small businesses have always been economic anchors. globally, they make up over 90% of all firms and provide more than 50% of employment. in emerging markets, they may generate 7 out of 10 jobs. (source: world bank data cited in multiple studies)
the question now is: as ai lowers entry barriers, can smes become the most powerful force in the next generation of entrepreneurship?

the Washington Post argues that ai is already reshaping entrepreneurship — not just for elite founders but for domain experts, creatives, and local problem-solvers. the promise: democratized tech, global reach, fast iteration, and new business models that scale. but it’s not automatic. success depends on how smes adopt, integrate, and navigate constraints.
let’s walk deeper.

the promise: ai as an equalizer

the washington post piece highlights three dynamics:

1. eliminating the technical divide
   ai tools allow people with deep domain knowledge — sommeliers, nutritionists, tradespeople — to build ai-backed services without coding.

2. accelerating experimentation
   rapid prototypes, applied feedback, and pivot capacity reduce risk in early stages of business ideas.

3. global reach from local roots
   translation, 24/7 service, and digital channels let niche local services find global customers.

these shifts could rewrite who can be an entrepreneur.

how big is the gap today?

to appreciate the scale of opportunity, we need context.

• mckinsey’s “a microscope on small businesses” finds that smes account for ~90% of firms, nearly half of economic value added, and two-thirds or more of business employment (higher in emerging economies). McKinsey & Company

• in advanced economies, smes operate at roughly 60% of the labor productivity of large firms (and in some emerging markets, only ~29%) according to research cited by itif. ITIF

• the oecd’s report on digital transformation warns that while digitalization has great upside, smes lag due to fewer resources, skills gaps, and financing constraints. OECD

• a recent survey by Reimagine Main Street found that among ~1,000 small businesses, 82% see AI as essential to remain competitive, and 25% already use it daily. Reimagine Main Street

these numbers tell a story: the infrastructure for sme-led ai entrepreneurship exists in potential, but many haven’t crossed the threshold yet.

bridging the divide: what adoption looks like

when smes adopt ai, the gains can be fast and large — but the path matters.

a. use cases that scale

• automating routine tasks — customer support, scheduling, data entry — frees up human time for higher-value work. bipartisanpolicy notes many small businesses report efficiency gains when applying ai to accounting, crm, and marketing. Bipartisan Policy Center

• leveraging generative ai in content creation, lead qualification, or product ideation helps more with less initial capital.

• packaging domain expertise into digital products — e.g. a tradesperson offering predictive estimating tools to peers.

b. compounding effects

• increased productivity helps free cash flow, which can be reinvested.

• success stories build confidence across peer networks.

• data generated through use enables further automation and insights.

c. real constraints

• skills & training — many owners are unfamiliar or wary of ai.

• integration friction — legacy systems, data silos, tool mismatch.

• capital & risk — small firms may lack startup buffers to iterate.

• trust, regulation, ethics — ensuring privacy, reliability, and accountability.

these are not insurmountable; they just require strategy and support.