Adoption and Perceived Value of AI Training in the Workplace

The proliferation of generative AI tools is rapidly transforming workplaces, yet questions regarding access, productivity impacts, and the value of training remain inadequately explored. Insights drawn from the November 2025 Survey of Consumer Expectations (SCE), conducted with a representative sample of U.S. workers, reveal significant trends and disparities in the use of AI tools at work and highlight the critical need for effective training.

Demographics and Adoption Rates of AI Tools

Among the respondents currently employed, 39% have utilized AI tools in their jobs within the past year. However, a closer inspection of this figure uncovers marked variations based on education and income. For instance, 58.7% of college graduates report using AI tools, whereas just 22.9% of those without a college degree have done so. Income levels also play a crucial role; AI usage spikes to 66.3% among workers earning over $200,000, compared to a mere 15.9% in the cohort earning less than $50,000. Furthermore, full-time workers are more likely to have employed AI in their roles (42.7%) than their part-time counterparts (24.7%). This data indicates that AI tool adoption favors higher-income and higher-educated demographic segments, raising concerns about its potential to exacerbate existing inequalities in the labor market.

Productivity Enhancements from AI Usage

Among those who have interacted with AI tools, approximately 66% believe these tools enhance their personal productivity. Specifically, 40% note that AI tools help them complete tasks more swiftly, and 22% feel they can tackle a larger volume of tasks. Conversely, 19% of respondents indicated that they are still mastering AI, which can temporarily slow their task completion rates. Furthermore, a significant barrier to broader adoption exists, as 37% of workers indicate that their employers do not provide access to AI tools, while 11% reported that their workplaces actively prohibit their use.

Perceptions and Availability of AI Training

While a majority of employees with access to AI tools recognize their productivity benefits, training opportunities remain limited. About 38% of workers identified training in AI tool usage as important; however, only 15.9% reported that such training is currently available through their employers. Among those who find training crucial, 68% cite the desire to ease job tasks, while 56.7% associate it with increases in productivity. In contrast, 39.2% believe that future job opportunities will necessitate AI skills. Conversely, nearly 60% of employed individuals who do not consider AI training important noted that they do not anticipate using AI in their roles.

Valuation of AI Training Among Workers

To quantify the monetary value workers attribute to AI training, those without access to it were asked how much of their salary they would be willing to sacrifice for a job offering extensive AI training. Conversely, workers currently with access were asked the salary increase they would demand to consider a job without AI training. Results indicate that workers without training access expressed an average willingness to pay (WTP) of 11.4% of their salary for training. However, this figure is skewed, with a median of 0% suggesting many are unwilling to accept a pay cut. Interestingly, around 61% of these respondents indicated a WTP of 0%. For those assigning positive values, 20% indicated a WTP between 0% and 10%, while 19% were willing to give up more than 10% of their salaries for AI training.

The picture is different for workers with access to AI training. They indicated a required salary increase of 24.2% to switch to a job that does not provide AI training, with a median requirement of 15%. Additionally, 26% of these workers stated they would not seek any salary premium for such a transition. This discrepancy between the average salary increase needed to relinquish AI training and the WTP to gain access reflects a phenomenon known as loss aversion—workers demand significantly more compensation for benefits already received than they would be willing to pay for new access.

Worker Characteristics and Training Valuation

Variations in WTP for AI training exist across different worker characteristics. Younger, non-white, and less formally educated workers, as well as those with less experience, tend to show a higher willingness to pay for training. Conversely, full-time employees and those lacking a college degree require more significant salary increases when considering roles that do not offer AI training. These findings raise important questions about the long-term impacts of AI adoption on labor market dynamics.

Anticipated Effects of AI on Employment

Respondents also shared their predictions regarding AI's influence on the labor market. Approximately 62% expressed concern that AI advancements will lead to a rise in unemployment in the coming year, while only 11.6% felt it would result in job growth. This prevailing sentiment emphasizes the need for proactive measures in workforce training and education to mitigate potential displacement effects of AI technology.

Conclusion

The November 2025 SCE results illuminate the prominent yet unequal adoption of AI tools in the workplace, where higher-income, well-educated, and full-time workers enjoy greater access. A notable fraction of the workforce values AI training highly, yet employer support for such training remains sparse. Alarmingly, individuals who find AI training most essential—often from disadvantaged groups—face the lowest rates of access and usage, illustrating a critical gap that, if unaddressed, could stymie potential productivity gains from AI tools. Addressing these disparities will be essential for leveraging the full capabilities of generative AI in the workplace.