The Tech Sales Newsletter #103: The AI Action Plan
“Today, a new frontier of scientific discovery lies before us, defined by transformative technologies such as artificial intelligence… Breakthroughs in these fields have the potential to reshape the global balance of power, spark entirely new industries, and revolutionize the way we live and work. As our global competitors race to exploit these technologies, it is a national security imperative for the United States to achieve and maintain unquestioned and unchallenged global technological dominance. To secure our future, we must harness the full power of American innovation.”
It's difficult to overstate how influential "America's AI Action Plan" will be if implemented, even partially. It sets in motion a large-scale transformation of a country that is betting big on AI. The implications for tech sales are numerous and severely underreported.
Let's dig in.
The key takeaway
For tech sales: The federal government is about to become the biggest driver of AI software acquisition through streamlined procurement and mandated AI adoption across every agency. Regulatory sandboxes in healthcare, finance, and other heavily regulated industries mean your enterprise deals just got 10x easier to close now that many of the excuses for avoiding evaluating these tools are going away. International expansion is also going to be a great play, but only within "American AI aligned" countries.
For investors: Infrastructure plays and companies building AI tools for government/enterprise adoption/compliance are the obvious winners here. The regulatory clarity and government backing create a predictable growth environment, but only for companies that can credibly claim American alignment and security standards. The wider investment play into land and energy companies that will feed the data centers is also on the table.
It’s AI morning again in America
Winning the AI race will usher in a new golden age of human flourishing, economic competitiveness, and national security for the American people. AI will enable Americans to discover new materials, synthesize new chemicals, manufacture new drugs, and develop new methods to harness energy—an industrial revolution. It will enable radically new forms of education, media, and communication an information revolution. And it will enable altogether new intellectual achievements: unraveling ancient scrolls once thought unreadable, making breakthroughs in scientific and mathematical theory, and creating new kinds of digital and physical art—a renaissance. An industrial revolution, an information revolution, and a renaissance—all at once. This is the potential that AI presents. The opportunity that stands before us is both inspiring and humbling. And it is ours to seize, or to lose.
Unlike the corporate narrative in enterprises, the vision offered here is far more ambitious. AI is not seen as an automation tool to squeeze margins, but as the lever to propel the nation into a new golden age.
America’s AI Action Plan has three pillars: innovation, infrastructure, and international diplomacy and security. The United States needs to innovate faster and more comprehensively than our competitors in the development and distribution of new AI technology across every field, and dismantle unnecessary regulatory barriers that hinder the private sector in doing so.
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We need to build and maintain vast AI infrastructure and the energy to power it. To do that, we will continue to reject radical climate dogma and bureaucratic red tape, as the Administration has done since Inauguration Day. Simply put, we need to “Build, Baby, Build!” We need to establish American AI—from our advanced semiconductors to our models to our applications—as the gold standard for AI worldwide and ensure our allies are building on American technology.
For this to work, it requires a broad focus across relaxing red tape, scaling energy production, and ensuring that American companies are given access to external markets and not damaged by excessive regulation from abroad.
Several principles cut across each of these three pillars. First, American workers are central to the Trump Administration’s AI policy. The Administration will ensure that our Nation’s workers and their families gain from the opportunities created in this technological revolution. The AI infrastructure buildout will create high-paying jobs for American workers. And the breakthroughs in medicine, manufacturing, and many other fields that AI will make possible will increase the standard of living for all Americans. AI will improve the lives of Americans by complementing their work—not replacing it.
Second, our AI systems must be free from ideological bias and be designed to pursue objective truth rather than social engineering agendas when users seek factual information or analysis. AI systems are becoming essential tools, profoundly shaping how Americans consume information, but these tools must also be trustworthy.
Finally, we must prevent our advanced technologies from being misused or stolen by malicious actors as well as monitor for emerging and unforeseen risks from AI. Doing so will require constant vigilance.
The other side of the bargain is what the government expects in return for this extremely favorable framework. Structurally, the expectation is that this should benefit predominantly US workers, that the models and applications would not promote anti-American views, and that every operator needs to build with security in mind. Now the full plan is 28 pages, so let's try to focus on several key initiatives.
Remove Red Tape and Onerous Regulation
To maintain global leadership in AI, America’s private sector must be unencumbered by bureaucratic red tape. President Trump has already taken multiple steps toward this goal, including rescinding Biden Executive Order 14110 on AI that foreshadowed an onerous regulatory regime.
AI is far too important to smother in bureaucracy at this early stage, whether at the state or Federal level. The Federal government should not allow AI-related Federal funding to be directed toward states with burdensome AI regulations that waste these funds, but should also not interfere with states’ rights to pass prudent laws that are not unduly restrictive to innovation.
Recommended Policy Actions
• Led by the Office of Science and Technology Policy (OSTP), launch a Request for Information from businesses and the public at large about current Federal regulations that hinder AI innovation and adoption, and work with relevant Federal agencies to take appropriate action.
• Led by the Office of Management and Budget (OMB) and consistent with Executive Order 14192 of January 31, 2025, “Unleashing. Prosperity Through Deregulation,” work. with all Federal agencies to identify, revise, or repeal regulations, rules, memoranda, administrative orders, guidance documents, policy statements, and interagency agreements that unnecessarily hinder AI development or deployment.
• Led by OMB, work with Federal agencies that have AI-related discretionary funding programs to ensure, consistent with applicable law, that they consider a state’s AI regulatory climate when making funding decisions and limit funding if the state’s AI regulatory regimes may hinder the effectiveness of that funding or award.
• Led by the Federal Communications Commission (FCC), evaluate whether state AI regulations interfere with the agency’s ability to carry out its obligations and authorities under the Communications Act of 1934.5
• Review all Federal Trade Commission (FTC) investigations commenced under the previous administration to ensure that they do not advance theories of liability that unduly burden AI innovation. Furthermore, review all FTC final orders, consent decrees, and injunctions, and, where appropriate, seek to modify or set-aside any that unduly burden AI innovation.
As long as a company is able to make a case for why their product is being delayed or can't launch because of regulations, it will be reviewed and potentially resolved. Adopting this across a variety of agencies and jurisdictions (state and federal level) ensures broad application.
Ensure that Frontier AI Protects Free Speech and American Values
AI systems will play a profound role in how we educate our children, do our jobs, and consume media. It is essential that these systems be built from the ground up with freedom of speech and expression in mind, and that U.S. government policy does not interfere with that objective.
We must ensure that free speech flourishes in the era of AI and that AI procured by the Federal government objectively reflects truth rather than social engineering agendas.
Recommended Policy Actions
• Led by the Department of Commerce (DOC) through the National Institute of Standards and Technology (NIST), revise the NIST AI Risk Management Framework to eliminate references to misinformation, Diversity, Equity, and Inclusion, and climate change.
• Update Federal procurement guidelines to ensure that the government only contracts with frontier large language model (LLM) developers who ensure that their systems are objective and free from top-down ideological bias.
• Led by DOC through NIST’s Center for AI Standards and Innovation (CAISI), conduct research and, as appropriate, publish evaluations of frontier models from the People’s Republic of China for alignment with Chinese Communist Party talking points and censorship.
While the stated goal is to remove ideological bias, the goal is ultimately to adopt models that represent the American point of view to the world. Together with the last point, this sets up the structural West vs. East divide in technology that will define the future going forward.
If the computing revolution of the last 40 years was fuel for globalism, the AI revolution will firmly establish a very different dynamic. Outside of the obvious implications from a national security point of view, this should also be a signal to those of you who are part of APAC teams that your future employer will probably operate in fixed markets rather than trying to expand. Your long-term viability within that company will also depend on which direction your market leans.
Encourage Open-Source and Open-Weight AI
Open-source and open-weight AI models are made freely available by developers for anyone in the world to download and modify. Models distributed this way have unique value for innovation because startups can use them flexibly without being dependent on a closed model provider. They also benefit commercial and government adoption of AI because many businesses and governments have sensitive data that they cannot send to closed model vendors. And they are essential for academic research, which often relies on access to the weights and training data of a model to perform scientifically rigorous experiments.
We need to ensure America has leading open models founded on American values. Open-source and open-weight models could become global standards in some areas of business and in academic research worldwide. For that reason, they also have geo strategic value. While the decision of whether and how to release an open or closed model is fundamentally up to the developer, the Federal government should create a supportive environment for open models.
Recommended Policy Actions
• Ensure access to large-scale computing power for startups and academics by improving the financial market for compute. Currently, a company seeking to use large-scale compute must often sign long-term contracts with hyperscalers—far beyond the budgetary reach of most academics and many startups. America has solved this problem before with other goods through financial markets, such as spot and forward markets for commodities. Through collaboration with industry, NIST at DOC, OSTP, and the National Science Foundation’s (NSF) National AI Research Resource (NAIRR) pilot, the Federal government can accelerate the maturation of a healthy financial market for compute.
• Partner with leading technology companies to increase the research community’s access to world-class private sector computing, models, data, and software resources as part of the NAIRR pilot.
• Build the foundations for a lean and sustainable NAIRR operations capability that can connect an increasing number of researchers and educators across the country to critical AI resources.
• Continue to foster the next generation of AI breakthroughs by publishing a new National AI Research and Development (R&D) Strategic Plan, led by OSTP, to guide Federal AI research investments.
• Led by DOC through the National Telecommunications and Information Administration (NTIA), convene stakeholders to help drive adoption of open-source and open-weight models by small and medium-sized businesses.
In the past 6 months, open-source has been heavily dominated by DeepSeek and Qwen releases, with open-weights models from US companies starting to fall behind. Rather than trying to push Meta and xAI into changing this dynamic, the preference is to make more capacity available across academia and small players that are currently priced out of meaningful opportunities. So not only will there be a push to make compute available, but also greater promotion of existing models that can be utilized across the economy.
Enable AI Adoption
Today, the bottleneck to harnessing AI’s full potential is not necessarily the availability of models, tools, or applications. Rather, it is the limited and slow adoption of AI, particularly within large, established organizations. Many of America’s most critical sectors, such as healthcare, are especially slow to adopt due to a variety of factors, including distrust or lack of understanding of the technology, a complex regulatory landscape, and a lack of clear governance and risk mitigation standards. A coordinated Federal effort would be beneficial in establishing a dynamic, “try-first” culture for AI across American industry.
Recommended Policy Actions
• Establish regulatory sandboxes or AI Centers of Excellence around the country where researchers, startups, and established enterprises can rapidly deploy and test AI tools while committing to open sharing of data and results. These efforts would be enabled by regulatory agencies such as the Food and Drug Administration (FDA) and the Securities and Exchange Commission (SEC), with support from DOC through its AI evaluation initiatives at NIST.
• Launch several domain-specific efforts (e.g., in healthcare, energy, and agriculture), led by NIST at DOC, to convene a broad range of public, private, and academic stakeholders to accelerate the development and adoption of national standards for AI systems and to measure how much AI increases productivity at realistic tasks in those domains.
• Led by the Department of Defense (DOD) in coordination with the Office of the Director of National Intelligence (ODNI), regularly update joint DOD-Intelligence Community (IC) assessments of the comparative level of adoption of AI tools by the United States, its competitors, and its adversaries’ national security establishments, and establish an approach for continuous adaptation of the DOD and IC’s respective AI adoption initiatives based on these AI net assessments.
• Prioritize, collect, and distribute intelligence on foreign frontier AI projects that may have national security implications, via collaboration between the IC, the Department of Energy (DOE), CAISI at DOC, the National Security Council (NSC), and OSTP.
In an action plan full of bullish initiatives, focusing on providing a usable framework for highly regulated or sensitive industries to adopt the technology is easily the biggest unlock. Between reducing regulation and driving cultural change through well-funded initiatives, this opens up a completely different operating landscape for startups and existing companies trying to expand to these customers.
Empower American Workers in the Age of AI
The Trump Administration supports a worker-first AI agenda. By accelerating productivity and creating entirely new industries, AI can help America build an economy that delivers more pathways to economic opportunity for American workers. But it will also transform how work gets done across all industries and occupations, demanding a serious workforce response to help workers navigate that transition. The Trump Administration has already taken significant steps to lead on this front, including the April 2025 Executive Orders 14277 and 14278, “Advancing Artificial Intelligence Education for American Youth” and “Preparing Americans for High-Paying Skilled Trade Jobs of the Future.”. To continue delivering on this vision, the Trump Administration will advance a priority set of actions to expand AI literacy and skills development, continuously evaluate AI’s impact on the labor market, and pilot new innovations to rapidly retrain and help workers thrive in an AI-driven economy.
Recommended Policy Actions
• Led by the Department of Labor (DOL), the Department of Education (ED), NSF, and DOC, prioritize AI skill development as a core objective of relevant education and workforce funding streams. This should include promoting the integration of AI skill development into relevant programs, including career and technical education (CTE), workforce training, apprenticeships, and other federally supported skills initiatives.
• Led by the Department of the Treasury, issue guidance clarifying that many AI literacy and AI skill development programs may qualify as eligible educational assistance under Section 132 of the Internal Revenue Code, given AI’s widespread impact reshaping the tasks and skills required across industries and occupations. In applicable situations, this will enable employers to offer tax-free reimbursement for AI-related training and help scale private-sector investment in AI skill development, preserving jobs for American workers.
• Led by the Bureau of Labor Statistics (BLS) and DOC through the Census Bureau and the Bureau of Economic Analysis (BEA), study AI’s impact on the labor market by using data they already collect on these topics, such as the firm-level AI adoption trends the Census Bureau tracks in its Business Trends and Outlook Survey. These agencies could then provide analysis of AI adoption, job creation, displacement, and wage effects.
• Establish the AI Workforce Research Hub under DOL to lead a sustained Federal effort to evaluate the impact of AI on the labor market and the experience of the American worker, in collaboration with BLS and DOC through the Census Bureau and BEA. The Hub would produce recurring analyses, conduct scenario planning for a range of potential AI impact levels, and generate actionable insights to inform workforce and education policy.
• Led by DOL, leverage available discretionary funding, where appropriate, to fund rapid retraining for individuals impacted by AI related job displacement. Issue clarifying guidance to help states identify eligible dislocated workers in sectors undergoing significant structural change tied to AI adoption, as well as guidance clarifying how state Rapid Response funds can be used to proactively upskill workers at risk of future displacement.
• At DOL and DOC, rapidly pilot new approaches to workforce challenges created by AI, which may include areas such as rapid retraining needs driven by worker displacement and shifting skill requirements for entry-level roles. These pilots should be carried out by states and workforce intermediaries using existing authorities under the Workforce Innovation and Opportunity Act and the Public Works and Economic Development Act, and should be designed to identify surface scalable, performance-driven strategies that help the workforce system adapt to the speed and complexity of AI-driven labor market change.
Rather than just being stuck talking about the impact of AI on the workforce, the action plan is initiating a number of key ways to address this. Between launching education initiatives, better tracking and researching structural changes, and funding to reskill displaced workers, this is a comprehensive attempt at adjusting government policy in a way that could actually benefit the average taxpayer.
Accelerate AI Adoption in Government
With AI tools in use, the Federal government can serve the public with far greater efficiency and effectiveness. Use cases include accelerating slow and often manual internal processes, streamlining public interactions, and many others. Taken together, transformative use of AI can help deliver the highly responsive government the American people expect and deserve.
OMB has already advanced AI adoption in government by reducing onerous rules imposed by the Biden Administration. Now is the time to build on this success.
Recommended Policy Actions
• Formalize the Chief Artificial Intelligence Officer Council (CAIOC) as the primary venue for interagency coordination and collaboration on AI adoption. Through the CAIOC, initiate strategic coordination and collaboration with relevant Federal executive councils, to include: the President’s Management Council, Chief Data Officer Council, Chief Information Officer Council, Interagency Council on Statistical Policy, Chief Human Capital Officer Council, and Federal Privacy Council.
• Create a talent-exchange program designed to allow rapid details of Federal staff to other agencies in need of specialized AI talent (e.g., data scientists and software engineers), with input from the Office of Personnel Management.
• Create an AI procurement toolbox managed by the General Services Administration (GSA), in coordination with OMB, that facilitates uniformity across the Federal enterprise to the greatest extent practicable. This system would allow any Federal agency to easily choose among multiple models in a manner compliant with relevant privacy, data governance, and transparency laws. Agencies should also have ample flexibility to customize models to their own ends, as well as to see a catalog of other agency AI uses (based on OMB’s pre-existing AI Use Case Inventory).
• Implement an Advanced Technology Transfer and Capability Sharing Program with GSA to quickly transfer advanced AI capabilities and use cases between agencies.
• Mandate that all Federal agencies ensure—to the maximum extent practicable—that all employees whose work could benefit from access to frontier language models have access to, and appropriate training for, such tools.
• Convene, under the auspices of OMB, a cohort of agencies with High Impact Service Providers to pilot and increase the use of AI to improve the delivery of services to the public.
Drive Adoption of AI within the Department of Defense
AI has the potential to transform both the warfighting and back-office operations of the DOD. The United States must aggressively adopt AI within its Armed Forces if it is to maintain its global military preeminence while also ensuring, as outlined throughout this Action Plan, that its use of AI is secure and reliable. Because the DOD has unique operational needs within the Federal government, it merits specific policy actions to drive AI adoption.
Recommended Policy Actions
• Identify the talent and skills DOD’s workforce requires to leverage AI at scale. Based on this identification, implement talent development programs to meet AI workforce requirements and drive the effective employment of AI-enabled capabilities.
• Establish an AI & Autonomous Systems Virtual Proving Ground at DOD, beginning with scoping the technical, geographic, security, and resourcing requirements necessary for such a facility.
• Develop a streamlined process within DOD for classifying, evaluating, and optimizing workflows involved in its major operational and enabling functions, aiming to develop a list of priority workflows for automation with AI. When a workflow is successfully automated, DOD should strive to permanently transition that workflow to the AI-based implementation as quickly as practicable.
• Prioritize DOD-led agreements with cloud service providers, operators of computing infrastructure, and other relevant private sector entities to codify priority access to computing resources in the event of a national emergency so that DOD is prepared to fully leverage these technologies during a significant conflict.
• Grow our Senior Military Colleges into hubs of AI research, development, and talent building, teaching core AI skills and literacy to future generations. Foster AI-specific curriculum, including in AI use, development, and infrastructure management, in the Senior Military Colleges throughout majors.
One of the most underreported stories in the last six months is tightly related to the dramatic changes in the IT landscape at the federal level. There has been a very aggressive push to remove overpriced, low-value software vendors and replace them with large-scale contractual vehicles. What that means is that a central contract with optional budget utilization would be signed, and entities within the federal government can benefit from it as they see fit. The plan here pulls the adoption timeline for AI-powered applications to a much shorter time horizon—with significant potential investments to be made already by the end of this year.
Create Streamlined Permitting for Data Centers, Semiconductor Manufacturing Facilities, and Energy Infrastructure while Guaranteeing Security
Like most general-purpose technologies of the past, AI will require new infrastructure—factories to produce chips, data centers to run those chips, and new sources of energy to power it all. America’s environmental permitting system and other regulations make it almost impossible to build this infrastructure in the United States with the speed that is required.
Additionally, this infrastructure must also not be built with any adversarial technology that could undermine U.S. AI dominance. Fortunately, the Trump Administration has made unprecedented progress in reforming this system. Since taking office, President Trump has already reformed National Environmental Policy Act (NEPA) regulations across almost every relevant Federal agency, jumpstarted a permitting technology modernization program, created the National Energy Dominance Council (NEDC), and launched the United States Investment Accelerator.21, 22, 23, 24 Now is the time to build on that momentum.
Recommended Policy Actions
• Establish new Categorical Exclusions under NEPA to cover data center-related actions that normally do not have a significant effect on the environment. Where possible, adopt Categorical Exclusions already established by other agencies so that each relevant agency can proceed with maximum efficiency.
• Expand the use of the FAST-41 process to cover all data center and data center energy projects eligible under the Fixing America’s Surface Transportation Act of 2015.25
• Explore the need for a nationwide Clean Water Act Section 404 permit for data centers, and, if adopted, ensure that this permit does not require a Pre-Construction Notification and covers development sites consistent with the size of a modern AI data center. 26
• Expedite environmental permitting by streamlining or reducing regulations promulgated under the Clean Air Act, the Clean Water Act, the Comprehensive
If there are going to be significant changes to how quickly AI-powered applications are adopted across all sectors of the economy, ensuring the capacity to deliver them becomes critical. There will be significant changes being made to how permits are provided for opening new data centers, which of course means that…
Develop a Grid to Match the Pace of AI Innovation
The U.S. electric grid is one of the largest and most complex machines on Earth. It, too, will need to be upgraded to support data centers and other energy-intensive industries of the future. The power grid is the lifeblood of the modern economy and a cornerstone of national security, but it is facing a confluence of challenges that demand strategic foresight and decisive action. Escalating demand driven by electrification and the technological advancements of AI are increasing pressures on the grid. The United States must develop a comprehensive strategy to enhance and expand the power grid designed not just to weather these challenges, but to ensure the grid’s continued strength and capacity for future growth.
Recommended Policy Actions
• Stabilize the grid of today as much as possible. This initial phase acknowledges the need to safeguard existing assets and ensures an uninterrupted and affordable supply of power. The United States must prevent the premature decommissioning of critical power generation resources and explore innovative ways to harness existing capacity, such as leveraging extant backup power sources to bolster grid reliability during peak demand. A key element of this stabilization is to ensure every corner of the electric grid is in compliance with nationwide standards for resource adequacy and sufficient power generation capacity is consistently available across the country.
• Optimize existing grid resources as much as possible. This involves implementing strategies to enhance the efficiency and performance of the transmission system. The United States must explore solutions like advanced grid management technologies and upgrades to power lines that can increase the amount of electricity transmitted along existing routes. Furthermore, the United States should investigate new and novel ways for large power consumers to manage their power consumption during critical grid periods to enhance reliability and unlock additional power on the system.
• Prioritize the interconnection of reliable, dispatchable power sources as quickly as possible and embrace new energy generation sources at the technological frontier (e.g., enhanced geothermal, nuclear fission, and nuclear fusion). Reform power markets to align financial incentives with the goal of grid stability, ensuring that investment in power generation reflects the system’s needs.
• Create a strategic blueprint for navigating the complex energy landscape of the 21st century. By stabilizing the grid of today, optimizing existing grid resources, and growing the grid for the future, the United States can rise to the challenge of winning the
The key to unlocking the grid challenge is to progress quickly towards nuclear fusion and then deploy it rapidly (nuclear power with significantly less radioactive waste). "Unlocking the 21st century" will not happen without significant amounts of energy generation in a scalable manner. Solving for intelligence through AI but being constrained by energy will not lead to improved outcomes that can be referred to as a "golden age."
I’ll stop here. Do you understand how big this is, tech sales anon?
