Hong Kong, China - February 26, 2026 - Etna Capital Management today released a new research framework, “Beyond Benchmarks: A Research-Led Framework for Evaluating AI Companies (2026 Edition),” outlining why research-led AI investing is becoming essential as automation accelerates globally and technical change compresses go-to-market cycles for early-stage AI companies.
As artificial intelligence moves from model breakthroughs into real-world deployment, venture investors are beginning to rethink how early-stage AI companies should be evaluated. According to Haina Xu, a global AI investor and Principal Investor at Etna Capital Management, who leads the firm’s U.S. brand and market expansion initiative, traditional performance benchmarks are quickly losing their usefulness as standalone signals of long-term success.
“Performance benchmarks are table stakes now,” Xu said. “What ultimately matters is whether intelligence can be integrated into real workflows, sustained at scale, and operated under real-world constraints.”
Xu recently introduced a research framework titled “Beyond Benchmarks: A Research-Led Framework for Evaluating AI Companies (2026 Edition),” which outlines how investors are shifting from model-centric analysis toward system-level execution. The framework reflects a broader structural change across the AI ecosystem, where rapid technical iteration has compressed go-to-market cycles and made operational reliability a key differentiator.
Rather than focusing solely on model accuracy or leaderboard performance, the framework emphasizes agent behavior, workflow integration, reliability under production conditions, and execution risk across global markets. Xu’s research draws on her evaluation of frontier AI sectors including voice agents, vertical AI applications, and AI services infrastructure.
Industry operators say the shift reflects how AI products are increasingly judged in practice. “It moves the conversation beyond demos and benchmarks and toward whether AI systems can actually operate reliably within real workflows,” said Jason Hu, Founder and CEO of Nexad, an AI startup backed by a16z Speedrun. “That perspective has been important for how we think about product direction and go-to-market execution.”
As automation accelerates and investors search for durable signals beyond early hype cycles, research-driven evaluation frameworks are becoming more central to capital allocation decisions. Xu believes this evolution marks a turning point in AI investing — one where technical capability alone is no longer enough, and long-term execution becomes the defining metric.
Etna Capital Management plans to host a global virtual briefing featuring Xu alongside operators and investors to discuss the framework’s implications for early-stage AI companies and the future of research-led investing.
About Etna Capital Management
Etna Capital Management is an AI-focused investment firm supporting early-stage companies across frontier AI categories, including voice agents, vertical AI, and AI services. Etna’s approach emphasizes rigorous research, system-level evaluation, and long-term execution assessment. Additional information about Etna Investment Group can be found at https://etnalabs.co/.
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