Trump’s ‘AI Action’ plan: the real opportunity is beyond big tech

Key points

• Trump’s AI Action Plan marks a shift from innovation to industrial deployment focusing on chips, energy, infrastructure, and cloud.

• The biggest opportunities may lie beyond Big Tech, in the physical and digital foundations that enable AI at scale.

• With policy and capital aligning, investors need a playbook to position across the full AI value chain, not just in the front-end models.

President Trump’s AI Action Plan is rapidly taking shape. Last week, the administration moved from broad vision to execution by signing three executive orders on infrastructure acceleration, export promotion, and ideological neutrality. Together, they signal that the U.S. is shifting from AI adoption to industrial-scale deployment.

Here’s what the orders aim to do:

1. Promote AI exports by helping U.S. companies sell full AI packages including chips, cloud, cybersecurity, and software to global markets, especially to compete with China.

2. Accelerate infrastructure buildout by making it easier to construct data centers and power systems, even if it means relaxing some environmental rules.

3. Push for ideological neutrality in government AI tools, a move likely aimed at Trump’s political base, focusing on how AI behaves or is trained.

Taken together, these moves revive a familiar American playbook: reduce red tape, push growth, and let private companies scale fast with the help of government resources. This also reframes how investors might think about AI exposure. The spotlight is moving away from front-end models and toward the foundational layers – chips, compute, power, cloud, and cybersecurity.

What follows is a playbook for positioning across this evolving AI value chain, in a policy-heavy environment where private capital may play a pivotal role alongside government funding.

1. Chipmaking: the brains of artificial intelligence

In this AI gold rush, chips are the shovels. From GPUs and memory to logic and interconnects, semiconductors are the enabling layer beneath every AI breakthrough.

Trump’s export-led strategy promotes full-package AI deployment—including chips, compute infrastructure, and software. This favors players who own both design and manufacturing, while boosting demand for fabrication equipment.

• Key players: NVIDIA, AMD, ARM, Intel, Micron, TSMC.

• Equipment suppliers: ASML, Lam Research, Applied Materials.

Strategically, this layer sits at the intersection of industrial policy, supply chain security, and global trade. That makes it a long-cycle theme with both domestic buildout and foreign demand tailwinds.

2. Networking & connectivity: scaling the backbone

As AI scales, data must move faster and more efficiently. Networking is no longer back-office plumbing, it is the strategic infrastructure enabling low-latency AI performance including training, inference, and real-time deployment.

Once chips are made, the challenge becomes moving data quickly between compute clusters, storage, and users. This infrastructure layer is critical in both training large models and deploying them at scale.

• Key players: Broadcom, Marvell, Cisco, Arista Networks.

This layer doesn’t usually get the spotlight, but it becomes increasingly investable as hyperscalers, private sector buildouts and federal projects demand high-throughput, low-latency networks.

3. Energy & power: feeding the AI boom

Energy is the bottleneck for AI scale. The surge in data center demand is already stressing grids, and AI workloads are only getting more power-hungry.

Trump’s emphasis on energy independence may funnel capital into new-generation utilities and resilient baseload providers.

Two key segments to watch:

• Conventional power: Vistra, Constellation Energy, Talen Energy.

• Nuclear potential: Oklo, GE Vernova, BWX Technologies, NuScale.

Nuclear power, especially through small modular reactors (SMRs), offers a long-duration solution for 24/7 clean energy – something hyperscalers are increasingly evaluating.

4. AI cloud infrastructure: Owning the platform layer

Cloud platforms are the distribution backbone of AI. They host model training, storage, and delivery at scale – effectively becoming the operating systems of the AI economy.

Trump’s export strategy encourages bundling the entire U.S. AI stack, from chips to cloud. Cloud players who control compute platforms, AI services, and data pipelines may benefit from government-backed expansion and overseas promotion.

• Key players: Amazon (AWS), Microsoft (Azure), Google Cloud.
• Infrastructure enablers: Vertiv, DigitalOcean, Nabors Industries (NBIS).

This is also where we could see repackaged CHIPS Act-style funding redirected toward politically favorable outcomes like public-private partnerships for sovereign compute.

5. Software, data, and cybersecurity: The intelligence layer

The front end of AI is where value gets realized. And in Trump’s vision, how AI is built and deployed matters just as much as what it does.

With a push for “ideologically neutral” AI in government procurement, enterprise platforms that offer transparency, auditability, and robust security may gain an edge. But beyond politics, this layer represents the most scalable delivery of real-world AI use cases across government, defense, and business.

• Key enterprise players: Palantir, Oracle, ServiceNow, IBM.

• Cybersecurity and cloud security: CrowdStrike, Palo Alto Networks, Zscaler, Cloudflare.

• Data & analytics: Snowflake, MongoDB.

This layer has recurring revenue potential and sits closest to the user—benefiting from both federal alignment and the growing need for secure, compliant, AI-integrated workflows.

Bringing it all together: Investing across the AI value chain

Trump’s AI plan reflects a classic U.S. industrial growth cycle, fueled by deregulation, public funding, and geopolitical competition. For investors, this shifts the narrative away from just AI use cases to AI capacity. Investors thinking long term may consider the full stack of enablers  including chips, power, networking, software, and security.

Rather than concentrated bets, a layered exposure strategy offers diversification across:

• Capital-intensive buildout (chips, energy, infra).

• Recurring software and services (cloud, enterprise AI, cybersecurity).

• Structural policy tailwinds (manufacturing, clean energy, defense tech).

This is a shift from AI hype to AI infrastructure, and that’s where durable value may lie.

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