We Need To Save Venture Capital From Bad Data

2026-06-30 · Source: Artificial intelligence - Crunchbase News · Field: Finance & Economics — Capital Markets & Investment Management, FinTech & Digital Financial Services · Depth: Intermediate, short

Summary

Henrik Landgren, co-founder and CPTO at Gilion and former VP of analytics at Spotify, argues that venture capital's reliance on founder charisma and packaged data creates information asymmetry, hindering effective investment. He contends that current AI adoption in VC often misguidedly focuses on speeding up existing, flawed processes rather than fundamentally improving data access. Landgren advocates for investors to build robust data infrastructure that enables direct access to granular company data, such as payment records and accounting systems, rather than relying on founder-provided information. This shift would allow investors to uncover hidden faults, accurately assess risk, and gain a competitive edge by reaching conviction faster, particularly for overlooked capital-efficient businesses and future deep tech companies. He emphasizes that better data infrastructure is a precondition for funding the next generation of transformative companies effectively.

Key takeaway

For Directors of AI/ML in venture capital firms evaluating AI strategies, you should prioritize building robust data infrastructure that enables direct access to granular company data. This approach moves beyond merely speeding up existing processes, allowing your team to identify hidden risks and opportunities more accurately. Investing in this foundational data access will enhance competitive deal-making and prepare your firm to evaluate future deep tech companies effectively.

Key insights

Venture capital needs to shift from superficial AI use to direct, granular data access to overcome information asymmetry.

Principles

• AI effectiveness depends on data quality.
• Independent data access reveals true company health.
• Better data infrastructure is a precondition for effective AI.

Method

Investors should plug directly into company financials, payment records, and marketing performance systems instead of relying on founder-packaged data. This allows analysts to start diligence at 70% completion.

In practice

• Access raw company financials directly.
• Prioritize data infrastructure over report automation.

Topics

• Venture Capital
• AI Investment
• Data Infrastructure
• Due Diligence
• Information Asymmetry
• Gilion Platform

Best for: Investor, Director of AI/ML, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence - Crunchbase News.