Michelle Turner began Here Now Health from her home in Virginia Beach with a problem she knew personally - a lack of mental health services for children entering the foster system. Turner, a foster parent, launched the company in January 2025 and quickly turned an idea into an operating platform that now employs 16 people and holds certification in three states to provide Medicaid-funded counseling to foster children.
Turner says she did not build an AI company, but relied heavily on AI tools to accelerate her path from concept to a functioning business. Working alone as a first-time founder - and a mother of six - she used generative tools to teach herself about startup culture, draft a business plan and polish investor presentations. The assistance, she said, substituted for formal credentials she does not hold and provided the kind of mentorship and feedback that would otherwise require time and money.
"A mom of six kids who’s a first-time founder, who’s a sole female founder, should not be able to raise (venture capital). I don’t have an MBA. I don’t have these things to back me up," Turner said. She described developing her funding pitch with AI guidance as "like going to a master’s level class every day from the robot. It was my startup advisor."
Turner’s experience is one microcosm of the broader economic debate swirling around the rapid rise of AI. Policymakers at the Federal Reserve are paying close attention. The Fed’s new chairman, Kevin Warsh, has initiated a broad internal review and assigned one panel to examine AI and its implications for productivity - the force that can allow output to grow faster without causing higher inflation, while potentially reducing the number of workers needed to produce the same goods or services.
Fed officials and outside analysts are weighing scenarios that range from an AI-driven productivity surge to more troubling outcomes such as structurally higher unemployment or a continued decline in labor’s share of national income. The discussion is politically charged because changes in returns to capital and labor have distributional consequences across society.
At the same time, the technology itself is rapidly diversifying. Different AI models are competing for users and investment, offering capabilities that extend beyond search and shopping to tasks such as problem solving, complex analysis and writing computer code. That competition has pushed investment into data centers and other infrastructure, which in turn can raise power and labor costs in some regions.
Jean Boivin, head of the BlackRock Investment Institute, summarized the tension at a seminar with journalists, saying markets now face "dramatically different competing narratives" - one of scarcity driven by the investment boom and rising costs, and another of abundance in which AI leads to major innovation and potential breakouts from slow growth.
For small entrepreneurs like Turner, the practical effect has been to lower the price and time needed to access entrepreneurial knowledge and tools. John Bailey, a nonresident senior fellow at the American Enterprise Institute who advised one of the firms that invested in Here Now Health, said the cost of things that used to be time-consuming or expensive has fallen "close to zero." Bailey, who helped Turner adopt the AI tools she used, believes that empowerment enables entrepreneurs to scale faster and hire staff, even when they are not building AI-centric businesses.
"These are not AI companies. They are traditional companies trying to deliver services but do it faster, cheaper," Bailey said.
Other observers see a similar pattern. Torsten Slok, chief economist at Apollo Global Management, attributes a recent increase in new business formation to AI, saying the technology is "dramatically reducing the cost and complexity of launching a company. As these firms scale, they will create jobs."
Nevertheless, public debate remains focused on AI’s capacity to disrupt employment. Recent rounds of layoffs in the tech sector have been attributed in part to AI-driven efficiencies, and there is evidence that firms are using AI to reduce back-office and clerical headcount. Some Fed officials have warned that this could result in an AI economy with structurally higher unemployment, while other observers point to continued declines in labor’s share of national income and question whether returns to capital will keep rising.
Richmond Fed President Thomas Barkin said he is grappling with the employment risks that AI might pose, but noted that firms in some skilled trades report the technology is easing worker shortages. Those employers are using AI to make current hires more productive rather than replacing workers outright, Barkin said.
"We are all quick to see the disasters, which is about jobs getting replaced," Barkin said. But he added that contacts in fields like auto repair or manufacturing generally "are still in a world of saying they cannot get enough workers," and are leveraging AI to increase the productivity of the people they hire. He warned, however, that the transition is likely to create concentrated risks - what he called a "rust-belt risk" for certain white-collar occupations - even as the economy faces persistent shortages in other areas.
Concerns about the social consequences of disruptive economic change are not new, and some analysts point to the painful adjustment that accompanied the globalization of manufacturing in the 1990s. Workers displaced then struggled to find equivalent opportunities, and programs designed to ease transitions were widely judged ineffective. Over time, weakened opportunities in certain regions contributed to political shifts and worsening public-health trends, according to observers who study those outcomes.
Researchers from the Brookings Institution and Opportunity@Work have warned that a similar pattern could emerge for workers in clerical, administrative and other roles now exposed to AI. Their study identified roughly 23 million people whose next logical career step could be into jobs highly exposed to AI automation. Those workers may find themselves at risk of being stuck in lower-paying employment paths if disruption curtails the usual route upward.
"Disruptions in these roles can have outsized effects on workers’ ability to move into higher-wage work," the researchers wrote, noting that the geographical impact of such displacement would likely differ from the earlier manufacturing shock. They pointed to concentrations of susceptible work in Florida, the Northeast, Texas and California - states with substantial shares of office, administrative and clerical roles.
For the Fed, both the eventual outcome and the pace of the AI transition are critical. Short-term effects could look very different from long-run outcomes, and only over time will it become clear whether AI produces a productivity boom substantial enough to change the growth and inflation backdrop.
At his first press conference as Fed chairman, Warsh called AI the most important economic change "that we’ve had in my adult lifetime," and said the country is "ultimately going to be better off" because of the technology. He also cautioned that such a transformation would be disruptive.
Turner’s experience sits at the intersection of these debates. Her use of AI to jumpstart a Medicaid-certified mental health service for foster children illustrates how the technology can reduce barriers for individual entrepreneurs and accelerate the formation of new firms. Yet the broader picture the Fed and other analysts are sketching is more complex - involving questions about labor displacement, capital returns, regional impacts and the need for policies that manage the transition.
As Turner’s company grows, it will join numerous other nascent firms that benefited from lower starting costs enabled by generative tools. Whether those firms collectively yield a net job gain, a lasting productivity improvement, or a mix of benefits and concentrated dislocations is the central economic question that policymakers and market participants are watching closely.
In the meantime, Turner’s account offers a concrete example of how AI is reshaping the mechanics of starting and scaling a business - particularly for founders who lack traditional credentials or networks but can use accessible tools to build operations, raise funding and deliver services quickly.