Introduction: A Turning Point in Business Creation
Artificial intelligence has emerged as one of the most significant forces reshaping entrepreneurship across North America. What once required substantial capital, specialized technical expertise, and prolonged development cycles is now increasingly accessible to a broader range of individuals. With a laptop, an idea, and access to AI-powered platforms, aspiring business owners can launch ventures that previously would have been out of reach. This development has been described by analysts as an entrepreneurial revolution.
The potential benefits are substantial, but they are accompanied by important caveats. Education, regulatory clarity, and equitable access will determine whether this revolution reaches beyond major urban centers and entrenched industry leaders. Without careful planning, there is a risk that the advantages of AI-enabled entrepreneurship will cluster in established hubs, leaving many small and midsize businesses behind.
Evidence of Declining Barriers to Entry
Recent data highlights the extent to which artificial intelligence is lowering traditional barriers to entry for entrepreneurs. According to Gusto’s 2025 New Business Formation report, nearly half of newly established U.S. businesses used generative AI in their operations, a sharp increase from roughly one in five in the previous year. Notably, adoption is happening early in the life cycle of new ventures, with founders leveraging AI immediately rather than years into their journey.
The U.S. Chamber of Commerce reported that by late 2024, 40 percent of small businesses were already using generative AI. In parallel, Axios summarized polling data from U.S. Bank that showed 36 percent of small firms were using AI, with an additional 21 percent planning adoption within a year. These figures illustrate that adoption is no longer confined to large corporations with extensive budgets. Instead, smaller firms are experimenting with affordable or free tools to streamline core functions.
Stripe’s research on AI companies adds further context. The top 100 AI firms reached key revenue milestones materially faster than the fastest-growing SaaS companies from a few years earlier. While these are technology-focused organizations, the broader implication is that development and scaling cycles are shortening. For smaller service-oriented firms, the availability of off-the-shelf AI allows them to assemble solutions quickly without requiring custom development.
Implications for Small and Midsize Businesses
For small and midsize businesses in Canada and the United States, AI is effectively acting as a suite of part-time specialists. It generates product copy, designs preliminary branding assets, manages customer communications, reconciles financial records, and converts raw transcripts into polished proposals. Shopify has reported that nearly half of small businesses using AI have seen increases in productivity, and a significant portion have experienced improvements in customer satisfaction.
This dual impact addresses two long-standing hurdles for entrepreneurs. The first is the skills gap. Non-technical founders can now deploy no-code platforms, hosted models, and integrations to create credible products and services. The second is capital intensity. Rather than hiring marketing professionals, bookkeepers, and support staff at the outset, businesses can automate essential functions and hire later when revenue permits.
The Organisation for Economic Co-operation and Development (OECD) has emphasized that broad adoption among small and midsize businesses is critical for realizing productivity gains. Without targeted policies to ensure diffusion, the benefits will concentrate among firms that already operate at the frontier.
Canada: Programs and Gaps
Canada offers a clear illustration of the opportunities and risks surrounding AI adoption. The Canada Digital Adoption Program (CDAP) supported more than 70,000 businesses in building digital strategies and adopting new technologies. However, the program has stopped accepting new applications, creating a gap at a time when demand for AI expertise is accelerating.
Provinces are beginning to respond. Ontario, for example, has expanded its Digital Modernization and Adoption Plan (DMAP) through the Ontario Centre of Innovation. The program provides grants of up to 15,000 dollars for planning and creates pathways for implementation funding. While this is a promising step, the coverage is uneven across Canada, leaving smaller regions with limited access to structured support.
Regulation is another area of concern. Bill C-27, intended to establish a federal framework for artificial intelligence oversight, was dissolved when Parliament was prorogued earlier in the year. The absence of a national standard leaves businesses navigating a fragmented landscape of provincial initiatives and evolving legal interpretations. For business owners, this uncertainty underscores the importance of proactive diligence in areas such as privacy, data governance, and vendor agreements.
The United States: Building a Framework
In contrast, the United States is building a more comprehensive support system. The Small Business Administration has begun releasing practical AI guidance and integrating AI resources into the nationwide Small Business Development Center (SBDC) network. A 10 million dollar grant from Google.org is funding “AI-U” clinics at universities and community colleges, aiming to reach 100,000 businesses. This partnership between government, private sector, and educational institutions represents a model of how small firms can be equipped for responsible adoption.
Regulation is also advancing. The Stanford AI Index documented a significant increase in federal AI-related actions in 2024. Sector-specific guidance in finance, healthcare, and employment is expected to grow in volume. For business owners, this means planning ahead and ensuring that compliance considerations are integrated into early adoption strategies.
Infrastructure as a Determining Factor
While AI tools themselves are inexpensive, access to reliable infrastructure remains a persistent obstacle. The Federal Communications Commission has reported that 95 percent of U.S. households and small businesses have access to broadband at 100/20 Mbps. However, independent reviews argue that the gaps are larger than official figures indicate. In Canada, the national goal is universal 50/10 Mbps access by 2030, but progress in rural areas is still uneven. For small businesses in underserved regions, inadequate connectivity directly limits the ability to participate fully in the AI-driven economy.
Strategic Policy Directions
Ensuring that this entrepreneurial revolution is inclusive requires deliberate policy design. Three priorities stand out for policymakers in both Canada and the United States.
- Localized advisory capacity. Expand AI clinics at community colleges, universities, libraries, and chambers of commerce to provide vendor-neutral, practical training. Programs like Ontario’s DMAP and the U.S. SBDC AI-U should be extended to smaller regions.
- Adoption-focused incentives. Governments should provide tax credits and grants tied to measurable outcomes such as the implementation of AI-driven quoting systems, knowledge bases, or financial tools. Incentives must encourage adoption among smaller firms rather than disproportionately funding research at the frontier.
- Regulatory clarity. Canada must establish a proportionate federal framework to replace the void left by Bill C-27. In the United States, sector-specific guidance should continue to expand with a clear focus on practical compliance measures for small firms. Both countries should support privacy-preserving solutions accessible to businesses of all sizes.
Practical Considerations for Business Owners
Business owners do not need to wait for new programs to begin adopting AI responsibly. A pragmatic approach includes identifying one workflow to automate within a quarter, investing in targeted training for staff, and documenting data management practices to align with emerging standards. These steps allow firms to test AI tools, build internal capacity, and position themselves for future compliance.
Conclusion: A Revolution in Progress
Artificial intelligence is expanding the possibilities of modern entrepreneurship across North America. The technology is lowering costs, reducing skill barriers, and accelerating business development cycles. At the same time, the benefits are not guaranteed to spread evenly without supportive infrastructure, thoughtful policy, and deliberate diffusion strategies.
The most compelling examples of this revolution are not found in venture capital portfolios but in everyday businesses. A contractor who accelerates proposals, a craftsperson who translates product descriptions for global markets, or a local retailer who engages customers through AI-assisted marketing all demonstrate the transformative potential at work. The task ahead is ensuring that these opportunities extend across regions, industries, and demographics. With deliberate action, AI can serve as the foundation for a more dynamic, inclusive, and resilient entrepreneurial landscape.
