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AI-native vendors close record enterprise deals as legacy software loses ground

Purpose-built AI platforms are winning enterprise contracts over traditional software providers, driven by integrated capabilities legacy systems can't match. SoundHound AI reported record customer deals in Q4 2025, while Baidu's AI cloud revenue hit CNY 30 billion. The shift reflects enterprises prioritizing native AI infrastructure over retrofitted solutions.

AI-native vendors close record enterprise deals as legacy software loses ground
Image generated by AI for illustrative purposes. Not actual footage or photography from the reported events.
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AI-native vendors closed a record number of enterprise deals in late 2025, capturing market share from traditional software providers struggling to retrofit AI capabilities into legacy systems.

SoundHound AI CEO Keyvan Mohajer reported record customer deals in Q4 2025, with all key profit metrics rising. "As traditional software faces massive AI disruption, businesses are looking to partner with AI natives," Mohajer said.

Baidu's AI cloud business—combining infrastructure and applications—reached CNY 30 billion ($4.1 billion) in revenue, demonstrating enterprise appetite for integrated AI platforms. The company's bundled approach contrasts with traditional cloud vendors adding AI as separate services.

Rezolve AI noted most legacy digital experience platforms lack native AI, conversational interfaces, or transaction-capable agents. The company positioned itself among the few combining proprietary LLMs with deep platform integration—a capability enterprises now prioritize in vendor selection.

The vendor consolidation stems from enterprises avoiding technical debt. Legacy systems require expensive middleware to connect AI features, creating performance bottlenecks and security gaps. Purpose-built platforms eliminate these layers.

Three factors drive the shift. First, AI-native vendors design data pipelines, model serving, and application layers as unified systems rather than bolted-on modules. Second, they optimize hardware and software together, improving inference speed and cost efficiency. Third, their development cycles move faster than enterprise IT departments can upgrade legacy stacks.

Traditional software vendors face a catch-22: rushing AI features risks quality, but slow rollouts lose customers to AI-first competitors. Many enterprises now specify "native AI architecture" in RFPs, effectively disqualifying retrofitted solutions.

The procurement shift appears across industries. Financial services, healthcare, and manufacturing buyers increasingly favor vendors who built AI capabilities from inception rather than acquisition. This preference shows in contract values—AI-native platforms command premium pricing while legacy vendors discount to retain accounts.

Analyst estimates suggest AI-native vendors captured 40-45% of new enterprise AI platform deals in H2 2025, up from 25% a year earlier. If the trend continues, traditional software companies may need acquisitions or complete platform rebuilds to remain competitive in AI-dependent enterprise workflows.