This is the second in a three-part series exploring AI and the future of entrepreneurial opportunity.

Artificial intelligence is changing not only how businesses operate but also what kinds of companies entrepreneurs can create. Founders are developing AI-powered healthcare applications, financial technology platforms, education tools and business services. Others are building entirely new companies around machine learning, automation and AI infrastructure. These developments are creating opportunities for entrepreneurs to enter markets that once required substantial technical resources, large teams and significant startup capital.

The scale of this entrepreneurial activity is significant. According to Stanford University’s 2026 AI Index Report , the United States recorded 1,953 newly funded AI companies in 2025. Yet as this new generation of businesses emerges, the regulatory environment surrounding them remains unsettled. Federal policymakers, state governments and technology companies are advancing different approaches to oversight, raising questions about transparency, accountability, consumer protection and innovation. For entrepreneurs developing AI technologies, these decisions could influence everything from product development and fundraising to market entry and long-term competitiveness.

The question of who governs AI is therefore about more than technology policy. It is also about who will have the opportunity to create, own and scale the next generation of American businesses.

A Changing Regulatory Environment For AI Startups

The debate over AI governance has intensified as federal and state governments pursue different regulatory approaches. The Trump administration’s America’s AI Action Plan emphasizes technological competitiveness, innovation and reducing regulatory barriers. Meanwhile, California has expanded oversight requirements, including September 2026 legislation establishing standards for independent AI assessments .

For startups, the consequences of these competing approaches are significant. A company developing an AI-powered financial services platform may need to consider existing financial regulations alongside evolving expectations for algorithmic transparency, data protection and automated decision-making. A founder developing AI tools for healthcare or employment may face additional requirements based on how those products are used. As companies expand across state lines, differences in applicable rules could introduce additional legal and operational costs.

These challenges are not necessarily arguments against regulation. Clear standards can strengthen consumer confidence, establish expectations for responsible development and help companies demonstrate the reliability of their products. The concern is whether emerging governance frameworks will distinguish adequately between the risks posed by different technologies and the resources available to companies developing them. A startup with five employees does not have the same compliance infrastructure as a technology company employing thousands. Policies that fail to recognize those differences could inadvertently make it more difficult for new competitors to enter the market.

Who Gets To Build The Next Generation Of AI Companies?

Much of the national conversation about artificial intelligence focuses on a relatively small group of companies developing large foundational models. Their investments in computing infrastructure, research and technical talent are shaping the direction of the industry. However, the broader AI economy also includes startups developing specialized applications, industry-specific models, AI-enabled software and services built on existing technologies.

These businesses represent an important part of the entrepreneurial opportunity emerging around AI. A founder does not necessarily need to develop a foundational model to create a valuable AI company. Entrepreneurs can build technologies that address specific business problems, serve underserved markets or introduce new capabilities into established industries.

Their opportunities, however, are shaped by more than entrepreneurial ingenuity. Access to computing resources, training data, technical talent and established AI platforms can influence which companies successfully enter the market. Governance decisions involving data rights, intellectual property, model access, liability and competition could further affect the costs and feasibility of developing new products.

Consider an entrepreneur creating an AI platform to help small manufacturers improve production efficiency. The company may depend on a third-party AI model, customer operational data and access to specialized computing resources. Changes in the terms governing those inputs, or uncertainty about responsibility for AI-generated errors, could affect product pricing, investor confidence and the company’s ability to scale.

For these founders, governance can become a material consideration in their business models.

The Implications For Capital And Competition

The regulatory environment may also influence how AI startups attract investment. Investors evaluating emerging technology companies consider not only market demand and growth potential but also the legal, technical and operational risks associated with bringing products to market. Uncertainty about future requirements can complicate those assessments, particularly for companies developing applications in heavily regulated industries.

At the same time, governance can create opportunities for entrepreneurs. Demand for AI auditing, cybersecurity, model evaluation, compliance software and responsible technology deployment could support the formation of new businesses. As organizations seek to understand and manage AI-related risks, startups that help companies meet those needs may find expanding markets for their services.

The National Institute of Standards and Technology’s AI Risk Management Framework offers one example of an approach designed to help organizations identify and manage AI risks. Its voluntary structure provides a reference point for companies seeking to incorporate trustworthiness into the development and deployment of AI systems.

The broader economic question is whether governance will encourage a competitive marketplace of AI innovators or reinforce advantages held by companies already possessing substantial financial, technical and legal resources. Requirements that improve accountability may help smaller firms establish credibility, while requirements that impose disproportionate costs could create additional barriers to entry.

What This Means For Small Businesses And Regional Economies

The implications extend beyond entrepreneurs creating AI technologies. Millions of existing small businesses may increasingly depend on AI products developed by this emerging generation of companies. Their ability to adopt these tools will be influenced by pricing, accessibility, reliability and the protections available when automated systems affect customers or business operations.

In my September 24 Forbes article, AI Is Redrawing The Map Of Entrepreneurial Opportunity , I examined the relationship between artificial intelligence and the geography of economic opportunity. AI governance adds another dimension to that discussion: the rules established today may influence not only where AI innovation develops but also which entrepreneurs and communities are positioned to participate.

A 2025 Brookings Institution analysis by Mark Muro and Shriya Methkupally documented substantial geographic differences in AI talent, research capacity and business adoption, while identifying opportunities for emerging metropolitan areas to participate in the growing AI economy. Their findings reinforce the importance of regional institutions in helping communities translate technological advances into economic opportunities.

Cities and regions seeking to build competitive entrepreneurial ecosystems must therefore consider both the creation of AI companies and the adoption of AI by existing businesses. Universities, research institutions, economic development organizations and small business support networks can help founders access technical expertise, understand regulatory expectations and commercialize new technologies. These institutions can also connect entrepreneurs to emerging markets and potential customers.

Making Entrepreneurship Part Of The Governance Conversation

As policymakers consider the future of AI oversight, the entrepreneurial consequences deserve greater attention. Governance frameworks should account for differences between developers of advanced foundational models, startups building specialized AI products and smaller businesses deploying existing technologies. Their activities, resources and potential risks are not identical.

The development of effective standards also presents an opportunity to engage entrepreneurs directly. Startup founders, small business organizations, investors and regional innovation institutions can provide practical insight into how proposed requirements affect product development, access to capital and competition.

The challenge is not simply choosing between regulation and innovation. It is determining how to support both responsible technological development and a business environment in which new companies can emerge and compete.

Artificial intelligence has the potential to change the economics of entrepreneurship by expanding access to capabilities that were previously expensive or difficult to obtain. But technological advancement alone will not determine who benefits from that opportunity. The decisions being made about AI governance will also help shape which companies are created, which innovations reach the market and which entrepreneurs have a meaningful opportunity to participate in the emerging AI economy.