Some research doesn’t shout. It nudges you, then lingers. You sit with it for a moment. You feel a shift in how you view the work we ask AI to do and the results we expect it to deliver.
This study created that shift.
A recent working paper on AI adoption in Denmark did exactly that. The researchers, based at the University of Copenhagen and the Center for Economic Behavior and Inequality, followed more than 12,000 workers across 2023 and 2024 as they brought AI chatbots into their daily routines.
The questions they tried to answer seemed simple: How much time do people actually save when they use these tools? What changes in their workweek? And do those changes ripple into wages or employment?
However, the answers painted a more nuanced story than many anticipated.
Surprise One: Time Savings Were Modest
Workers reported only modest improvements, roughly 2.8 percent of their weekly hours. A little over an hour. That figure matters because it contrasts with the sweeping efficiency gains often featured in headlines. Instead of instant transformation, we see gradual shifts. Small adjustments. A slow accumulation of benefits. The distance between hype and lived experience becomes visible, and it invites us to ask why progress feels steadier than expected.
Surprise Two: Labor Market Effects Remain Flat
The study also found no meaningful movement in wages or hours worked, even in fields that adopted chatbots quickly. Nothing spiked. Nothing dropped. Things simply held steady. This stability stands out. It reminds us that tools rarely transform work on their own. People reshape processes. Systems evolve. Incentives shift. When those elements move slowly, technology advances at a different pace than organizational behavior.
Surprise Three: New Tasks Emerge and Offset Gains
A share of workers said AI created entirely new tasks. Verifying AI output. Detecting AI use in student assignments. Experimenting with prompts to refine quality. These tasks absorbed time, which then offset the gains from the chatbot itself. It’s a familiar pattern. Each new tool brings work around the work. It’s the unexpected labor that makes the tool productive but also delays the upside.
Understanding the Macro Picture
These findings point toward a larger story about where we are in this transition. Many teams still treat AI as an accessory rather than a catalyst. They plug a chatbot into an existing workflow without redesigning the workflow itself. That approach limits impact. Deep integration takes time, experimentation and a willingness to rethink long standing habits.
The tools themselves also continue to evolve. Today’s chatbots handle writing and reasoning, but they sit somewhat isolated from the systems that run core operations. As those connections strengthen, friction falls. The value of AI grows when it becomes part of an ecosystem rather than a standalone helper. This is one area where tools like Civic Nexus will continue to help. Civic Nexus supports a broader streamlining of workflows, so that more efficiencies can take place across teams.
Steps to Unlock Real ROI
Leaders can still take clear action. Start with the work, not the job titles. The workflows. When teams map how work actually moves from start to finish, they spot repetition, slow points and needless handoffs. AI creates value when it enters this flow with intention. Redesign often sparks more progress than direct replacement.
Then cultivate a culture that supports new patterns of work. People need space to learn and experiment. They need shared understanding about when AI helps and when it distracts. When teams feel supported, they adopt new habits with confidence. Culture becomes the bridge between technology and meaningful improvement.
Supporting the Bigger Shift
As organizations pursue AI powered operations, they will seek tools that integrate cleanly, reduce shadow work and strengthen accountability. They will look for solutions that adapt to the real choreography of their processes.
Civic Nexus supports that shift. It helps teams apply AI in ways that streamline the work they already perform, while opening the door to more coordinated and efficient systems.
If you want AI that truly delivers, start by understanding the work. Then choose tools that help your people move through it with clarity and momentum.
