring the Real Value of AI, draws a line between deployment and impact. According to the study, “the most successful organizations don't just deploy AI - they reinvest the time it saves into their people.”
The differentiator between the way companies deploy AI is not usage alone, but how organizations use the time created by it to develop skills, redesign roles and modernize how work happens.
Gerrit Kazmaier, President, Product and Technology at Workday, links AI productivity directly to trust and human strengths.
“Too many AI tools push the hard questions of trust, accuracy, and repeatability back onto individual users,” he said.
“At Workday, we've spent years delivering AI as simple, human-centered solutions - not raw technology - so customers aren't left to wire things together and fact-check every answer on their own. Our philosophy is that AI should do the complex work under the hood so people can focus on judgment, creativity, and connection. That's how organizations turn AI-powered speed into durable, human-led advantage.”
AI productivity gains absorbed by rework
The research highlights what Workday calls the AI Productivity Paradox. AI is unquestionably speeding up tasks, but organizations are not yet equipped to convert that improved output into business impact.
“AI is delivering meaningful time savings, but that speed doesn't always translate into better outcomes,” it says.
Workday reports that 85% of employees report saving one to seven hours per week using AI, yet nearly 40% of AI time savings are lost to rework, including correcting errors, rewriting content, and verifying outputs from one-size-fits-all AI tools.
Only 14% of employees consistently get clear, positive net outcomes from AI.
“Employees who use AI every day are overwhelmingly optimistic - more than 90% believe it will help them succeed. But they also carry the biggest burden: 77% review AI-generated work just as carefully as work done by humans, if not more.”
Younger employees (aged 25–34) make up nearly half (46%) of those dealing with the most AI rework.
Training is not keeping up with usage. Workday’s report says that “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 - revealing a clear disconnect between leadership intent and employee experience.”
And that creates the so-called productivity paradox. Employees are using advanced tools inside outdated job structures.
According to Workday, in most organizations (89%), fewer than half of roles have been updated to reflect AI capabilities.
In other words: “Employees are using 2025 tools inside 2015 job structures.”
Treating AI time as a strategic resource
The second major theme in the report is reinvestment.
Most organizations agree that AI productivity should benefit their people, but the study finds that savings are flowing disproportionately toward systems instead of skills.
Companies are more likely to put AI savings back into technology (39%) than into employee development (30%). And instead of using time saved to build skills, many simply increase workload (32%).
Workday argues that the organizations realizing the greatest value from AI productivity are those treating saved time as strategic capacity rather than spare capacity.
“Employees with positive AI outcomes are far more likely to use saved time to increase the value of their work - through things like deeper analysis, stronger decision-making, and strategic thinking (57%) - rather than just taking on more tasks.”
These same employees are also “far more likely to have had increased skills training (79%).”
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The organizations utilizing AI in the most effective way reinvest in upskilling their teams, improving collaboration, and strengthening judgment-driven work.
Workday’s findings say that the biggest opportunity is helping employees learn how to use AI effectively - particularly in areas that require judgement, creativity, and decision-making.
Annie Rosencrans, People & Culture Director at HiBob, agrees that investment in learning and development is crucial to successful AI deployment and productivity gains.
She says: "HR teams should rethink internal training by leveraging AI like a collaborator, not just a tool. Learning programs should go beyond basic platform instruction to build AI literacy alongside human skills through hands-on, role-specific learning focused on prompt design, evaluating outputs, and recognizing bias, combined with decision-making and problem-solving practice. By embedding AI training into everyday workflows and supporting it with coaching and peer learning, HR teams can help employees use AI responsibly to enhance outcomes while preserving the uniquely human strengths that technology can’t replace.
"The biggest misconception about AI in the workplace is that AI will replace people, when in fact it’s meant to augment work and shift employees toward higher-value tasks.
“Employers can help by being transparent about AI’s role, investing in training on ethical use and critical evaluation, and modelling AI in leadership. When organizations frame AI as a partnership and support experimentation, employees can adapt with confidence and focus on the uniquely human skills that AI can’t replace.”
HR thought leader and analyst Josh Bersin, believes companies like HiBob and Workday will play a huge part in creating that transformation.
“The major HR platforms - Workday, SAP, Oracle, ServiceNow, HiBob, and others - are, on the whole, well-positioned for AI change and adoption, but that doesn’t guarantee success,” he says. “
“To stay relevant, they need deep AI talent, robust architectural integration, and data systems capable of supporting Super Agent functionality. If they rise to the challenge, we may see a new wave of investment and innovation in core HR systems; whether they can or not remains to be seen and could become one of the most significant factors in the industry over the next 12 months.”
