Much of the discussion around AI tools has centered on productivity. These discussions have ranged from notions of AI supporting the human workforce to become more productive (doing more with less), to human + AI collaborative relationships that supercharge efficiency, to doomsday predictions where AI is productivity manifest, and humans are well and truly out of the loop.
Well, the direction of travel is certainly not about eliminating human ingenuity but instead pairing human intelligence with AI. However, the importance of productivity is being matched by other perceivable outcomes, like developing new business models, improving the customer experience, and forecasting, as well as employee development made possible when AI does the heavy lifting.
So, what’s next in terms of value creation, and where are companies going wrong? That’s what a new report from Workday, Beyond Productivity: Measuring the Real Value of AI, sets out to answer.
Study Overview and Methodology
To compile the data for the report, Workday gathered responses from 3,200 full-time employees at organizations using AI technologies and with annual revenue exceeding $100M across North America, APAC, and EMEA. Overwhelmingly, the report found that companies deploying AI tools ARE achieving the productivity gains they set out to achieve. Still, in a vast number of cases, these gains are being eaten up by the work required to optimize the output.
The report found that companies winning the AI game are not simply introducing tools, but ensuring a sustained business impact by investing time saved through productivity gains back into people. While AI has introduced significant productivity gains, many companies have failed to implement measures to advance and revisit roles, skills, and business processes to optimize results.
Here are some of the key findings from the report to support Workday’s conclusions:
- 85% of respondents save one to seven hours per week thanks to AI deployments.
- Close to 40% of these savings are depleted through time spent on revisions, such as error correction, content rewriting, and verification. Just 14% of respondents “consistently get clear, positive net outcomes from AI.”
- 90% of daily AI users are confident in the tools’ capabilities to help them achieve better results, yet 77% review AI-generated outputs to the same or greater degree than they do human-generated work.
- 66% of leaders believe skills training is a top priority, but only 37% of employees responsible for rework can access it, while 89% of companies have updated fewer than 50% of roles to match the introduction of AI.
People vs. Technology
According to the report, instead of reinvesting in workforce development (30%), more companies are investing in technology (39%). Business owners who choose the employee route are seeing higher returns.
When AI is optimized, 57% of employees use it to create greater value through analysis, strategy, and decision-making, and are 79% more likely to have received additional skills training.
“Too many AI tools push the hard questions of trust, accuracy, and repeatability back onto individual users,” said Gerrit Kazmaier, President, Product and Technology, Workday.
“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.”
Closing Thoughts
What stands out most to me in this report is the focus on the human workforce: many other AI-related studies have focused on the value of AI in technology. However, as the conversation shifts to the inevitable human + AI future, research like this is incredibly important because it realigns the narrative to consider the massive business gains of upskilling, not just deployment.
This report flips the notion of massive AI investments on its head. Yes, it argues for better investment in AI, but not only at the technical level, but with a focus on a people-led approach. Instead of being a complementary strategic decision, empowering users with the skills to do more with AI is, as argued by the report, “the fastest way to reduce rework, improve outcomes, and turn AI speed into lasting business value.”
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