Artificial intelligence is raising expectations of workforce productivity, but the anticipated efficiency gains are not necessarily translating into reduced workloads or lower operating costs. According to the Factorial Business Facts Index 2026, 70% of surveyed executives in Germany have increased their performance expectations since introducing AI, while 67% report that workloads have remained unchanged or increased. The findings, drawn from a wider survey of 3,760 business leaders across five European countries, highlight a growing economic challenge: companies risk increasing their technology expenditure without addressing the organisational inefficiencies that limit productivity.
The study, conducted with market research company Dynata in August 2026, surveyed executives and decision-makers in Germany, France, Italy, Spain and Portugal. Approximately 750 respondents were based in Germany. Only 27% of German participants reported a reduction in workload following AI adoption, while 80% expected the technology to change how their companies operate within the next twelve months. These figures relate specifically to Germany and should not be interpreted as representative of European businesses as a whole.
Key figures: AI, productivity and operational costs
| Indicator | Survey finding |
|---|---|
| Higher performance expectations | 70% of German executives |
| Unchanged or increased workloads | 67% of German executives |
| Reduced workloads following AI adoption | 27% of German executives |
| Time spent retrieving existing information | 48.5% of German executives spend 20–30% of working time on these activities |
| Overlapping software subscriptions | 43.7% of German executives report paying for applications with largely identical functions |
| Disconnected business systems | 60% of surveyed European executives work with tools that do not share data |
| Estimated annual cost of inefficient management time | €444,454 for a model German company with 1,000 employees; approximately €383,000 in Factorial’s European benchmark |
Source: Factorial Business Facts Index 2026. German indicators refer to the national sample; European indicators cover the five surveyed countries. Financial figures represent estimated labour-time costs, not verified savings or direct financial losses.
Fragmented systems create hidden operating costs
Beyond rising performance expectations, the study identifies poor integration between business applications as a significant source of inefficiency. Almost half of surveyed European business leaders report spending between two and three hours out of every ten retrieving existing information or repeating operational tasks. Factorial estimates that this fragmented way of working represents approximately €383,000 in annual management labour costs for a model company with 1,000 employees, while the corresponding German calculation reaches €444,454.
These figures require careful economic interpretation. Time spent on inefficient processes does not automatically translate into an equivalent financial loss that can be recovered through automation. Direct savings arise only when companies can reduce expenditure, avoid additional staffing requirements, improve output or redirect employee capacity towards higher-value activities. Nevertheless, the estimates illustrate the potential opportunity costs associated with disconnected software environments and duplicated administrative work.
The problem is particularly relevant as companies expand their AI investments. Additional applications can introduce new licensing, integration, maintenance and training costs, particularly when they operate alongside existing systems with overlapping capabilities. According to the German survey results, 43.7% of executives report software subscriptions with substantially duplicated functions, while 72.4% believe fewer, more centralised applications could improve organisational efficiency.
Europe’s AI investment challenge goes beyond adoption
The findings emerge against a backdrop of accelerating AI adoption across the European economy. According to Eurostat, 20% of EU enterprises with at least ten employees used AI technologies in 2025, compared with 13.5% in 2024. Adoption varies considerably between member states, with Denmark, Finland and Sweden reporting substantially higher usage rates than several countries in Central and Eastern Europe.
For European businesses, the challenge is therefore not simply to introduce additional AI capabilities. It is to demonstrate that these investments produce measurable operational improvements. Companies need to assess implementation and recurring costs alongside processing times, error rates, software utilisation and the productive use of employee capacity. Where fragmented data and inefficient workflows remain unresolved, AI may accelerate individual tasks without improving the overall economics of business operations.
The Factorial study measures executives’ assessments rather than independently verified productivity gains or investment returns. It therefore cannot establish whether AI itself is responsible for changes in workload or financial performance. Its broader economic message, however, is significant: higher performance expectations are not evidence of higher productivity, and greater technology spending is not a substitute for organisational efficiency. For European companies seeking sustainable returns from AI, better integration of systems and processes may be just as important as the capabilities of the technology itself.
Sources: Factorial Business Facts Index 2026, based on 3,760 executives and decision-makers surveyed in Germany, France, Italy, Spain and Portugal in August 2026; Factorial’s German market findings published on 28 October 2026; Factorial analysis of fragmented software costs, October 2026; Eurostat, AI adoption in EU enterprises, December 2025. Financial estimates are derived from the study’s modelling assumptions and should not be interpreted as audited company losses.
