Five AI Stocks to Build a Foundational Portfolio From Scratch

As artificial intelligence infrastructure spending accelerates globally, a veteran financial analyst has identified five cornerstone stocks that would form the backbone of an AI-focused portfolio built from ground zero. The selection spans semiconductor suppliers powering data center buildouts, cloud giants monetizing AI workloads, and an emerging neocloud competitor capturing share in the GPU-intensive computing segment.

The recommended portfolio emphasizes exposure across the AI value chain—from the chips enabling AI infrastructure to the platforms delivering AI services to enterprise customers. This diversified approach acknowledges both the massive opportunities in AI infrastructure investment and the nascent but rapidly expanding market for AI-powered cloud services.

Semiconductor Giants and Infrastructure Beneficiaries

The foundation of any AI portfolio must include companies positioned at the critical juncture of hardware and infrastructure deployment. Nvidia ($NVDA) and Broadcom ($AVGO) represent the two most essential semiconductor plays for investors seeking exposure to AI infrastructure buildout.

Nvidia remains the dominant supplier of graphics processing units (GPUs) essential for training and deploying large language models and other AI workloads. The company's H100 and subsequent generation chips have become the de facto standard for data centers racing to expand AI capabilities. With major cloud providers and enterprises competing fiercely for GPU allocation, Nvidia's supply constraints have persisted despite massive capacity investments.

Broadcom provides the networking and infrastructure chips that enable data centers to operate efficiently at scale. The company manufactures custom silicon for cloud providers managing massive AI compute clusters, benefiting from the same infrastructure spending wave that lifts Nvidia. Broadcom's revenue increasingly derives from hyperscale data center customers deploying next-generation AI infrastructure.

Both companies occupy non-negotiable positions in the AI supply chain:

• Nvidia: GPU compute for model training and inference
• Broadcom: Networking infrastructure and custom silicon for data center operations

Cloud Computing Platforms with Usage-Based AI Revenue

Microsoft ($MSFT) and Alphabet ($GOOGL) represent the second pillar of an AI investment strategy, capturing value from enterprise adoption of AI services at scale.

Microsoft has positioned itself as the primary commercialization engine for OpenAI's technology through its Azure cloud platform and Copilot suite of AI-powered productivity tools. The company's enterprise relationships and existing cloud infrastructure provide a natural distribution channel for enterprise AI adoption. Critically, Microsoft's revenue model captures incremental cloud computing usage as enterprises deploy AI workloads—essentially creating a variable cost structure where AI adoption directly drives data center utilization and Azure revenue expansion.

Alphabet operates a similarly positioned platform through Google Cloud and its own powerful large language models. The company's dominant position in search, combined with its AI infrastructure investments, creates opportunities to integrate AI capabilities into existing revenue streams. Like Microsoft, Alphabet benefits from usage-based cloud revenue that scales with enterprise AI adoption.

These cloud giants benefit from several structural advantages:

• Existing enterprise relationships and trust
• Massive installed customer bases evaluating AI capabilities
• Usage-based revenue models that capture AI consumption growth
• Proprietary AI models and intellectual property

The High-Risk, High-Reward Play

Nebius represents the portfolio's asymmetric return opportunity—a GPU-focused neocloud company experiencing rapid growth in the emerging market for alternative AI infrastructure providers.

Nebius operates as a specialized cloud provider optimized specifically for GPU-intensive AI and machine learning workloads. The company targets customers seeking alternatives to hyperscale cloud providers or requiring specialized infrastructure configurations. As AI adoption accelerates and demand for GPU compute exceeds traditional cloud provider capacity, companies like Nebius capture share from customers who cannot obtain sufficient resources from major cloud providers or who benefit from specialized AI infrastructure optimization.

Nebius's appeal lies in its pure-play exposure to GPU-focused cloud infrastructure and its position ahead of potential consolidation in the emerging neocloud market. However, the company carries execution risks, competitive threats from larger cloud providers, and the inherent volatility of high-growth technology stocks.

Market Context and Competitive Landscape

The AI infrastructure market exists at an inflection point. Enterprises and governments are racing to develop proprietary AI capabilities, creating extraordinary demand for compute infrastructure, chips, and cloud services. This competition has created chip shortages, supply chain constraints, and pricing power for companies controlling critical AI infrastructure components.

The competitive landscape includes:

• Semiconductor competitors: AMD ($AMD), Intel ($INTC) competing with Nvidia in GPUs and AI chips
• Cloud infrastructure: Amazon Web Services ($AMZN) competing with Microsoft and Alphabet in cloud services
• Alternative infrastructure providers: Various neocloud and specialized AI infrastructure companies competing with Nebius

However, Nvidia's entrenched position in AI chips, Microsoft's enterprise distribution advantages, and Alphabet's technical capabilities create durable competitive moats. The recommendation to start "from scratch" implicitly prioritizes these structural leaders over emerging competitors or alternative plays.

Regulatory considerations remain relevant, particularly regarding export controls on advanced semiconductors and ongoing antitrust scrutiny of technology giants. These macro factors could impact growth trajectories but appear secondary to the fundamental opportunity in AI infrastructure investment.

Investor Implications and Portfolio Construction

For investors building AI exposure, this portfolio recommendation reflects a bet on the continued acceleration of AI infrastructure spending and enterprise AI adoption over a multi-year horizon.

The portfolio construction balances multiple considerations:

• Semiconductor exposure ($NVDA, $AVGO) captures value from the physical infrastructure buildout and hardware constraints
• Cloud platform exposure ($MSFT, $GOOGL) captures value from software, services, and usage-based monetization of AI capabilities
• Neocloud exposure ($NEBIUS) provides asymmetric return potential with commensurate risk

Investors should consider their risk tolerance, investment horizon, and valuation concerns when evaluating these positions. Nvidia and Microsoft already command significant market valuations reflecting AI opportunity expectations, while Broadcom, Alphabet, and Nebius may offer different risk-return profiles depending on current pricing.

The recommendation implicitly assumes continued strength in AI infrastructure demand and the absence of major regulatory disruptions or technological shifts that could alter competitive dynamics. Changes in these assumptions—such as breakthrough efficiency improvements in AI chips, significant new competitors, or regulatory constraints on data center expansion—could materially impact portfolio returns.

Looking Forward

Building an AI portfolio from scratch requires exposure across the infrastructure value chain, from the semiconductors enabling AI compute to the cloud platforms monetizing AI services. This curated list of five stocks provides that exposure through proven market leaders and an opportunistic bet on emerging infrastructure providers. As AI infrastructure spending continues its acceleration through the coming years, investors positioned across computing hardware, networking infrastructure, and cloud services platform should benefit from multiple expansion vectors across the sector.