Almost every investor carries AI exposures within their equity portfolios to some degree. As the AI industry continues to evolve, it’s worth thoughtful, modern investing solutions according to KraneShares in a recent webcast. Hosted by Kirsten Chang, Senior Industry Analyst at VettaFi, the webcast discussed AI ecosystem developments, opportunities, and more.
Many investors also gain AI exposure through targeted funds, but it’s worth noting that many of those funds launched before AI capabilities began to ramp up in 2022. “There’s not really a solution capturing the true AI potential,” according to Derek Yan, CFA, Senior Investment Strategist at KraneShares.
The KraneShares Artificial Intelligence & Technology ETF (AGIX) seeks to help fill that void by offering high conviction, concentrated exposure to AI companies. The fund tracks the Solactive Etna Artificial General Intelligence Index that holds both public and private AI companies.
Solomon Bier, Partner & Portfolio Manager at Etna Capital Management, discussed the evolution of the three dominant technology cycles in the last 60 years. These include the mainframe cycle, pc/server cycle, cloud/mobile cycle, and now AI. “Each trend is bigger than the prior trend,” Bier noted. “We see this [AI] wave continuing for a decade — at least 15 years, the same as cloud and mobile.”
It creates a broad expanse of opportunity when looking across the AI ecosystem. Specifically, Etna believes a number of AI beneficiaries exist beyond the traditional Magnificent 7 companies. These include semiconductors, datacenters, cloud companies, edge AI, large language models, and AI applications.
Image source: KraneShares
“We think investors should take a more holistic and systematic approach when you… think about a long-term investment into the AI basket,” Yan said.
AGIX invests in three fundamental pillars of the AI ecosystem: infrastructure, hardware, and applications. The index begins with a starting universe of approximately 3,000 companies and filters for characteristics such as liquidity and market cap. It then screens for companies that fall within 12 AI-related industries.
Each security then receives an AI exposure score, a proprietary formula that considers “AI readiness” as well as “AI relevance”. Highest scoring companies make it into the Index, and are further weighted by their AI exposure score as well as by market cap. No single pillar makes up more than 40% of the total weight of the underlying index. The strategy is a high conviction one, with between 40-50 securities at any given time.
AGIX carries an expense ratio of 1.00%.
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