“If you’re a small business, you can move as fast as your willpower.”
Ram Ahluwalia used that line in our recent conversation to describe what AI is beginning to make possible. A handful of people can now command resources and capabilities that once required an organization around them. A small business owner can adopt a new AI tool today, redesign a workflow tomorrow and keep experimenting as quickly as the technology changes. There are few layers of approval standing between an idea and its implementation.
Ram pointed to businesses already being built around this idea: two people directing hundreds of AI agents to perform specific tasks. The entrepreneur becomes an orchestrator, deciding what needs to be done, assigning the work and judging the results. Each improvement in AI expands what that small team can attempt. That role for the entrepreneur is central to Ram’s view of AI. “AI doesn’t have any agency,” he told me. “It needs someone to direct and lead it.” Someone has to decide what problem is worth solving, set the objective, evaluate the work and decide what happens next.
An individual with an idea can acquire expertise, analyze a market, build software, create marketing materials, handle customer inquiries and manage routine operations with AI. Each new capability increases the range of businesses a person can start with limited capital and a small team.
Ram is doing this himself at Lumida, the investment management company he founded. He described using AI for investment research and to build tools that can analyze a client’s tax situation, evaluate different business structures and even understand trust and estate diagrams. These capabilities ordinarily draw on multiple areas of professional expertise. Lumida is putting them to work inside a relatively small organization.
There is another implication of Ram’s argument: more people could earn a living without having a traditional job. Starting a business requires expertise, time, capital and other people to do the things you cannot do yourself. AI is reducing some of those barriers. More people may be able to turn an idea, a skill or an expertise into a viable one-person or small business. If that happens at scale, employment statistics could become increasingly misleading.
Independent work is already difficult to measure. An NBER study found that roughly one in ten people who initially said they worked for an employer turned out, after more detailed questioning, to be an independent contractor on at least one job. Correcting for workers who were miscoded nearly doubled the researchers’ estimate of the independent-contractor share on the main job, to about 15%.
AI could widen this same blind spot and is creating other measurement challenges as well. Anton Korinek and Patrick McKelvey argue that conventional statistics are failing to capture the rapid growth in quality-adjusted AI output and have proposed an “AI GDP.” Diane Coyle and John Poquiz warn that AI is changing business processes, service quality and the organization of labor in ways poorly reflected in official data.
If Ram is right, AI may create prosperity in a form our employment statistics were never designed to measure.
A clip from the interview episode posted to Exploring Prosperity YouTube channel:
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