Not every state needs an AI hub

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COMMENTARY | States must be strategic in how they use their limited funding, and they can do so while addressing the priorities that matter most to their residents.

For the past year and a half, volatility in federal research and development funding has left state leaders asking what comes next. The instinct may be to think about replacement: which programs can states preserve, which gaps can they fill, and how much funding can they put on the table?

But states can’t simply replace the federal research enterprise. According to the National Center for Science and Engineering Statistics, federal agencies obligated $194.2 billion for R&D in fiscal 2024. At the same time, state government agencies reported $3.3 billion in R&D expenditures, equivalent to less than 2% of federal R&D obligations.

The opportunity for states is not to become smaller versions of the federal government. It’s to use limited funding strategically, placing it where it can attract additional research, talent and investment while addressing priorities that matter to residents.

Choose Sectors With a Credible Path to Innovation Leadership

Artificial intelligence, quantum computing, biotechnology, semiconductors and advanced manufacturing all have strong claims on public attention. It is understandable that states may want to jump into these fast-growing fields.

But a high-profile sector is not automatically the right focus for every state. A credible innovation ecosystem requires more than a designation, an incentive package or a new building. It depends on research depth, specialized talent, facilities, industry participation and a realistic path from discovery to application.

The better starting point is not, “Which sector is attracting the most attention?” It is, “Where does our state have a realistic opportunity to lead?”

Illinois and Tennessee offer useful examples of targeted action. In July 2026, each state announced $3 million in support for National Science Foundation X-Labs quantum teams that establish research, commercialization or business operations there. The amounts are small relative to federal R&D, but that’s the point. They are designed to amplify federal funding to draw teams and future growth toward a defined priority.

The lesson is not that every state should invest in quantum. It is that modest funding can matter when it reinforces a deliberate strategy.

Build From Strength and Public Need

A state’s strongest opportunity is likely to sit at the intersection of two questions: Where is strong research already happening, and where could it create meaningful value for residents or the state economy?

The answer may be agricultural technology in areas where farming is central to the economy, water management in a drought-prone region, rural health where access gaps persist, or advanced materials where universities and manufacturers already have deep expertise.

State R&D spending already reflects this practical orientation, with health, environmental and natural-resource research, and energy among the largest areas of state agency investment, according to NCSES.

But states enter this moment with very different budgets, institutions and research bases. The best use of tax dollars will depend on evidence about what each can protect, accelerate or translate into broader value.

Create Regional Hubs That Combine Complementary Strengths

Some states may find that their strongest advantage is not entirely within their borders. Research ecosystems are shaped by universities, laboratories, companies, infrastructure and talent markets that often span a wider region.

One state may have a leading university program, another specialized manufacturing capacity, and a third clinical, agricultural, energy or testing infrastructure. Trying to duplicate every asset may be more expensive and less effective than building around complementary strengths.

Federal regional innovation programs already support this rationale. The National Science Foundation’s Regional Innovation Engines and the Economic Development Administration’s Tech Hubs include multistate ecosystems in fields such as semiconductors, ocean technology, biotechnology and advanced energy.

States do not need to recreate those programs. But they can apply the same logic: understand the full array of regional capabilities and strengths before deciding what must be built independently and where collaboration could produce a stronger result.

How Can States Use Research Intelligence to Guide Funding Decisions?

These choices require states to say no as well as yes. Leaders need to distinguish a genuine competitive advantage from an attractive ambition, and a promising research cluster from one that still lacks the institutions, partners or translation capacity needed to grow.

Research intelligence can reveal more than where grants and publications are concentrated. Comparing those strengths with patents, company formation, employment and other outcomes can show where promising research is failing to move toward commercialization. A state may not need to put more money into basic research in an already strong field. 

The better investment may be shared infrastructure, commercialization support or partnerships that close the next gap in the pipeline. That evidence gives leaders a stronger basis for choosing among competing priorities and explaining why an investment represents the best use of public funds.

Turn Research Strengths Into Lasting Regional Value

Federal uncertainty may give states greater reason to shape their own innovation agendas. States will still have to make difficult choices about what to fund, what to pursue with partners, and what not to pursue at all. The states that benefit most will not necessarily be those that spend the most or announce the most hubs. 

Used well, targeted state investment can do more than soften the effects of federal volatility. It can preserve valuable capabilities, move promising research toward practical use, and help build regional innovation ecosystems with a stronger chance of lasting.

Xueying (Shirley) Han is head of research analytics at Digital Science.

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