Positioning for the Next Bull Market: Why These AI Semiconductor Leaders Still Offer Value

The stock market started 2026 with considerable strength, building on the momentum generated throughout 2024 and 2025. AI-related equities have been primary drivers of this rally, as organizations across sectors accelerate their investment in artificial intelligence infrastructure and move toward enterprise-scale deployments. According to research from Grand View Research, the global artificial intelligence market is anticipated to expand from $390.9 billion in 2025 to approximately $3.5 trillion by 2033, underscoring that the next bull market in AI could have substantial runway ahead. This expanding opportunity suggests that despite recent gains, select semiconductor and memory companies remain attractively valued relative to their long-term expansion prospects.

The Shifting AI Infrastructure Landscape and Investment Opportunity

The transition toward enterprise AI is fundamentally different from previous technology cycles. Rather than inventory-driven swings characteristic of past semiconductor booms, the current expansion is anchored by sustained multi-year capital expenditures in AI infrastructure. Hyperscaler companies—the massive cloud and AI service providers reshaping the digital landscape—are projected by Goldman Sachs to allocate nearly $527 billion toward AI-related capital investments throughout 2026. This structural shift creates a durable demand environment for memory and processing power, distinguishing today’s opportunity from cyclical chip rallies of the past.

Within this context, two semiconductor-focused companies stand out as potential next bull market leaders: firms with established market positions, strong cash generation, and exposure to multiple AI growth vectors. These businesses benefit from secular tailwinds while trading at valuations that don’t fully reflect their long-term potential.

Qualcomm: Diversified AI Leadership Across Multiple Growth Vectors

Qualcomm has evolved beyond its traditional identity as a mobile chip designer, establishing itself as a multifaceted player in the artificial intelligence semiconductor space. In fiscal 2025 (ending September 28, 2025), the company generated non-GAAP revenue of $44 billion and produced free cash flow totaling $12.8 billion while maintaining solid operational margins. This financial strength provides ample capacity for strategic investments across emerging AI markets.

The company’s positioning in AI-powered personal computers represents a near-term catalyst. Qualcomm intends to drive approximately 150 Snapdragon-powered AI PC designs to commercialization through 2026, leveraging its complete computing platform approach. The recent launch of the Snapdragon X2 Plus processor family expands AI capabilities to price-sensitive segments, facilitating the transition of AI PCs from early-adopter niches to mainstream volume markets.

Beyond consumer devices, automotive represents an underdeveloped but significant revenue opportunity. The automotive division contributed over $1 billion in revenue during the fourth quarter alone, with substantial upside as vehicles increasingly incorporate artificial intelligence capabilities. Additionally, Qualcomm has expanded into AI data center infrastructure, announcing plans for a 200-megawatt capacity deployment in 2026.

Trading near 12.8 times forward earnings, Qualcomm appears reasonably priced for an enterprise with such diversified AI exposure and multi-year growth catalysts.

Micron Technology: Memory Chip Dominance in the AI Era

Micron Technology entered 2026 with a compelling financial trajectory underpinned by robust demand for AI-oriented memory solutions. The company delivered 56% year-over-year revenue expansion to $13.6 billion in its first fiscal quarter (ending November 27, 2025), a pace exceeding historical norms and reflecting intense AI-driven purchasing patterns.

The supply-demand dynamics favor Micron substantially. Demand for its DRAM, NAND, and high-bandwidth memory (HBM) product families significantly exceeds current manufacturing capacity, granting the company enhanced pricing leverage and the ability to expand profitability margins. Management has stated that 2026 HBM production is fully contractually allocated, with volumes and pricing terms already locked in with major customers. This forward revenue visibility—a rarity in semiconductor cycles—provides earnings certainty and reduces execution risk.

Each successive generation of AI processors demands incrementally greater performance memory to execute complex machine learning workloads, including specialized HBM and high-capacity storage systems. This technical imperative creates a structural floor under Micron’s demand prospects throughout the coming years.

The company is also demonstrating capital discipline. Micron reported nearly 30% free cash flow margins and reduced total debt by $2.7 billion within a single quarter, strengthening its balance sheet while maintaining growth investments. The stock currently trades at 8.6 times forward earnings, a modest multiple for a company commanding industry-leading market share in mission-critical memory categories during a secular AI buildout.

Building a Next Bull Market Portfolio: Investment Considerations

Both companies share fundamental characteristics that position them as potential next bull market winners: contractual revenue visibility from multi-year AI infrastructure investments, technological moats that competitors struggle to replicate, and valuations that appear reasonable relative to forward earnings and market opportunity.

Micron’s combination of supply constraints, pricing power, contractual demand certainty, and disciplined capital allocation creates a compelling risk-reward profile. Qualcomm’s diversification across AI PCs, automotive, and data center infrastructure reduces single-market dependency while expanding addressable opportunities.

For investors evaluating exposure to the artificial intelligence theme, these semiconductor leaders merit serious consideration. The next bull market phase of AI adoption is still in early innings, and companies positioned at critical infrastructure layers—where every new AI implementation drives incremental demand—appear well-situated to capture disproportionate value creation over the coming years.