In recent years, the investment spotlight has largely been on semiconductor manufacturers and artificial intelligence (AI) infrastructure businesses, which underpin much of the technology powering AI advancements. However, as the AI ecosystem matures, 2026 is shaping up to be a breakthrough year for AI software enterprises. Their value proposition extends beyond hardware, focusing on applications that utilize AI capabilities in innovative ways tailored to specific industries and needs.
This report investigates three notable players in the AI software space that are positioned to capitalize on the transition. These companies—SoundHound AI, Salesforce, and Snowflake—demonstrate robust strategies both in technological development and market engagement, suggesting they could become influential actors in AI’s next growth phase.
1. SoundHound AI: Advancing Voice-Led Agentic AI
Originating as a specialist in AI voice recognition, SoundHound AI has evolved to center its business around voice-driven agentic AI technology. This shift reflects the increasing significance of AI systems that not only process spoken input but also comprehend user intent, a capability critical for conversational AI agents.
Throughout 2025, SoundHound AI experienced rapid revenue growth, more than doubling its income in the first three quarters. This strong performance correlates with enhanced deployment of its AI voice technology across key sectors, notably automotive and restaurant industries. In automobiles, its solutions facilitate sophisticated voice assistants, enriching user interaction in vehicles. For restaurants, its technology streamlines voice-operated ordering systems, enhancing service efficiency.
Additionally, SoundHound bolstered its platform by acquiring Amelia, a company that provides technology foundational to its agentic AI platform. This acquisition also brought customer access in fields such as healthcare, financial services, and retail, indicating a strategic placement across diverse industries.
Financially, SoundHound is on an improving trajectory, with its gross margins increasing and expectations to reach positive EBITDA status in the near term. Its Amelia 7 platform, integrating AI agents for complex task management, is actively being rolled out, positioning the company well for growth in the upcoming years.
2. Salesforce: Leveraging Data Management and Agentic AI Integration
Though sometimes perceived as vulnerable in the AI transition, Salesforce stands out as a key participant due to its expansive role as a system-of-record provider. Its platform serves global enterprises by managing customer service, sales, and marketing data, which constitutes a rich resource as AI applications increasingly depend on clean, structured data to function effectively.
Salesforce strengthened this position through acquiring Informatica, a company specializing in data integration from various sources into unified datasets. This acquisition advances Salesforce’s utility as a reliable source of consolidated enterprise data.
The company is also innovating by embedding agentic AI capabilities into its product portfolio via the Agentforce solution. This technology, integrated across applications like Slack and Tableau, has demonstrated significant adoption. In the previous quarter, Agentforce’s annual recurring revenue surged by 330%, reaching $540 million. Salesforce attributes part of this success to introducing flexible pricing models that accommodate both seat-based and consumption-based options, catering to diverse customer preferences.
From a valuation standpoint, Salesforce’s shares appear reasonably priced. It trades at a forward price-to-sales ratio below 5.5, a forward price-to-earnings ratio near 20, and a price/earnings-to-growth ratio under 0.65. The PEG ratio being less than 1 typically suggests undervaluation relative to earnings growth prospects.
3. Snowflake: Cloud Data Warehousing as an AI Cornerstone
Snowflake operates a prominent cloud-based data warehousing and analytics platform characterized by its architectural separation of storage and computing. This design allows clients to store information in a data lake that can be accessed across various cloud providers, ensuring multi-cloud flexibility. This independence from a single cloud service provider presents customers with agility and enhanced data sharing capabilities in real time.
However, data stored within Snowflake’s system is notably “sticky,” meaning it’s challenging to migrate once consolidated, which benefits platform retention.
Snowflake has also embraced AI agent technology through its Snowflake Intelligence initiative. This tool enables users to develop AI agents capable of securely accessing Snowflake-hosted data. Recently, over 1,200 customers have adopted this solution, driving the company to an AI-generated revenue run rate of $100 million.
Once considered potentially at risk in the AI evolution, Snowflake has demonstrated robust operational performance. Its revenue rose 29% in the last reported quarter, bolstered by strong growth in both new and existing clients. The company achieved a record influx of new customers, and its net revenue retention rate over the preceding 12 months stood at a strong 125%, indicators that underscore its potential as a sustainable AI growth stock well into 2026 and beyond.
Conclusion
The transition from hardware-centric to software-driven AI innovation paves the way for companies adept at integrating AI functionalities into practical applications. SoundHound AI’s voice-focused AI agents, Salesforce’s data orchestration and agentic AI integration, alongside Snowflake’s cloud data services coupled with AI agent development, collectively illustrate the diverse avenues through which AI software firms can flourish.
As 2026 approaches, these companies’ strategic positioning in their respective niches and demonstrated financial momentum warrant attention from investors and industry observers tracking the AI market’s next phase of growth.