Washington is spending billions of dollars and countless hours deciding what America's artificial intelligence future should look like. Policymakers are debating data centers, computing infrastructure, model development and the rules that will govern them. Those debates matter. But they often overlook the part of the economy where those policies will ultimately be put into practice: millions of small and midsize businesses.
As the director of Arizona State University's Small and Medium-Sized Business Lab, I spend a great deal of time with business owners confronting real operating challenges. They are not asking abstract questions about innovation. They are asking how to reduce costs, find people with the right skills, serve customers faster
and survive in markets that are changing faster than their internal capacity.
The pattern is clear: Access to technology is not the same as the capacity to use it effectively. A tool may be powerful, affordable and easy to discuss in a policy meeting, but that does not mean a small business has the infrastructure, data, people, trust or workflow discipline to use it well.
Large corporations can support AI adoption with dedicated IT teams, lawyers, consultants, engineers and capital. A small business faces the same technology with a very different set of realities. Will this work with the systems I already have? Who will own it? Can I trust the output? What happens when it is wrong? Will it help my business, or will it become another project nobody has time to manage?
Those questions are becoming more urgent as pressure to adopt increasingly comes from customers and business partners. A large customer may start using AI and then expect smaller suppliers to connect data, change processes, respond faster or meet new digital requirements.
From the outside, that may look like healthy technology diffusion. On the ground, it can feel like a mandate without the capacity to comply. A small business may want to adopt AI, but its infrastructure, people, data and workflows may not be ready. Willingness to adopt is not the same as readiness to execute.
Research from the U.S. Chamber of Commerce has found that small businesses with higher levels of technology adoption are more likely to report growth in sales, profits and employment than businesses with lower levels of adoption. That is an important finding, but it raises the question policymakers should be asking next: What actually turns adoption into execution success?
Our on-the-ground research with small businesses suggests the answer is not adoption alone. AI execution depends on a fine balance between organizational readiness, employee trust, workflow fit, implementation capacity, data discipline and the ability to absorb change without disrupting daily operations.
That matters because AI can affect more than individual tasks. It can change how information moves through a company, how employees make decisions and where responsibility for those decisions sits.
One signal should make policymakers pause. In a number of our interviews, participants gave AI a name or described it almost like a working counterpart. Business owners do not talk that way about a CRM system or an ERP module. AI is entering the business as something closer to a decision partner than a passive tool, which changes the implementation problem.
This is why the usual answers are not enough. Education helps, but education alone does not fix weak infrastructure, thin margins, messy data, limited technical support or tools that do not fit the way a business actually operates. Funding helps, but money spent on awareness campaigns, consultants or generic training will not solve an execution problem that has not been properly diagnosed.
If policymakers measure progress only through adoption rates, they risk mistaking activity for capability. AI implementation affects people, processes, data and customer expectations at the same time. Policies that consider those elements separately may miss how adoption actually unfolds inside a small business.
Small businesses will still need software providers, managed service providers, accountants, consultants, community colleges, universities and other trusted partners. But those partners cannot simply drop AI tools into a business and declare the adoption successful. They have to help build the capability to use AI without disrupting the operating system of the firm.
None of this means AI should be left without guardrails. Sensible rules are necessary to protect consumers, safeguard data, encourage competition and maintain trust. But effective regulation requires a serious understanding of the businesses that will bear the downstream costs of those rules.
Before policymakers regulate America's AI future, they should require a small-business execution test for major technology policy. They should ask how proposed rules affect adoption cost, compliance burden, infrastructure readiness, workforce readiness, data quality, workflow fit, feedback risk and the ability of smaller firms to compete.
Small business owners and the organizations that work with them should also have a meaningful role in that process. The test should not simply be whether a policy works on paper, but how it functions when it reaches a business with 20 employees, thin margins, limited technical staff and customers demanding that it keep up.
America has an opportunity to lead not only in building the world's most advanced AI, but also in helping businesses of every size put AI to work responsibly and productively. Understanding how that happens on the ground should be part of the conversation from the beginning.
Hitendra Chaturvedi is a professor of practice in the NASPO Department of Supply Chain Management at the W. P. Carey School of Business, Arizona State University, where he teaches and advises on topics including AI, supply chain strategy, sustainability, entrepreneurship and business strategy. He is faculty director of the Master of Science in Entrepreneurship and Innovation program, founder of the Small and Medium-Sized Business Lab and strategic adviser to the dean on entrepreneurship. He also co-chairs the West Valley Chamber's Supply Chain and Manufacturing Committee and is a founding member of Arizona Venture Alliance.
This article originally appeared on Arizona Republic: Arizona small businesses deserve a voice in AI policy | Opinion
