The first year of Donald Trump’s second term marked a clear institutional shift in US science and technology policy. This was not a set of scattered grants or isolated initiatives. According to the White House report Trump Administration Science & Technology Highlights: Year One, the US moved to a new governance model. The federal government stopped acting as a referee between interests and became an active player in the technology cycle. It rewrote rules, accelerated infrastructure, and pulled in private capital at scale.
The main story is not the amount of money or the number of executive orders. The administration openly links technology to power. Economic power. Industrial power. Strategic power. Artificial intelligence, energy, semiconductors, nuclear technology, quantum computing, and space are treated as parts of one system. Each supports the other. This is no longer a set of sectors. It is a coordinated architecture aimed at technological leadership of the United States.
Donald Trump placed artificial intelligence in the United States at the center of the new model. In the report, AI is not described as a promising industry. It is framed as a universal tool that must penetrate government, science, defense, energy, and transport.
That is why the first move was regulatory rollback. In the first days of the second term, the previous administration’s AI executive order was revoked. The White House argued that earlier requirements created excessive burdens and uncertainty for developers. In July 2025, the administration released the key document of the year: Winning the AI Race: America’s AI Action Plan. It became the backbone of the new US science and technology policy.
The AI Action Plan is not a classic strategy document. It lists more than ninety concrete federal actions across agencies. These actions focus on three goals:
- Accelerate AI innovation
- Scale domestic AI infrastructure
- Promote American AI abroad
These goals are not staged over time. They move in parallel. The Office of Management and Budget rewrote procurement and usage rules. Agencies were told clearly: excessive caution is no longer the priority. AI officers are expected to deploy systems, not delay them. Procurement is simplified. Reuse and fast scaling are encouraged.
Through the General Services Administration, federal agencies gain centralized access to commercial AI models at lower cost. The federal government effectively acts as a single customer. This reduces expenses, shortens implementation time, and creates a stable demand base for the private sector.
The report also addresses algorithmic neutrality. The language is pragmatic. For government use, AI must deliver reproducible results. Contracts include transparency and accountability clauses. This is framed not as ideology but as trust in automated decision making in defense, administration, and social policy.
In November 2025, the administration launched Genesis Mission. It is presented as the largest US scientific initiative in decades. The goal is blunt: double federal research productivity within ten years. AI is the key instrument. It operates on top of massive datasets, supercomputers, and experimental systems. The initiative connects 17 national laboratories of the Department of Energy, private companies, and leading universities. Exascale supercomputers are treated as routine tools, not showcase projects. They are used in medicine, energy, materials science, and defense.
Funding is distributed across several directions:
- A national platform for hosting AI models and scientific data
- Self learning models for research tasks
- Robotic labs and autonomous experiment management
- Large scale data preparation
Hundreds of millions of dollars were allocated at launch. More than twenty industrial partners joined. The National Science Foundation and the Department of Energy expanded access to datasets and integrated thousands of machine readable resources into the National AI Research Resource. The report explicitly describes an open AI ecosystem as a component of technological sovereignty of the United States.
AI is also deployed in cybersecurity. In the Artificial Intelligence Cyber Challenge, algorithms detected most vulnerabilities and automatically fixed a large share of them. Final solutions were published openly. For the administration, this shows that AI can operate inside critical infrastructure without growing bureaucracy.
The report is direct. Without cheap, reliable, scalable energy, an AI economy is impossible. The administration ties energy and AI together as a single policy track. In July 2025, an executive order accelerated data center construction. Environmental procedures were simplified. Federal land was opened for infrastructure. NEPA processes were adjusted through new regulations and court decisions. The energy policy focuses on base generation and grid resilience. Rules for backup power were eased. Grid connection for large loads was accelerated. Distributed generation received support.
The infrastructure logic culminates in the Stargate project. It is described as the largest AI infrastructure initiative in US history. Investments are estimated in the hundreds of billions of dollars. Up to twenty major data centers are planned across several states. Capacity is measured in gigawatts. The project is positioned as the anchor of the US AI infrastructure and adjacent industries.
The energy track connects directly to nuclear policy. The report speaks openly about a nuclear renaissance. Executive orders accelerate testing and deployment of new reactors. Regulatory barriers are lowered. Small modular and micro reactors are seen as power sources for AI infrastructure, industry, and defense.
Space is integrated into the same framework. The report sets a goal to deploy nuclear reactors on the Moon and in orbit. Preparation of a lunar reactor with a 2030 horizon is treated as a national initiative. Space is not symbolic. It extends energy and technology policy.
Semiconductors occupy a special place. The approach is direct and layered. The government uses investment, regulation, and trade tools at once. TSMC expansion in Arizona is highlighted. Investments in Intel and Micron Technology are part of the same strategy. An Investment Accelerator supports projects above one billion dollars. The objective is clear: reduce dependence on external supply chains and strengthen the domestic industrial core. Tariff and trade measures are used against practices that, in the administration’s view, distort competition.
Quantum technologies follow the same pattern. National quantum centers were updated. Federal funding increased. DARPA is testing the feasibility of an industrially useful quantum computer on an accelerated timeline. Military labs cooperate with industry on scalable quantum components.
The architecture ends with talent. Apprenticeship programs are expanded. AI literacy is integrated into vocational training. A US Tech Force initiative aims to attract engineers into government service. Human capital is treated as a bottleneck that must expand in parallel with infrastructure.
Taken together, the first year of Trump’s second term in science and technology looks like a shift to a project state. Regulatory barriers are reduced. Private capital receives signals of scale and predictability. Policy stops being reactive. The report is not neutral. It states priorities openly. Speed over process. Scale over pilots. Control of supply chains over abstract efficiency.
In this model, US science and technology policy is no longer a support function. It becomes the central instrument of economic strategy. The administration frames artificial intelligence in the United States, energy, and US semiconductors as parts of a single system designed to secure long term US technological leadership.
Sultan Valikhanov, expert of the EconomyKZ.org portal
