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A new benchmark for AI investment: Swift Ventures unveils system to separate talk from action

Credit: VentureBeat made with Midjourney
Credit: VentureBeat made with Midjourney

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Swift Ventures has unveiled a new artificial intelligence company index today, creating the first systematic scoring system to identify public companies making genuine investments in AI technology rather than just talking about it in earnings calls.

The venture capital firm developed the index by fine-tuning large language models to analyze thousands of earnings transcripts, hiring data, and research contributions. The analysis revealed that while companies mentioned AI over 16,000 times in last quarter’s earnings calls, only a small fraction are making substantial investments in the technology.

“Everyone sees that the world’s changing — AI is changing the world, but most people, they just don’t have a way to partake in the upside,” said Brett Wilson, cofounder of Swift Ventures, in an exclusive interview with VentureBeat. “They can’t invest in private companies like I do as a VC, and it’s just not easy to find true AI companies beyond just buying Nvidia or the Magnificent Seven.”

How top AI companies are crushing market returns: New performance data

The index currently tracks approximately 90 companies and uses three primary metrics: investment in AI research and open-source contributions, AI talent density, and revenue derived from AI operations.

Companies that meet the criteria for inclusion in the index have demonstrated remarkable market performance, with the index showing 37% annual growth over the past three years, substantially outperforming both the Nasdaq’s 12% and the S&P’s 19% growth during the same period.

Perhaps most striking is the correlation between research investment and profitability. Wilson noted, “When we looked at companies that are regularly contributing to AI research and open-source models, you see it reflected in their profitability. Those companies have an average gross profit of something like double regular tech companies that don’t — 55% versus 25%.”

The AI talent crisis: Why only 1% of public companies are winning the hiring race

The index reveals a stark talent gap in public markets. According to Swift’s analysis, only about 200 public companies maintain more than 1% of their workforce in AI-specific roles, despite widespread claims about AI adoption. This metric has become increasingly important as the U.S. Bureau of Labor Statistics projects unprecedented demand for AI engineers.

“You can’t just talk about AI and be an AI company,” Wilson emphasized. “It’s about making investments in AI talent and infrastructure and research and contributing to the community.”

Inside Swift Ventures’ game-changing plan to transform AI investment

The index has identified several under-the-radar companies making significant AI investments, including Doximity, which develops AI-powered medical writing applications, and Leidos, which focuses on defense-oriented autonomous systems. These companies are “growing over 50% per year,” according to Wilson, suggesting a broader AI transformation beyond well-known tech leaders.

Swift Ventures plans to make the index available for free with quarterly updates and is considering launching an ETF in early 2025 if investor interest materializes. The firm’s approach represents a significant shift from existing AI investment vehicles, focusing on programmatic scoring rather than individual stock picking.

“We don’t want to look like something like a Kathy Wood‘s vehicle, where someone’s cherry-picking certain stocks,” Wilson explained. “Our intention was to use kind of a programmatic criteria to pick companies, and have the system do it.”

The index launch comes at a critical moment for AI investment, as public market investors struggle to differentiate between companies making meaningful AI investments and those simply adopting AI terminology. It also arrives as private AI companies like Databricks, Scale AI and Anthropic prepare for potential public offerings in the coming years, suggesting the AI company landscape could shift dramatically.

This new methodology has the potential to become a standard benchmark for evaluating AI investments, potentially influencing how companies allocate resources to AI development and how investors measure AI capabilities in public markets.

For corporate leaders, the index provides clear metrics for what constitutes genuine AI investment. As Wilson noted, “Real AI investment means that you have a preponderance of AI people, that you’re investing in AI research, contributing it to the community, and that your revenue is fundamentally affected by those AI investments.”