Generative AI (GenAI) is increasingly becoming a pivotal topic in discussions around productivity and the future of work. Despite its rapid diffusion, systematic firm-level evidence is still limited, reflecting the technology’s novelty. Recent task-based studies have documented significant performance gains in specific activities, but translating these micro-level findings into broader estimates of aggregate productivity remains a challenge.
Utilizing the Bundesbank Online Panel – Firms (BOP-F), a representative survey of the German corporate sector, we analyzed data from the second quarter of 2025, encompassing over 7,000 firms across manufacturing and services. This survey documents firms’ past, present, and planned GenAI adoption, associated costs, and perceived impacts on productivity, employment, and wages. The results reveal rapid growth in GenAI adoption among German firms, with the share of businesses employing or planning to adopt the technology jumping from 26% in 2024 to 44% in 2025 and projected to reach 56% in 2026.
Moreover, the survey measured GenAI usage intensity by calculating the share of total working hours employees use generative AI. Among early adopters, the average share of working time involving GenAI is expected to rise from about 7.5% in 2024 to 10.2% in 2025 and further to 12.6% in 2026. This growth is largely attributed to incumbent firms deepening their use, while new adopters typically start with lower intensity. Consequently, although many firms are integrating GenAI, the average increase in usage intensity is tempered by the lower participation of new entrants.
A critical question arises regarding how this swift adoption affects AI-related expenditures. Firms reported that average spending on GenAI as a share of annual sales would rise from approximately 1.0% in 2024 to 1.5% in 2026. Overall, this translates to an increase in aggregate AI-related expenditures within the German economy, expected to rise from 0.3% of total sales in 2024 to 0.8% by 2026, positioning GenAI spending on par with traditional digital investment categories.
Cost and intensity are closely linked, but the data suggest a concave cost-intensity relationship. Firms with lower expenditures, including those utilizing free tools or low-tier subscriptions, have already begun to report notable GenAI use. As expenditures increase, the intensity rises but at a diminishing rate, indicating that initial, easily scalable applications may deliver the bulk of immediate benefits. This pattern suggests that as organizations integrate GenAI more deeply, they face diminishing returns when the most straightforward applications are exhausted.
Notably, a significant portion of GenAI spending is directed toward ongoing operational costs rather than one-off implementation expenses. Most firms report that less than 25% of their total expenditure on GenAI is allocated to initial setup costs like external consulting and hardware. This trend indicates a move towards recurring subscriptions and permanent staff, which in turn suggests implications for how AI-related expenditures are measured and their sensitivity to cash-flow conditions.
In assessing the economic impacts of GenAI, two key findings emerge from firms’ projections. First, among current and prospective adopters, productivity expectations are largely optimistic. The percentage of firms anticipating at least a 2% increase in labor productivity rises from 46% in 2024 to 54% by 2026. This aligns with the macroeconomic literature that generally views AI as a significant driver of growth potential.
Second, concerning labor market impacts, firms foresee modest gains in high-skill employment alongside a gradual increase in wages. While about two-thirds of firms expect changes in high-skill employment to remain within ±1%, 28% are anticipating growth of at least 2% by 2026, contrasting with only 8% predicting declines. This highlights the belief that GenAI may complement high-skill work, while expectations for low-skill roles remain more balanced.
Overall, while wage expectations remain stable, a shift toward anticipated growth is evidenced by an increase in the percentage of firms expecting wage increases of 2% or more, from 19% in 2024 to 26% in 2026. This suggests that firms expect the benefits of GenAI adoption, such as task complementarities, to counteract any displacement effects.
This analysis underscores the growing importance of GenAI in shaping the future of work and highlights both the opportunities and challenges that come with its adoption in the corporate landscape.
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