The advent of artificial intelligence (AI) and generative AI is reshaping the organizational landscape across various sectors, including among organizations supporting the economic stability and advancement of lower-income workers and households, as well as the businesses that employ those workers. Over the course of seven roundtables and listening sessions in 2025, we spoke with nearly 60 community development stakeholders, including representatives from workforce training and education organizations, nonprofits, and businesses, among others. Through discussions focused on the ways in which organizations were adopting, or considering adopting, AI tools—and how those decisions were affecting their staffing and operations—we found that:
The organizational adoption of AI to date has been uneven.
Among the stakeholders we spoke with, a handful reported that they were essentially still “on the sidelines” when it came to AI adoption. These respondents tended to be associated with organizations providing social services, and, either because of personal concerns or prohibitions from funders related to employing AI, they expressed apprehensions about data privacy and the ability to protect sensitive client information when using commonly available AI tools.
However, the most common response among participants was that organizations have already been experimenting with AI at different levels, from individual productivity tools to organization-wide applications. A small number of respondents even reported moving beyond off-the-shelf applications to develop their own AI tools to support operations or client services. For the nonprofits in that group, the ability to attract flexible philanthropic capital meant to spur technological experimentation allowed them to develop tools they otherwise wouldn’t have been able to access.
Budgetary constraints and operational gaps motivated many organizations’ AI adoption.
Nonprofits we spoke with reported that challenges with an uncertain and increasingly constrained funding environment have been a driver of their efforts to use AI –to increase efficiencies and “do more with less.”
At the same time, multiple businesses noted that they adopted AI to help backstop positions for which their recruitment efforts had been unsuccessful. Employers also reported interest in using AI to help retain workers, including in high-turnover roles such as customer service and phone centers.
Integrating AI tools has influenced organizations’ staffing and hiring decisions.
Among the organizations that reported integrating AI into their operations, we heard a range of ways in which AI adoption had impacted hiring and staffing decisions. In some cases, employers were able to use AI to augment their existing workforce and hold off on hiring for additional roles. For instance, one respondent from a community development financial institution noted that they were able to increase efficiencies among their underwriting staff by using AI, and were able to forego hiring the two new underwriters they had planned to recruit.
In other cases, respondents reported hiring differently. For example, rather than hiring a junior fundraiser, one nonprofit respondent noted that they hired a more senior fundraiser, with the expectation that AI would help take care of administrative support tasks.
In that vein, the respondents who reported cutting positions or using AI to replace roles entirely shared that those positions tended to be entry-level communications and administrative positions, consistent with findings from recent SF Fed research that found lower-income workers with high exposure to AI impacts were most likely to work in office and administrative occupations.
Organizations using AI underscored the need to “keep humans in the loop.”
Although respondents noted the ways AI has helped increase efficiencies, they also emphasized the importance of human involvement. Those discussants with more experience experimenting with AI agreed that it is not a standalone “easy button” and requires careful oversight. One frequently cited example was the use of AI to assist in translation. Several of the organizations we heard from use AI to help translate communications for the multilingual communities they serve. However, they all cautioned that output needed to be verified by skilled human translators to ensure correct translation, particularly around the use of idioms and culturally sensitive topics.
In addition to the importance of verifying the accuracy of AI-produced content, respondents—particularly those working with vulnerable populations—also expressed the need to maintain the human connection with their clients, especially those navigating uncertain or difficult circumstances. For those organizations, AI augmentation may help stretch limited resources and support operations, but it will not be able to fully replace the case workers and front-line staff who engage directly with clients.
While the experiences of organizations varied, these roundtables and listening sessions underscored how quickly the AI landscape is evolving and influencing organizational decisions across sectors and industries, albeit at different and uneven paces. They also highlighted the importance of tracking the real-time impacts on organizations and employees as AI tools continue to evolve and disseminate.
This article is part of a Community Investments series exploring the ways in which the growing prevalence of artificial intelligence may be impacting economic conditions, especially in low- and moderate-income communities and among community development stakeholders. Gaining greater insight into emerging economic trends through community engagement and analysis—including better understanding the economic experiences of lower-income workers and consumers—contributes to the Federal Reserve Bank of San Francisco’s work to support monetary policy, strengthen financial institutions, and enhance the payments systems.