The State AI Readiness Divide: Which States Are Actually Helping Their People Learn and Use AI?
An Underwood Partners Collaboration Evangelist White Paper
By Craig Underwood in collaboration with ChatGPT
Artificial intelligence is often discussed as if it were a single national wave: ChatGPT appears, companies scramble, schools debate cheating, workers worry, and everyone tries to keep up.
But that is not what is happening.
AI adoption is not spreading evenly across the United States. It is being shaped by public choices — by whether states are giving government employees secure AI tools, helping educators understand how to teach with AI, investing in public higher education, and making AI training available to residents.
In other words, the next AI divide may not be just between people who use AI and people who do not.
It may be between states that help their people learn AI — and states that leave them to figure it out alone.
That was the hypothesis behind this research. I wanted to know whether states differ meaningfully in their investment in and support for AI, and whether Massachusetts — my home commonwealth — is at or near the top.
The short answer: yes.

The longer answer is more interesting.
State AI readiness evaluation criteria.
For this analysis, we ranked all 50 states plus Washington, D.C. on a 100-point AI readiness index. The index was not designed to measure private-sector AI activity alone. Silicon Valley venture capital, university research labs, and AI startups matter, but they were not the core question.
The question was civic and public:
Which states are helping their residents, students, educators, public employees, and institutions actually learn and use AI?
The ranking used four categories:

We gave the most credit for concrete implementation: secure AI tools, training programs, statewide public AI portals, public higher-ed credentials, K–12 AI guidance, workforce-development programs, and published use cases.
We gave much less credit for task forces, commissions, executive orders, or legislation unless they were tied to real funding, training, tool access, implementation, or public-facing programs.
We also distinguished among three policy postures:
| Policy posture | Meaning |
| Responsible AI enablement | The state encourages AI adoption while providing guardrails, training, privacy protections, and human oversight. |
| Neutral risk management | The state is studying or regulating AI but has limited public evidence of broad adoption support. |
| Restrictive or chilling policy | The state’s actions appear more likely to discourage useful AI adoption than to enable it. |
That distinction matters. AI governance is not automatically anti-AI. In fact, the most impressive states are not choosing between innovation and responsibility. They are trying to do both.
The top 10 states and jurisdictions
The highest-ranked states are not merely “interested” in AI. They are putting AI into public systems.
| Rank | State / Jurisdiction | Score | Tier |
| 1 | Massachusetts | 91 | AI Readiness Leader |
| 2 | Utah | 88 | AI Readiness Leader |
| 3 | New York | 86 | AI Readiness Leader |
| 4 | New Jersey | 84 | AI Readiness Leader |
| 5 | California | 82 | AI Readiness Leader |
| 6 | District of Columbia | 80 | AI Readiness Leader |
| 7 | Maryland | 78 | AI Readiness Leader |
| 8 | Colorado | 77 | AI Readiness Leader |
| 9 | Ohio | 76 | AI Readiness Leader |
| 10 | Georgia | 75 | AI Readiness Leader |
Massachusetts ranks first because it appears to have the most complete public AI readiness strategy. The Commonwealth has launched a secure enterprise AI assistant for executive-branch employees, partnered with Google and the Massachusetts AI Hub to offer no-cost AI training to residents, and developed K–12 AI guidance and educator resources through the Department of Elementary and Secondary Education.[1]
Utah ranks second and may be the national leader in education-focused AI readiness. Utah has announced a statewide AI Workforce Credential for public college and university graduates and a statewide partnership to bring Gemini for Education to K–12 schools.[2]
New York ranks third because of the scale of its state workforce rollout. The state has expanded AI training and a secure AI tool, AI Pro, to more than 100,000 state employees, while also investing in Empire AI, a major public-interest AI research consortium.[3]
New Jersey ranks fourth because it has one of the clearest examples of practical public-sector AI implementation. Its NJ AI Assistant has been used by about 20,000 state employees, with more than 300,000 sessions and 1 million prompts as of February 2026.[4]
California ranks fifth because it combines a massive AI economy with state and local government training, K–12 guidance, higher-ed activity, and workforce-disruption planning. But California’s posture is more complex than the top four because it is also heavily focused on regulation and labor-market disruption.
The bottom 10 states
The bottom states should not be described as “anti-AI.” That would overstate the evidence. In many cases, they are better described as states with limited public evidence of broad statewide AI enablement.
| Rank | State | Score | Tier |
| 42 | West Virginia | 42 | Limited / Early |
| 43 | Wyoming | 41 | Limited / Early |
| 44 | New Hampshire | 40 | Limited / Early |
| 45 | Alaska | 39 | Limited / Early |
| 46 | North Dakota | 38 | Limited / Early |
| 47 | Louisiana | 37 | Limited / Early |
| 48 | Nebraska | 36 | Limited Public Evidence |
| 49 | Kansas | 34 | Limited Public Evidence |
| 50 | South Dakota | 32 | Limited Public Evidence |
| 51 | Arkansas | 30 | Limited Public Evidence |
This is an important methodological point. A low ranking does not prove that nothing is happening. It means I found less recent public evidence that the state is combining AI tool access, training, education strategy, workforce development, and responsible-use infrastructure into a coherent statewide approach.
That distinction matters because the AI landscape is changing fast. A state could move from the bottom tier to the middle quickly if it launched a statewide AI training portal, gave public employees secure AI access, published K–12 guidance, and used community colleges to scale workforce credentials.
The map tells the story.
The lead map shows a striking pattern: AI readiness is not evenly distributed.
Some states are already treating AI as a public-capacity project. They help people learn, practice, and use AI responsibly. Others are still closer to the study-and-watch stage.
National research supports this uneven picture. Code for America’s 2026 Government AI Landscape Assessment concluded that states are at different stages of AI adoption, ranging from readiness and piloting to implementation and impact.[5] The National Conference of State Legislatures has also tracked a surge in state AI activity, reporting that all 50 states, Puerto Rico, the Virgin Islands, and D.C. introduced AI-related legislation in 2025, while 38 states adopted or enacted around 100 measures.[6]
But legislation alone is not the same as readiness.
The leading states are doing more than passing bills. They are creating tools, training people, building public infrastructure, and giving educators and public employees permission to experiment within guardrails.

What the K–12 comparison adds
We also compared each state’s AI readiness rank with its K–12 education rank, using WalletHub’s 2026 public school system ranking as the K–12 comparison source.[7]
The result is one of the most interesting parts of the analysis.
Good schools help, but they do not automatically produce AI readiness.
Some states have both strong K–12 systems and strong AI readiness. Massachusetts is the clearest example: it ranked first in both our AI readiness index and the WalletHub K–12 ranking. New Jersey, New York, Maryland, Virginia, Connecticut, Rhode Island, Wisconsin, Pennsylvania, and Utah also appear in the high-education / high-AI zone.
These states are in the strongest strategic position. They have educational capacity and are beginning to convert that capacity into AI readiness.
But the scatterplot also reveals two other important patterns.
First, some states appear to be using AI as a leapfrog strategy. California, Georgia, Ohio, North Carolina, Colorado, Oregon, Arizona, Texas, and New Mexico do not rank at the very top on K–12 education, but they show stronger public evidence of AI support and investment than their education rankings alone would predict.
That may be strategically wise. AI training can scale faster than traditional education reform. Community colleges, public universities, workforce boards, libraries, and state agencies can help adults, small businesses, and public employees gain practical AI skills quickly.
Second, some states with relatively strong K–12 systems appear to be underleveraging that advantage. New Hampshire, Nebraska, North Dakota, Montana, Wyoming, Indiana, and Vermont all have educational strengths, but weaker public evidence of broad AI readiness.
That is the danger for high-education states: yesterday’s education advantage does not automatically become tomorrow’s AI advantage.
Four strategic positions for states
The AI readiness vs. K–12 education scatterplot creates four useful strategic categories.
- High K–12 / High AI: Compounding advantage
These states have the strongest starting position. They have relatively strong education systems and are also investing in public AI readiness.
Strategic imperative: move from AI readiness to AI advantage.
These states should publish public AI use-case libraries, scale AI literacy expectations, train public employees, support educator professional development, fund public higher-ed credentials, and measure productivity and learning gains.
The risk is complacency. Strong schools and strong universities are not enough. AI advantage requires structured implementation.
- Lower K–12 / High AI: Leapfrog opportunity
These states may be using AI as a way to accelerate workforce development and public-sector modernization.
Strategic imperative: use AI as a human-capital accelerator.
These states should focus on community colleges, adult learners, small-business training, teacher productivity, student supports, and accessible AI credentials.
The opportunity is speed. A state does not need to wait 20 years to improve every K–12 metric before helping people build useful AI skills.
The risk is inequity. If AI programs primarily benefit already-advantaged residents, AI may widen internal gaps.
- High K–12 / Lower AI: Underleveraged education advantage
These states may have strong educational foundations but less visible statewide AI implementation.
Strategic imperative: convert education strength into AI readiness.
The playbook is straightforward: issue practical K–12 AI guidance, train educators, give public employees secure tools, create public AI learning portals, and use public universities and community colleges as AI training engines.
The risk is losing ground to states with weaker traditional education systems but stronger AI implementation strategies.
- Lower K–12 / Lower AI: Double catch-up challenge
These states face the hardest strategic position.
Strategic imperative: start with practical, low-cost, high-leverage AI readiness moves.
They should create a statewide AI learning portal, train state employees in responsible AI use, publish K–12 AI guidance, partner with community colleges on short credentials, and build a public use-case library.
The risk is that AI becomes another driver of regional inequality.
The deeper point: AI readiness is public infrastructure.
The best states are not treating AI as a gadget. They are treating AI readiness as a form of civic infrastructure.
That means giving people:
- access,
- training,
- permission,
- examples,
- guardrails, and
- time to practice.
A state employee who has access to a secure AI assistant can learn by doing. A teacher with practical guidance can move beyond fear and confusion. A community college student with an AI credential can enter the labor market with greater confidence. A small business owner with free training can experiment without hiring a consultant. A resident with access to a public AI learning portal can begin without needing to be part of the technology sector.
That is the difference between AI as a private advantage and AI as a public capability.
Why Massachusetts matters
Massachusetts is a particularly useful case because it already had advantages: great universities, strong K–12 performance, a dense innovation economy, world-class hospitals, and a highly educated workforce.
But those advantages alone are not what made Massachusetts rank first.
What matters is that Massachusetts appears to be converting its existing advantages into public AI readiness.
The Commonwealth is giving executive-branch employees secure AI access. It is offering residents no-cost AI training. It is building a public AI Hub. It is supporting K–12 educators with guidance and resources.
That combination is the key.
Massachusetts is not simply an AI-rich state. It is investing to become an AI-ready Commonwealth.
The policy lesson
The policy lesson is not that every state should copy Massachusetts exactly. States differ in size, economy, demographics, politics, education systems, and fiscal capacity.
But every state can do five things:
- Give public employees safe AI access and training.
- Publish practical K–12 AI guidance.
- Use public higher education and community colleges to scale AI credentials.
- Create a public AI learning portal for residents and small businesses.
- Measure outcomes and publish use cases.
The first states to do these things well will have an advantage.
Not just a technology advantage. A civic advantage.
Final thought
AI adoption is often framed as an individual responsibility: learn the tools, keep up, do not fall behind.
But this research suggests that public leadership matters enormously.
Some states are making AI learning easier, safer, and more accessible. Others are leaving residents, teachers, workers, and public employees to navigate the AI era largely on their own.
That is the state AI readiness divide.
And it may become one of the most important competitiveness and equity issues of the next decade.
Endnotes
[1] Massachusetts state AI assistant materials; Massachusetts-Google free AI training announcement; Massachusetts AI Hub; Massachusetts Department of Elementary and Secondary Education AI resources.
[2] Utah System of Higher Education announcement of statewide AI Workforce Credential; Google announcement of Gemini for Education partnership with Utah K–12 schools.
[3] New York Governor’s Office announcement of AI Pro and AI training expansion to state workforce; Empire AI materials.
[4] New Jersey Innovation Authority, NJ AI Assistant project page and 2026 update.
[5] Code for America, 2026 Government AI Landscape Assessment.
[6] National Conference of State Legislatures, 2025 AI legislation summary and AI legislation database.
[7] WalletHub, 2026 public school system ranking.
Source links for the article endnotes
Massachusetts has an official enterprise AI assistant page, and Google announced no-cost AI training for Massachusetts residents through the Massachusetts AI Hub and Grow with Google. (Massachusetts Government)
Utah’s higher-ed system announced a no-cost AI Workforce Credential for more than 50,000 public college and university graduates, and Google announced Gemini for Education access for every Utah K–12 school beginning in the 2026–2027 school year. (Utah System of Higher Education)
New York announced expansion of AI education and AI Pro to more than 100,000 state employees, while New Jersey reported about 20,000 state employees using its AI Assistant, with more than 300,000 sessions and 1 million prompts as of February 2026. (Governor Kathy Hochul)
Code for America’s 2026 Government AI Landscape Assessment evaluates state AI adoption across readiness, piloting, implementation, and impact, while NCSL tracks AI legislation across states and reported that 38 states adopted or enacted around 100 AI-related measures in 2025. (Code for America)
For education context, Playlab reports that 36 states plus Puerto Rico had official K–12 AI guidance or policy frameworks as of May 2026, and FutureEd tracked 71 AI-in-education bills across 27 states during the 2026 legislative session. (learn.playlab.ai










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