Macroeconomic Costs of AI Regulation in Florida

1. Summary

I estimate the macroeconomic effects for the state of Florida of adding AI regulation beyond what currently exists at the federal level. I make the conservative assumption that Florida restrictive AI regulation could reduce business productivity by 1.0% and could reduce individual labor productivity by a range of 1.0% for the highest earners down to 0.1% for the lowest earners. My macroeconomic simulation shows that increased AI regulation would have the following effects over the 2026-2035 period:

• Reduce Florida GDP by an average of 1.9% or $38 billion per year.

• Reduce Florida employment by an average of 0.5% or 54,100 workers per year.

• Decrease the average wage by an average of 1.4% per year.

2. Background

Big picture debate in the US. An active debate is ongoing in the US and abroad about how much artificial intelligence (AI) should be regulated. One extreme is that AI is dangerous and should be heavily regulated. Another side is that AI needs to be allowed to flourish unfettered by overly precautionary regulatory policy. In addition, states are wrestling with the federal government over what level of government should have jurisdiction over these questions.

OBBBA. As part of the One Big Beautiful Bill Act (H.R.1, OBBBA), the House of Representatives included a 10-year moratorium on AI regulation by the states.¹ Rep. Jay Obernolte (R-CA) has argued that the moratorium is “necessary to avoid a ‘labyrinth of regulation’ with ‘50 different states going 50 different directions on the topic of AI regulation.’”² There have been many other voices supporting the moratorium with these arguments.³

A number of Republican Senators and Representatives initially opposed the moratorium.⁴ Forty attorneys general signed a May 16 letter to Congress opposing the measure.⁵ All of the main arguments against the moratorium are based on the complaint that it violates the federalist principle that states should have the freedom to independently regulate issues within their borders. The primary specific issues cited are limits on any state regulation and child safety regulations.⁶ The Abundance Institute has drafted an AI moratorium fact sheet addressing each of the main arguments against the moratorium.⁷

Florida proposed regulations. In the last 12 months, Florida has proposed at least 5 different AI regulations in the state. These Florida proposals are summarized in Table 1 below. I am not opposing these Florida regulations, but I am highlighting the action being taken in one state and that this action is representative in quantity of the many other differing regulations currently occurring in other states.⁸

The argument is compelling that a patchwork of regulations across states will stifle AI in the United States. It is not just the worry that a particular state will enact its own AI regulatory policy that slows down productivity. It is more that a patchwork of 50 different regulatory policies will create its own compliance, adoption, and investment cost that might dwarf the costs of any one specific set of state regulations.

3. Results

In the analysis in this article, do not assume that AI regulation is bad. I only assume that patchwork regulation across states is inefficient and will create limits on the benefits that can be obtained by optimal development, implementation, and use of AI.

Google and Alphabet CEO, Sundar Pichai, has recently said that Google’s internal metrics estimate that the use of AI has increased the productivity of its employees by about 10 percent.⁹ This 10 percent productivity increase from AI at Google is certainly larger than we would expect the benefit to be for the United States as a whole, even if some workers are seeing an even higher productivity increase. But there are many current use cases that are extending broadly to US residents in general.¹⁰

In our simulation, we use Florida as our example state. Based on the assessments above, we assume that extra AI regulation from Florida would decrease business productivity by 1 percent. We further assume that worker productivity in Florida would decrease by 1.0 percent for the highest earners, phased down to 0.1 percent for the lowest earners. From the discussion above, we think this is a conservative estimate for the potential productivity loss from restrictive AI regulation. But we provide the results of a smaller decrease in productivity in Table 3 below for those who think the effect might be smaller.

I use the open-source OG-USA macroeconomic model to simulate the effects of increased AI regulation at the national level, then we project those percent changes onto Florida GDP, capital stock, employment, and wages. I discuss some of the weaknesses of this approach in Section “4. Caveats”, but I think this approach is an appropriate first pass at the effects of extra AI regulation in Florida. All the code and results for running these analyses are available in the GitHub repository https://github.com/openSourceEcon/FL-AIreg.

Table 2 shows the results of extra Florida restrictive AI regulatory policy on state GDP, capital stock, employment and wages, assuming a 1 percent decrease in business productivity (total factor productivity) and a varying individual workforce productivity decline of 1.0 percent for the highest earners down to 0.1 percent for the lowest earners. The average annual loss in Florida GDP over the period 2026-2035 is -$38.1 billion per year, and the average annual loss in employment over the same period is -54,100 workers per year.

In the case that one thinks that the decrease in Florida business productivity would be less than 1 percent, we ran an extra simulation of the model in which the extra Florida restrictive AI regulation decreased business productivity by 0.5 percent and decreased worker productivity by 0.5 percent for the highest earners and declining to 0.05 percent for the lowest earners. Table 3 below summarizes those results, which are close to half as big as the results in Table 2.

The average annual loss in Florida GDP over the period 2026-2035 for a lower assumed loss in productivity of 0.5 percent is -$19.1 billion per year, and the average annual loss in employment over the same period is -27,730 workers per year.

4. Caveats

In these analyses, we are imputing results from a model of the entire United States onto the state of Florida. There are several potential weaknesses and sources of bias and error from this approach, which include the following:

• US demographics to which the model is calibrated are different from the demographics of Florida. One example is that Florida has an older population than that of the United States as a whole.

• The macroeconomic model is calibrated to US taxes, spending, deficits, and debt trajectory. This is very different from the state of Florida, which has no state income tax and has a balanced budget each year.

• The macroeconomic model is calibrated to the US being a large open economy in which international capital flows into the country to purchase a percentage of government debt and to supply private capital to domestic producers. More realistically, the state of Florida should be modeled as a small open economy that takes the world interest rate as given. International capital flows to Florida are likely very different from those to the US as a whole.

Despite these potential sources of bias in error from using a national model and scaling its results down to a particular state, I think this is a good approximation of what the effect of extra AI restrictive regulatory policy in a state would be.

5. Conclusion

It is likely that AI regulation will be needed as the capacity of the tools grow quickly and our adoption of these tools becomes more widespread. But supporters of the AI moratorium argue that those regulations should be made in one place, at the federal level. Not only is there a race among US tech companies to build the best AI tools and increase market share, but there is also a race among the tech companies of various countries and regions. The main competitor to the US right now in AI is China.

In this article, I estimate the potential economic costs to the state of Florida by enacting its own restrictive AI regulation. These costs are generated by the restrictive regulation reducing Florida business and worker productivity. I found that a 1 percent decrease in business productivity coupled by a varied worker productivity reduction generates annual losses in Florida GDP of $38 billion and annual losses in employment of $54,100 workers.

These losses are significant and might be a lower bound on the losses that could come from every state having its own varied restrictions on AI. The moratorium on state AI regulation in the One Big Beautiful Bill Act (H.R. 1), which is now being debated in the Senate, is an important piece in the global competitiveness framework of US productivity and growth. Furthermore, it can help states, businesses, and individuals better take advantage of the emerging benefits from artificial intelligence.

Model Notes

I used the open source OG-USA macroeconomic model to simulate these results. The documentation for the OG-USA model is online at https://pslmodels.github.io/OG-USA, and the documentation of all the theory of the model is online from the OG-Core model repository at https://pslmodels.github.io/OG-Core. The code for the OG-USA model is available in the GitHub repository https://github.com/PSLmodels/OG-USA. The model can also be downloaded as a Python package (ogusa) through the Python Package Index website https://pypi.org and API. All the code and data to replicate the analyses in this article are in the GitHub repository https://github.com/openSourceEcon/FL-AIreg.

References

Abundance Institute, “Fact Check: Addressing Misconceptions about the AI Law Pause”, Abundance Institute, June 25, 2025.

Adragna, Anthony, “Senate parliamentarian green lights state AI law freeze in GOP megabill”, Politico, Jun. 22, 2025.

Barkley, Taylor, “Protecting Kids Requires Smart, National AI Policy—Not Fifty Shades of Red Tape”, Now + Next, Substack, May 13, 2025a.

Barkley, Taylor, “The State AI Regulatory Moratorium in the States”, Now + Next, Substack, Jun. 2, 2025b.

Barkley, Taylor and Sebastian Griffin, “Op-Ed: AI regulatory moratorium provides time to get the standard right”, Opinion, The Center Square, May 20, 2025.

Chow, Andrew R., “Why AI Regulation has Become a ‘States’ Rights’ Issue”, Time, June 25, 2025.

Frazier, Kevin and Adam Thierer, “1,000 AI Bills: Time for Congress to Get Serious About Preemption”, Lawfare, May 9, 2025.

Kolas, Logan and Nate Karren, “Governors Break Ranks Over AI Regulation Patchwork”, Now + Next, Substack, Jun. 4, 2025.

Maslej, Nestor, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Njenga Kariuki, Emily Capstick, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, Tobi Walsh, Armin Hamrah, Lapo Santarlasci, Julia Betts Lotufo, Alexandra Rome, Andrew Shi, and Sukrut Oak, “Artificial Intelligence Index Report 2025”, Institute for Human-Centered Artificial Intelligence (HAI), Stanford University, April 2025.

Nguyen, Britney, “Big Tech’s AI spending spree is going strong. Here’s how big it could be this year”, Quartz, Mar. 5, 2025.

Oremus, Will and Andrea Jiménez, “Republican's’ bid to stop state AI laws heads for a crucial vote”, Washington Post, Jun. 26, 2025.

Endnotes

1. The text of The One Big Beautiful Bill Act (H.R. 1) is available at https://www.congress.gov/bill/119th-congress/house-bill/1/text. This bill was passed by the US House of Representatives on May 22, 2025. It is now with the Senate, trying to pass its version of the bill before July 4. The current moratorium text from the House Bill is in “Subtitle C—Communications”, “Part 2—Artificial Intelligence and Information Technology Modernization”, “Sec. 43201. Artificial intelligence and information technology modernization initiative”, part (3)(c). Specifically, the federal moratorium on state AI regulation says, “…no State or political subdivision thereof may enforce, during the 10-year period beginning on the date of the enactment of this Act, any law or regulation of that State or a political subdivision thereof limiting, restricting, or otherwise regulating artificial intelligence models, artificial intelligence systems, or automated decision systems entered into interstate commerce.”

2. See Adragna (2025).

3. My Abundance Institute colleague, Taylor Barkley has authored and coauthored a number of articles in the last month on the state AI regulatory moratorium. See Barkley (2025a, 2025b), Barkley and Griffin (2025).

4. See Adragna (2025). “Rep. Marjorie Taylor Greene (R-GA) and the House Freedom Caucus… opposed the AI moratorium.” And Senators Josh Hawley (R-MO) and Marsha Blackburn (R-TN) opposed the moratorium.

5. A link to the letter to Congress from 40 state attorneys general is here. See Washington Post commentary in Oremus and Jiménez (2025). Kolas and Karren (2025) also highlight governors opposing the AI moratorium.

6. Senator Ed Markey (D-MA) “has drafted an amendment to strip the [AI moratorium] provision” from the One Big Beautiful Bill Act, with his main argument against the provision being its limitation on states’ rights (see Chow, 2025; Oremus and Jiménez, 2025). Other arguments by legislators include

7. The Abundance Institute AI moratorium fact sheet is available at this link (see Abundance Institute, 2025 for full reference).

8. Frazier and Thierer (2025) highlight that in states, “one thousand artificial intelligence (AI) bills have already been introduced just over four months into 2025.”

9. See Sundar Pichai’s interview on the Lex Fridman June 5, 2025 podcast. Around the minute marker of 1 hour and 31 minutes, they begin talking about the productivity increases from AI. Fridman claims that his programming capability has become 5 times more productive due to AI. Pichai responds that Google’s internal estimates suggest that productivity of Google employees has increased by 10 percent due to AI. Alphabet, Inc. employed 183,323 employees as of Dec. 31, 2024 (See Alphabet, Inc., Dec. 31, 2024 quarterly 10K SEC filing).

10. Google has integrated its Gemini AI into its general search engine for all users. The major AI companies are investing billions of dollars into training their models to be better. Nguyen (2025) reported that the top US tech companies, Meta, Microsoft, Alphabet, and Amazon, “could spend a combined $320 billion on AI development and infrastructure this year.” The free and base models of the top AI companies have had drastic increases in capability in the last 12 months, and been much more broadly adopted across the economy (see Maslej, et al, 2025).