What is the core problem Landgren identifies with how investors use AI today?

Investors use AI to make reports and summaries faster, but this does the same thing faster without eliminating unnecessary processes or rethinking workflows. The real issue is that investors rely on data cherry-picked and packaged by founders, which obscures how a company actually operates.

How would direct access to company data change investment decisions?

Instead of starting their analysis from zero, analysts could begin at 70% comprehension by plugging directly into a company's financials and operational data. This frees specialist time for tasks requiring human judgment, like understanding the team and assessing founder capability.

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VC needs better data access, not just faster AI tools

Crunchbase News AI20h ago4 min read

Key takeaway

An investment platform co-founder argues that venture capital firms are adopting AI to speed up their existing due-diligence processes, but what they really need is direct access to raw company data instead of founder-provided summaries. Building better data infrastructure would let investors assess risk more accurately and move faster on deals, particularly for companies in emerging categories that traditional metrics fail to capture.

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3 Key Points

What happened
Henrik Landgren, co-founder and CPTO at Gilion (an AI investment intelligence platform), argues in an opinion piece that venture capital investors are using AI to speed up existing processes rather than fundamentally rethinking how they gather and analyze company data.
Why it matters
Investors currently rely on data packaged and cherry-picked by founders themselves, creating an information asymmetry problem. Landgren contends that direct access to raw company data—payment records, marketing performance, accounting systems, and board reports—would let investors spot hidden faults before founders choose to reveal them, shifting how they understand risk and potentially enabling them to fund capital-efficient businesses currently passed over because their data isn't accessed fast enough.
What to watch
Landgren notes that in five years, the companies worth funding will require reassessment of how we evaluate performance, as traditional income models and historical indicators of success will no longer measure up for AI-powered hardware, infrastructure, and new categories of deep tech.

FAQ

What is the core problem Landgren identifies with how investors use AI today?: Investors use AI to make reports and summaries faster, but this does the same thing faster without eliminating unnecessary processes or rethinking workflows. The real issue is that investors rely on data cherry-picked and packaged by founders, which obscures how a company actually operates.
How would direct access to company data change investment decisions?: Instead of starting their analysis from zero, analysts could begin at 70% comprehension by plugging directly into a company's financials and operational data. This frees specialist time for tasks requiring human judgment, like understanding the team and assessing founder capability.

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