The Shifting AI Value Chain: Why Software and Services Will Outperform Hardware in the Next Era of AI Growth

The artificial intelligence (AI) landscape is undergoing a seismic shift, with the value chain migrating from hardware-centric innovation to software and services-driven monetization. While semiconductors remain foundational to AI's infrastructure, the sector's growth is increasingly bottlenecked by supply constraints and diminishing returns. Meanwhile, software and services are emerging as the primary engines of value creation, driven by scalable adoption, platform integration, and strategic capital allocation. For investors, this transition signals a critical inflection point: capital should flow toward companies that leverage AI to enhance software ecosystems and services, rather than those reliant on hardware alone. Alphabet Inc. (GOOGL) exemplifies this new paradigm, while chipmakers face mounting headwinds that could erode long-term returns.

The Hardware Bottleneck: Growth, Constraints, and Rising Costs

The semiconductor industry has been a cornerstone of AI's rise, with sector revenue projected to expand by 38% from 2025 to 2026, fueled by hyperscaler investments and AI workload diffusion. However, this growth is increasingly constrained by supply-side challenges. Memory chip shortages, driven by the prioritization of high-bandwidth memory (HBM) for AI servers, are disrupting production for consumer electronics and automotive applications. As reported by Bloomberg, China's Semiconductor Manufacturing International Corp. (SMIC) has warned that these shortages will hit cars and phones in 2026, with memory companies like SK Hynix and Micron redirecting production to high-margin AI-related orders.

Compounding these issues is the underinvestment in memory production during the 2023–2024 downturn, which has delayed capacity expansion. CNBC notes that memory prices have surged by up to 60% year-to-date, with analysts predicting a "robust upward pricing cycle" that will ripple into consumer product costs. Geopolitical tensions further exacerbate vulnerabilities, particularly for advanced AI chip technologies. While hardware remains essential, these constraints highlight the sector's growing fragility and its susceptibility to diminishing returns.

Software and Services: The New AI Value Engine

As hardware bottlenecks emerge, software and services are becoming the primary drivers of AI monetization. According to a report by GlobalX ETFs, AI adoption is moving beyond experimental phases into scalable integration, with leading tech firms embedding AI into search, cloud services, advertising, and workflow automation. Deloitte's 2026 predictions emphasize a shift toward making AI "usable at scale," prioritizing data hygiene, integration, governance, and regulatory compliance over headline-grabbing models. This trend underscores the growing importance of software platforms that enable seamless AI deployment across industries.

Agentic AI-a rapidly evolving subset of AI that employs autonomous agents to automate complex workflows-is poised to redefine enterprise software models. By 2026, these agents could transform SaaS (software-as-a-service) platforms, enabling businesses to optimize operations without significant infrastructure overhauls. This shift aligns with the broader industry move toward software-as-a-service, where recurring revenue and platform stickiness outweigh one-time hardware sales.

Alphabet's Strategic Position: Cloud, Controlled Inventory, and AI-Driven Monetization

Alphabet is uniquely positioned to capitalize on this software-centric AI era. In Q3 2025, the company reported a record $102.4 billion in revenue, with cloud computing revenue surging 35% year-over-year to $15.2 billion, driven by Vertex AI and custom Tensor Processing Units (TPUs). Alphabet's control over its AI chip portfolio-most notably the upcoming seventh-generation TPU Ironwood-provides a cost and performance edge over competitors like Microsoft and OpenAI.

The company's strategic shift toward controlled inventory further strengthens its position. While Google Network advertising revenue declined 1% year-over-year in Q2 2025, driven by AI-powered search features like AI Overviews reducing external traffic, Alphabet has offset this by focusing on owned platforms like YouTube. YouTube advertising revenue reached $10.3 billion in Q3 2025, reflecting the value of controlled inventory where ad placements and content are fully monetized.

Alphabet's capital expenditures, which rose to $91–93 billion in 2025, underscore its commitment to scaling AI infrastructure. A recent deal with Anthropic to supply up to 1 million TPUs highlights its ability to secure AI processing capacity amid industry-wide shortages. These moves position Alphabet to dominate the next decade of AI growth, leveraging its cloud ecosystem and platform dominance to capture long-term value.

The Case for Sector Rotation: From Hardware to Software

For investors, the implications are clear: capital should flow toward software and services players that are integrating AI into scalable platforms, rather than hardware firms facing supply constraints and margin pressures. Chipmakers, while essential, are increasingly exposed to volatile demand cycles and geopolitical risks. In contrast, companies like Alphabet are building moats through AI-driven cloud services, autonomous workflows, and controlled inventory models that generate recurring revenue.

The semiconductor industry's projected 22.43% CAGR from 2025 to 2034 may seem attractive, but this growth is contingent on resolving supply bottlenecks and navigating rising costs. Meanwhile, software and services firms are capturing the lion's share of AI's value creation, with Deloitte noting that 2026 will be defined by "making AI usable at scale." This shift aligns with broader trends in technology, where platform ecosystems and data-driven monetization outperform discrete hardware innovations.

Conclusion: Long-Term Capital Allocation in the AI Era

The AI value chain is undergoing a fundamental realignment, with software and services emerging as the dominant force. Alphabet's strategic investments in cloud infrastructure, controlled inventory, and AI integration exemplify the opportunities in this new era. Conversely, chipmakers face a challenging path, with supply constraints and pricing pressures threatening long-term returns. For investors, the case for sector rotation is compelling: prioritize companies that leverage AI to enhance software ecosystems and services, and avoid overexposure to hardware sectors where growth is increasingly constrained.

As AI adoption accelerates, the winners will be those who master the art of scaling software-driven value, not just manufacturing the tools that enable it.