Observed Signal · Jun 18, 2021 · Market Research / Survey · Source: OnlineMarketing.de · Impact: 2/5 · Sentiment: Positive
Productivity over Waste: Germans Demand More Automation
A UiPath study of 4,500 office workers, including 500 in Germany, conducted in March 2021, finds that more than half of working time is spent on repetitive tasks. On average, 3.5 hours per week are wasted on tasks that employees feel could be automated. The data show 52% of respondents want more automation in their job, with especially strong demand for automating data entry (59%), scheduling calls and meetings (53%), and writing emails (43%). Sixty-five percent express strong interest in artificial intelligence. The study notes that 39% of employers have increased investment in automation software, and 77% of workers who received automation training improved their performance, while 72% would prefer to work for a company that enables learning. Tom Clancy, UiPath Senior Vice President of Learning, stresses the importance of automation and upskilling for a productive, engaging workday. The article also offers practical tips for employees and organizations to accelerate automation adoption.
Highlights widespread demand for automation and training; not tied to a major platform or policy.
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Key Takeaways & Evidence Grounding
- Survey of 4,500 office workers (including 500 in Germany) conducted in March 2021.
- Average 3.5 hours per week are wasted on repetitive tasks.
- 52% of respondents want more automation in their job.
- Automation opportunities cited: data entry 59%, scheduling calls/meetings 53%, writing emails 43%.
- 65% express strong interest in artificial intelligence.
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Germany Misses Enormous AI Potential
Germany currently lags in applying AI at work despite widespread private use, according to the Indeed and YouGov Workforce Insights study covering roughly 80,000 employees globally. In Germany, 59% use AI privately, above the global average of 52% and leading major economies like the USA (53%) and UK (45%). However, only 46% use AI in the workplace, creating a 13-percentage-point gap to private use (global gap 8 points). About 34% report that AI has not been adopted or is insufficiently supported in their company, slightly above the global 33%. The study finds notable productivity potential: regular German AI users save about 1.7 hours per week (≈90 hours per year) and report 72% experiencing more automated workflows and 63% noting gains in innovation and problem solving. The results underscore the need for infrastructure, training, and strategic alignment to bridge the gap between employee readiness and corporate adoption.
AI in IT: 89% report productivity gains, but disparities persist
A new survey by Snowflake, involving 200 data and IT professionals from companies with over 500 employees, including 150 from Germany, reveals that 85% of respondents use AI daily. 89% report increased productivity and 87% say AI saves time rather than creating extra work. However, the benefits are uneven: 68% of executives feel a noticeable relief, compared to only 55% of non-managerial staff. Conversely, 20% of individual contributors say AI has increased their daily workload, versus 11% of executives. Looking ahead, 89% believe AI will further improve their company's working methods in the next two years. Snowflake's Germany Country Manager, Jonah Rosenboom, emphasizes that merely introducing AI tools is insufficient; companies must address foundational systems to fully realize AI's benefits.
AI fatigue: Nearly three-quarters prefer pre-ChatGPT work
A survey by technology consultancy Adaptavist of 2,500 knowledge workers (500 in Germany) finds growing "AI fatigue." In Germany nearly three quarters say they long for the pre‑generative‑AI workplace and 41% would prefer generative AI abolished. Respondents cite poor-quality outputs: 45% say results make work feel less meaningful, 37% report lower motivation, and 25% say their creativity is constrained. Many flag productivity hits—39% in Germany spend more time checking AI than they save, 42% say poor outputs slow projects, and 49% see team efficiency harmed. The article references an OpenAI analysis of over 800,000 messages and industry warnings about job risk, while noting a tension as a majority still want their company to expand AI use.
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