Thinking that
earns its keep

Most venture-backed AI companies treat federal funding as something that belongs to an earlier stage — a pre-seed play for university spinouts and garage-phase startups. This is a strategic error worth millions. The NSF's SBIR and STTR programs routinely award between $250,000 and over $1 million per project, and they are explicitly designed for small businesses with fewer than 500 employees developing high-potential technologies. That description fits the majority of Series B AI companies in the United States.

The math is straightforward. A $1 million SBIR Phase II award is non-dilutive capital — it costs your cap table nothing. At a stage where every equity round is priced against traction and burn rate, that is not a rounding error. It is a strategic asset that extends runway, funds R&D that venture investors want to see de-risked, and signals to future investors that your technology has passed federal peer review.

In March 2026, the NSF announced the AI-Ready America initiative in partnership with the Department of Labor, the Small Business Administration, and USDA's National Institute of Food and Agriculture. The program is establishing AI-Ready Coordination Hubs in every U.S. state and territory, and its three focus areas — expanding AI literacy, equipping small businesses with AI adoption tools, and building applied learning pathways — create direct alignment opportunities for AI companies whose products serve these missions.

The NSF's Artificial Intelligence topic under SBIR/STTR is explicitly broad, covering deep learning systems, computer vision, natural language processing, and any AI system that interacts with humans in personalized contexts. The program emphasizes technologies that are safe, robust against adversaries, privacy-preserving, and computationally efficient. If your product meets those criteria — and most responsible AI companies are building toward them — the alignment is not a stretch. It is a match.

But here is where most growth-stage companies stumble: compliance architecture. Federal grants come with reporting requirements, cost allocation standards, and restrictions on how funds can be deployed. Companies accustomed to venture capital — where a wire transfer arrives and a board seat is the primary oversight mechanism — are not structured for this. The result is either botched applications that never get funded, or worse, funded grants that trigger compliance failures downstream.

New York State compounds the opportunity. The Innovation Matching Grants Program through Empire State Development's NYSTAR provides matching funds for federal SBIR and STTR awards — up to $100,000 for Phase I and up to $200,000 for Phase II. This means a New York-based AI company that secures a $1 million federal SBIR Phase II can stack an additional $200,000 in state matching funds on top — all non-dilutive, all equity-preserving.

The companies that capture this capital are the ones that treat government funding not as an afterthought but as a parallel capital strategy — one that requires its own compliance infrastructure, its own application expertise, and its own advisory relationship. The ones that don't will continue to dilute themselves unnecessarily while their competitors compound an advantage that grows with every funding cycle.

Section 48D of the Internal Revenue Code provides a 25% investment tax credit for qualified investments in advanced manufacturing facilities — facilities whose primary purpose is manufacturing semiconductors or the equipment used to manufacture them. The credit has been one of the most powerful incentives in the CHIPS and Science Act, helping catalyze over $500 billion in announced private-sector investments across more than 100 projects nationwide. But the statute contains a hard deadline: the credit does not apply to property for which construction begins after December 31, 2026.

That deadline is now eight months away, and for many manufacturers, the compliance requirements to establish that construction has "begun" are more technical than they realize.

The final regulations published by Treasury and the IRS in October 2024 provide two methods for establishing that construction has begun. The first is the physical work test — demonstrating that physical work of a significant nature has commenced on the project. The second is the 5% safe harbor — demonstrating that the taxpayer has paid or incurred at least 5% of the total cost of the qualified property. Either method satisfies the requirement, but both demand documentation and planning that cannot be improvised in the final weeks of the year.

For companies pursuing multi-year construction projects — which describes virtually every semiconductor fabrication facility — the continuity requirement is equally critical. Once construction begins, the taxpayer must demonstrate continuous efforts to advance the project. The final regulations provide that a taxpayer satisfies this requirement by paying or incurring 5% or more of total project costs each calendar year after the year construction began. Interruptions due to supply chain delays, permitting issues, or labor shortages are recognized, but they must be documented and defensible.

The stakes are significant. Intel's finalized CHIPS Act award alone is $7.86 billion in direct funding, and the company intends to claim Section 48D credits on qualified investments exceeding $100 billion. But the credit is not reserved for the industry's largest players. The final regulations expanded the definition of semiconductor manufacturing to include wafer production, assembly, testing, and advanced packaging. Any company whose primary business involves these activities — and that includes dozens of mid-market manufacturers in the semiconductor supply chain — is potentially eligible.

Meanwhile, the Semiconductor Industry Association and 16 member companies have formally urged Congress to extend the credit beyond its 2026 expiration and expand eligibility to cover the full supply chain, including R&D and chip design. Proposed legislation — the STAR Act and the BASIC Act — would accomplish both. But those bills have not passed, and planning based on legislation that hasn't been enacted is not planning. It is hope.

What manufacturers need right now is a structured assessment: Does your facility qualify as an advanced manufacturing facility under the final regulations? Has construction "begun" under either the physical work test or the 5% safe harbor? Can you document continuous efforts going forward? And critically — are you at risk of an "applicable transaction" involving material expansion in a foreign country of concern, which would trigger recapture of previously claimed credits within a 10-year window?

These are questions that require cross-disciplinary expertise: tax, legal, and regulatory. They cannot be answered by a tax advisor alone, and they certainly cannot be answered in December.

When the Elementary and Secondary School Emergency Relief (ESSER) funds expired, the education technology industry braced for contraction. The three rounds of ESSER funding — totaling roughly $190 billion — had powered an unprecedented technology buying cycle in American schools. Districts purchased devices, platforms, and subscriptions at a pace that many EdTech companies mistook for normal demand. The "ESSER cliff" was a correction, and it was painful.

But the next wave of education funding is already arriving — and it looks fundamentally different. Where ESSER was broad, crisis-driven, and loosely monitored, the emerging federal funding landscape for education technology is narrow, evidence-based, and AI-focused.

The Accelerate organization's Call for Effective Technology program offers grants of $150,000 to $250,000 for AI-powered and educational technology tools deployed during the 2026–27 school year. The explicit requirements are revealing: tools must be grounded in learning science, must enable personalized learning and individualized instruction, and must be currently in use with real students during the school day. Tools that provide standardized, one-size-fits-all experiences are specifically excluded from eligibility.

Federal formula grants remain available through established channels: Title II-A (Supporting Effective Instruction), Title I Part A (Improving Basic Programs), and Title III Part A (English Language Acquisition). These programs provide automatic grants to states based on formula criteria, and a portion of these funds can be used by districts to purchase qualifying educational technology. But the competitive landscape has shifted: districts are now under pressure to demonstrate that their technology purchases produce outcomes, not just access.

For EdTech companies, this shift creates both an opportunity and a compliance challenge. The opportunity is that AI-powered adaptive learning platforms — those that genuinely personalize content, pacing, and instructional approaches — are exactly what the new funding programs are designed to support. The challenge is that eligibility increasingly requires evidence of efficacy: pilot data, independent evaluation, and clear theories of action. The era of selling software to schools on a demo and a promise is ending.

Companies that position themselves as evidence-ready partners — with compliance infrastructure, outcome measurement, and grant-aligned implementation models — will capture the next funding cycle. Those that treat government funding as a sales channel rather than a regulatory relationship will not.

The window is open now. Most federal grant applications for the 2026–27 cycle close by mid-2026. State-level programs operate on their own calendars. The companies that move first — with structured applications, defensible compliance frameworks, and genuine evidence of student impact — will establish positions that compound over multiple funding cycles.

New York State has committed over $400 million in public and private investment to the Empire AI Consortium — a first-in-the-nation partnership among the state's research universities to advance AI for the public good. Governor Hochul's fiscal year 2026 budget added $90 million in capital funding to expand computing capacity, with an additional $25 million from the SUNY system and $50 million in matching funds from new consortium members including the University of Rochester, Rochester Institute of Technology, and Icahn School of Medicine at Mount Sinai.

This is not a grant program in the traditional sense. It is infrastructure for an ecosystem — one that will generate research partnerships, workforce pipelines, procurement opportunities, and commercial spinouts for years to come. The companies that position themselves within this ecosystem now will have structural advantages that late entrants cannot replicate.

But Empire AI is only one layer. In the state legislature, the Artificial Intelligence Literacy Act — introduced in both the Senate and Assembly during the 2025–2026 session — would establish a competitive AI Literacy Grant Program under the Digital Equity Competitive Grant Program. The bill targets public schools, community colleges, higher education institutions, and nonprofit organizations, with the explicit goal of expanding equitable access to AI education across the state.

For AI and EdTech companies, the implications are concrete. If the AI Literacy Act passes, it will create a funded demand channel for AI education tools, curricula, and training programs. Companies that can demonstrate alignment with the bill's priorities — digital equity, workforce readiness, and responsible AI engagement — will be positioned to serve a state-funded market before most competitors realize it exists.

At the state incentive level, New York's NYSTAR Innovation Matching Grants Program provides matching funds for federal SBIR/STTR awards to small businesses with 100 or fewer employees. And individual AI companies have begun securing significant state tax incentive packages — a signal that New York is actively competing for AI investment at the company level, not just the institutional level.

The strategic lesson is this: New York's AI investment strategy is multi-layered and institutional. It operates simultaneously through research consortia, legislative initiatives, workforce development programs, state incentive packages, and matching fund programs. Companies that engage with only one layer miss the compounding effect of engaging with several. The most effective approach is to map your business against the full architecture — and pursue alignment at every level where it exists.

This requires a structured assessment: Which programs is your company eligible for? Where do your products align with the state's stated priorities? What compliance infrastructure do you need to pursue multiple funding streams simultaneously without creating conflicts? And critically — what is the sequencing strategy that maximizes your positioning over the next 18 months?

Government funding is having a moment. Between CHIPS Act incentives, NSF AI programs, state-level matching grants, and the expanding landscape of federal appropriations for re-industrialization and education technology, mid-market companies are being told — by their advisors, their investors, and increasingly by their competitors — that they should be pursuing public capital. And they should be. But the conversation about pursuit is running ahead of the conversation about readiness, and that gap is where the most expensive mistakes in government funding occur.

The pattern is predictable. A company identifies a grant opportunity. Leadership gets excited about non-dilutive capital. The application is prepared — often by a consultant who specializes in grant writing but not in compliance architecture — and submitted. If the application succeeds, the company receives funding and celebrates. Six months later, a compliance review reveals that the company's cost allocation structure does not meet federal standards, or that a workforce reporting requirement conflicts with existing HR systems, or that a restriction on foreign transactions impacts an existing supply chain relationship. The celebration becomes a remediation project. In the worst cases, it becomes a recapture event.

This is why feasibility assessment should precede grant pursuit, not follow it. A structured pre-application assessment answers the questions that determine whether a funding opportunity is genuinely advantageous — or whether it creates more risk than it resolves.

The assessment begins with structural eligibility: Does your corporate structure, ownership composition, and operational geography satisfy the program's requirements? For Section 48D tax credits, this includes confirming that you are not a "foreign entity of concern" and that you have not engaged in an "applicable transaction" involving material expansion in a foreign country of concern. For SBIR/STTR programs, it means confirming that your company has fewer than 500 employees, is majority-owned by U.S. citizens or permanent residents, and is not majority-controlled by multiple venture capital or private equity firms. These are threshold questions, and companies that discover disqualifying factors after investing months in an application have wasted resources they cannot recover.

Next is operational readiness: Can your organization absorb and deploy the funded activities within its existing operational structure? Do you have the financial controls to track grant expenditures separately from commercial operations? Can you meet the reporting requirements — which for federal grants can include quarterly progress reports, annual financial audits, and milestone-based disbursement documentation?

Finally, there is strategic alignment: Does this funding opportunity advance your business strategy, or does it distort it? A grant that requires you to redirect engineering resources toward a use case that does not serve your core product roadmap may cost more in opportunity than it delivers in capital. The best government funding strategies are the ones where the funded activities and the company's organic growth trajectory are pointing in the same direction.

Companies that conduct this assessment before they apply make better decisions about which opportunities to pursue, submit stronger applications because their compliance narratives are grounded in actual infrastructure, and — when they are funded — execute without the remediation cycles that plague companies that skipped the assessment. The investment in feasibility is not a cost. It is the highest-return line item in the government funding process.