Beyond Chips: Why "Second Derivative" AI Software Stocks Could Outpace Semiconductors in 2026

The artificial intelligence investment narrative has been dominated by semiconductor and infrastructure plays for years. But what if 2026 marks a turning point—when the truly transformative gains flow not to chip makers, but to the software companies building on top of them? Here’s why three compelling AI software stocks warrant serious attention.

The Voice-First AI Agent Revolution: SoundHound AI’s Untapped Potential

SoundHound AI (NASDAQ: SOUN) has evolved far beyond its original positioning as a voice technology company. The firm is now architecting what could be a defining layer in the coming wave of AI agents—platforms that can interpret human speech, understand intent, and act autonomously.

This positioning isn’t mere branding. The company has grown explosively in 2025, with revenues more than doubling during the first nine months of the year. More importantly, SoundHound has built real traction in high-value vertical markets. Its voice-controlled ordering systems power restaurant chains, while automotive manufacturers rely on its technology for advanced voice assistants. The strategic acquisition of Amelia wasn’t just a product grab—it came with established customer relationships across healthcare, financial services, and retail.

What makes this particularly compelling is the technical advantage: an AI agent that can’t accurately parse what users are saying is fundamentally limited. By owning the voice layer, SoundHound provides an edge that’s difficult to replicate. The company’s Amelia 7 platform is still in early rollout phases, gross margins are climbing, and management has signaled the approach to positive EBITDA. The trajectory suggests substantial upside potential remains ahead.

The Data Infrastructure Play: Salesforce’s Quiet Strength

Salesforce (NYSE: CRM) spent much of 2024 defending against narratives of AI displacement. Yet the reality is far more nuanced. As enterprises grapple with the fundamental challenge of feeding AI systems—getting clean, organized, trustworthy data—Salesforce’s core positioning becomes harder to attack.

Consider what the company controls: it operates the system of record for customer interactions, marketing operations, and front-office sales processes for countless global enterprises. When the question shifts from “Will AI replace CRM software?” to “Where do I source reliable data for my AI models?”, Salesforce sits in a commanding position.

The Informatica acquisition crystallized this strategy. By absorbing a best-in-class data integration platform, Salesforce constructed a moat around data governance and preparation—exactly what enterprises need as they scale AI deployments. The company’s Agentforce product, now woven throughout Slack and Tableau, has generated remarkable early momentum. Last quarter, Agentforce achieved an annual recurring revenue run rate of $540 million, representing 330% year-over-year growth.

The valuation floor suggests further upside: a forward price-to-sales multiple below 5.5x, forward P/E near 20x, and a PEG ratio under 0.65—a metric typically signaling undervaluation when below 1.0. A flexible pricing model (mixing seat-based and consumption approaches) has accelerated adoption, indicating the product captures genuine customer demand rather than forced migration.

The Data Warehouse Transformation: Snowflake’s AI Intelligence Layer

Snowflake (NYSE: SNOW) operates what amounts to Switzerland in the cloud computing wars—a data warehouse and analytics platform architected to remain neutral across cloud providers. Its separation of storage and compute means customers avoid vendor lock-in while gaining real-time data sharing capabilities. Once data resides within Snowflake, the switching costs become prohibitively high, creating genuine stickiness.

The company’s latest catalyst is Snowflake Intelligence, which allows customers to construct proprietary AI agents that securely access warehouse data. The early adoption metrics are striking: over 1,200 customers have deployed this capability, and the company has reached a $100 million annualized revenue run rate in its AI product suite.

The overall business momentum is undeniable. Last quarter delivered 29% revenue growth alongside record customer additions. The 125% net revenue retention rate measured over the past 12 months signals powerful expansion within the existing installed base—a hallmark of category leaders.

Once dismissed as potentially vulnerable to AI disruption, Snowflake has instead positioned itself as a critical infrastructure layer for how enterprises implement AI at scale.

The Convergence Point: Why Second Derivative AI Stocks Matter Now

These three companies share a crucial characteristic: they’re not directly competing with AI hardware makers. Instead, they’re enabling the next phase of AI adoption by solving the practical, operational challenges that determine whether AI agents and systems actually generate value in the real world. They represent the “second derivative” of AI—the software layer that transforms raw computational power into business outcomes.

Investors watching semiconductor stocks for the past four years have captured tremendous value. But the inflection from infrastructure-focused to application-focused AI investing could create a new generation of outperformers.