Global Study Highlights Early Impact of AI on Businesses
The most extensive international research on artificial intelligence’s influence at the firm level has been released, offering a more positive outlook than many anticipated. The study, surveying nearly 6,000 verified executives across four countries, shows that AI has prompted modest changes in productivity and employment over the last three years. These results reflect the initial stages of AI deployment rather than technological shortcomings.
Widespread AI Adoption Across Industries
According to the study published by the National Bureau of Economic Research and conducted by teams from the Federal Reserve Bank of Atlanta, the Bank of England, the Deutsche Bundesbank, and Macquarie University, approximately 69% of companies are already utilizing some form of AI. Popular applications include large language model (LLM) based text generation (41%), machine learning for data processing (28%), and visual content creation (29%). In the UK alone, firm-level AI adoption increased from 61% to 71% between 2024 and 2025.
Measured Productivity Gains and Employment Changes
The impact on productivity so far has been incremental, consistent with the adoption patterns of previous general-purpose technologies. Over 90% of firms reported no significant headcount change due to AI in recent years. However, executives expect more pronounced effects in the next three years, forecasting an average 1.4% productivity increase and a 0.8% rise in output. Notably, US executives predict a 2.25% gain in productivity, while UK firms anticipate a 1.86% increase.
Regarding employment, executives foresee a modest 0.7% reduction in workforce numbers across the surveyed countries. In the UK, this adjustment is expected mainly through slower hiring rather than layoffs, indicating a gradual reallocation of roles. New positions related to AI, such as data governance, model oversight, prompt engineering, and AI-based service development, may offset some job displacement.
Differences Between Executive and Employee Perspectives
The study also highlights contrasting expectations between executives and employees. A parallel survey of US workers revealed that employees generally anticipate a 0.5% employment increase at their firms and predict productivity improvements of 0.92%, both figures lower than the executives’ estimates. This divergence likely arises from the different viewpoints: executives focus on cost and competitive dynamics, while employees experience AI as augmentative to their daily tasks.
Evidence suggests AI tools are often deployed to assist rather than replace workers, especially in knowledge-intensive roles. Controlled trials with AI in customer support and professional services have demonstrated productivity gains primarily among less experienced staff, coupled with quality improvements. Clear communication and training reduce resistance to AI adoption.
Survey Methodology and Implications for the Future
The researchers acknowledge that survey design affects results. For instance, a McKinsey survey conducted during the same period reported an 88% AI adoption rate, higher than the 69% found here, while the US Census Business Trends and Outlook Survey showed lower adoption estimates. Differences stem from sampling methods, definitions of AI, and respondent seniority, with executive surveys capturing enterprise-level deployments and intent more effectively.
This study’s respondents were predominantly CEOs and CFOs from the UK and Germany, verified by phone and unpaid, with data cross-checked against ten years of macroeconomic statistics. The findings suggest an inflection point is approaching as AI integrations mature and become routine workplace tools. The key challenge is how quickly organizations can translate AI adoption into measurable economic benefits.
Overall, the research underscores a cautiously optimistic forecast for AI’s role in enhancing productivity while reshaping employment landscapes gradually, emphasizing the creation of new jobs alongside the reallocation of existing ones.
Fonte: ver artigo original
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