🔍 Read the full analysis: The Process Of Setting Wages With AI In The Picture on ThorstenMeyerAI.com
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TL;DR
A November 13 article from ThorstenMeyerAI.com explains how wages are shaped by bargaining, labour-market conditions and legal rules, not productivity alone. It cites a customer-support study in which an AI assistant raised issues resolved per hour by 15% on average, while saying whether those gains reach workers depends on how pay is set. The article does not provide evidence that AI has raised wages.
ThorstenMeyerAI.com published an explainer on November 13 about how wages are set as artificial intelligence changes workplace output, arguing that higher productivity does not by itself determine whether workers receive higher pay. The article points to a study in which an AI assistant increased customer-support agents’ issues resolved per hour by 15% on average, and says the division of any resulting gains depends on bargaining, markets and rules.
The article uses Germany’s minimum-wage increase as a current example of how pay can be set outside individual negotiations. Effective January 1, 2026, the legal minimum rose from €12.82 to €13.90 an hour. According to the article, a six-member Minimum Wage Commission—three representatives each from unions and employers—proposed the increase, with two academic advisers who do not vote. The government made it binding by regulation. The article says about six million people received a raise as a result.
It distinguishes the economic idea that pay reflects a worker’s added output from the real-world process of deciding how income is shared. In 1899, economist John Bates Clark described a theoretical market in which workers receive the value they add to production, provided the market operates “without friction.” The article treats that model as a benchmark rather than a complete account of wage-setting.
As an example of wage regulation, the article says Germany’s 2015 minimum wage affected 15% of employees, increased pay and did not reduce employment, citing a study published in the Quarterly Journal of Economics. It also reports that Germany’s labour share—the portion of national income paid to employees as wages, salaries and employer social contributions—was 73.5% in 2025. These figures describe different aspects of pay; neither establishes how AI’s productivity gains are being distributed.
Infographic 01 · The number to remember
73.5%: where Germany's income goes
The labour share: pay for employees as a share of national income.
Out of every €100 of German national income, 2025
Labour share, Germany · % of national income
The share rose in 2024 and 2025 partly because company and investment income fell in a weak economy while pay kept rising (IW). A higher share is not automatically good news. Definitions matter: measured against GDP, or with the self-employed counted differently, labour shares come out differently.
Sources: Destatis, key national accounts aggregates (as of 30 Sep 2026); M. Grömling, IW-Kurzbericht 20/2026 (12 Mar 2026).
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Who Receives AI Productivity Gains
The question matters because workplace AI can change the amount of work employees complete without settling how the economic gains are divided. The customer-support study cited by the article measures issues resolved per hour, not workers’ wages, hours, job security or the share of revenue going to employees. It therefore cannot, by itself, show that employees benefited financially from the productivity increase.
For workers, employers and policymakers, the practical issue is how pay responds when output changes. Individual negotiations, collective bargaining, competition for workers and statutory wage floors can all affect that outcome. Germany’s minimum-wage example shows one route: a commission proposal followed by a government regulation. It does not establish that the same process, or the same effects, will apply to AI-related productivity gains.
The article’s central point is that productivity and pay are related but not interchangeable. Understanding who captures gains from AI requires evidence about compensation and bargaining, not output measures alone.
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From Wage Bargains to Legal Floors
The article places current wage-setting debates within a history of competing explanations. In The Wealth of Nations (1776), Adam Smith described wages as a contract between employers and workers with differing interests, and argued that employers often have more power to wait. The article uses Smith’s account to highlight bargaining power as one influence on pay.
In 1817, David Ricardo described a “natural price of labour” tied to workers’ subsistence. Later, Clark’s marginal-product theory offered a model in which pay corresponds to a worker’s additional contribution to output. The source contrasts these ideas with the development of wage floors, including Germany’s minimum wage, introduced in 2015 at €8.50 an hour.
The article’s historical examples provide context, not a direct forecast of AI’s effects. They show that wages have been shaped by economic models, negotiation and public rules. The source also notes that Germany’s 2026 minimum-wage decision was made through a commission and government regulation, rather than by each affected worker negotiating individually.
““What are the common wages of labour, depends everywhere upon the contract usually made between those two parties, whose interests are by no means the same.””
— Adam Smith, quoted in ThorstenMeyerAI.com’s article
What the AI Evidence Does Not Show
The source does not identify the customer-support study by title, authors, publication date or sample size, and it does not describe the study’s methods. Its reported 15% average increase concerns issues resolved per hour; the article supplies no wage comparison, time period for wage effects or evidence that the productivity gain was passed on to employees.
It is also unclear from the source how the increase in Germany’s minimum wage affected individual workers’ total compensation, hours or employment in 2026. The article reports the new rate and the estimated number of people receiving a raise, but does not provide a detailed breakdown of the estimate or a post-change evaluation. Its discussion should not be read as evidence that AI has raised wages or reduced employment.
Tracking Pay After Output Gains
The next evidence needed is research that follows both productivity and compensation over time, including wages, hours and employment for workers using AI tools and comparable workers who are not. Details about the cited customer-support study would help readers assess what its 15% figure measures and how broadly it applies.
In Germany, the article identifies the 2026 minimum-wage rate as effective January 1, but gives no next commission decision date or later policy milestone. For now, the central question remains whether AI-driven output gains translate into higher worker pay—and what role employers, collective bargaining and regulation play in that outcome.
Key Questions
What wage development does the article report?
It says Germany’s legal minimum wage rose from €12.82 to €13.90 an hour on January 1, 2026, following a Minimum Wage Commission proposal that the government made binding by regulation.
Does the reported AI productivity gain mean wages increased?
No. The article cites a 15% average increase in customer-support issues resolved per hour, but gives no evidence that wages rose as a result.
Who proposed Germany’s 2026 minimum wage increase?
According to the article, the proposal came from the Minimum Wage Commission, with three voting representatives from unions and three from employers. Two academic advisers could not vote; the government made the proposed rate binding by regulation.
What does the labour share measure?
It measures the portion of national income paid to employees as wages, salaries and employer social contributions. The article reports Germany’s labour share at 73.5% in 2025.
What remains unknown about AI and wages?
The source does not show whether AI-related productivity gains have increased workers’ pay, nor does it provide study details or a longer-term comparison of wages, hours and employment.
Source: ThorstenMeyerAI.com
