According to a recent LinkedIn post from Dakota, the firm is positioning data coverage rather than AI model choice as the core strategic issue for investment managers exploring artificial intelligence. The post highlights comments from founder and CEO Gui Costin, who suggests that limited underlying data can translate into a competitive disadvantage, regardless of the sophistication of the AI layer.
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The post indicates that Dakota seeks to differentiate itself via what it describes as coverage of more than 95% of the global LP, GP, and private company market, characterizing this breadth as “intelligence” rather than a traditional database. For investors, this emphasis points to a potential value proposition in data depth and completeness for private markets participants, particularly asset managers and allocators adopting AI-driven workflows.
The message further implies that firms moving quickly to integrate such data resources into their AI strategies could outpace slower adopters in sourcing, due diligence, and market intelligence. If this positioning resonates with institutional clients in private and alternative investments, it could support Dakota’s client acquisition and retention, strengthening its role as an infrastructure provider in the evolving AI-enabled investment ecosystem.