On September 19, the EmergingTech Economic Research Network (EERN), a Federal Reserve Bank of San Francisco initiative in collaboration with the Federal Reserve System Innovation Office, convened selected employers, workforce leaders, and researchers to examine how artificial intelligence is reshaping jobs and economic mobility, especially for low- and moderate-income (LMI) workers. SVLG was honored to be invited by the SF Fed team to participate.
Key Research Findings
Elizabeth Kneebone, Assistant Vice President of Research, Community Engagement and Analysis at the SF Fed shared new analysis on AI exposure across occupations. About one in five U.S. workers are in jobs considered highly exposed to AI, where core tasks could be automated or significantly augmented.
Of significance to Bay Area conversations on economic mobility, Kneebone noted that this exposure is not spread evenly: roughly six million workers from lower-income households are in high-exposure roles. Without intentional mobility and training strategies, these workers could face outsized risks of displacement and fewer opportunities for advancement.
A Near-Term Playbook for Employers
The panel discussion, moderated by Natalie Holmes, Senior Researcher of Community Engagement and Analysis at the SF Fed, emphasized practical lessons for employers and workforce partners. Four themes stood out as a near-term playbook for action:
- Build two lanes. Invest in AI-specific training pathways while also embedding AI literacy into non-tech functions such as finance, HR, and operations.
- Keep humans at the center. Critical thinking, communication, and creativity remain the differentiators. Workers need to be able to evaluate and improve what AI produces, not just generate outputs.
- Support the whole learner. Upskilling is most effective when combined with supports that reduce “time poverty,” such as childcare, ESL instruction, digital skills training, and financial literacy tools.
- Harness bottom-up adoption. Many employees are already experimenting with AI on their own. Rather than restricting this, organizations can provide safe guidelines and spaces to share what works.
One data point underscored the urgency: in 2021, 92% of jobs required at least one digital skill, and wages rose with the number of skills required. Many workers still lack these foundations, which makes building AI literacy even more pressing.
Fireside Chat with President Mary C. Daly
In her remarks, Mary C. Daly, President and Chief Executive Officer, Federal Reserve Bank of San Francisco, tied the conversation back to the Fed’s dual mandate of price stability and maximum employment. She noted that while hiring has slowed, it is too early to say how much of that is directly attributable to AI as opposed to broader economic cycles.
Daly highlighted opportunities in fast-growing sectors such as healthcare, education, and social assistance. These fields are both highly exposed to task automation and chronically short of workers. With careful adoption, AI could reduce administrative burdens and allow professionals to focus more on direct service and teaching.
Her perspective was pragmatic: AI is not inherently disruptive or equalizing. Its long-term impact will depend on how businesses, educators, and policymakers choose to integrate it, and whether equity is a priority in that process.
Closing
The EERN convening made one point clear. AI’s impact on economic mobility is not predetermined. With coordinated strategies informed by research and practice, the same tools that could widen divides can also expand opportunity.
SVLG thanks the Federal Reserve Bank of San Francisco and the EmergingTech Economic Research Network team for the invitation to attend, and for convening this important conversation. We look forward to continuing to engage with our members and regional partners on building an inclusive AI future for the Bay Area.
