Founders’ takes: How AI is rewriting the playbook for investing
Summary
Cem Ötkün of Bounce Watch argues that AI is shifting venture capital from a network-and-narrative business to a data-driven operating system. Traditional deal flow — reliant on intros, noisy signals and slow diligence — is being upended by tools that unify data, detect micro-patterns and accelerate workflows. Firms are using fine-tuned LLMs, vector databases and embeddings to query documents and surface weak signals, while agents and copilots begin to automate sourcing, memos and prioritisation.
The result is a change in how conviction is formed: less about meeting volume, more about velocity and quality of insight. Europe, with fragmented ecosystems, stands to gain as models surface hidden opportunities. But AI is not infallible — poor data or badly tuned systems can amplify bias — so the winning approach is machine-assisted humans with robust internal logic and creative questioning.
Author
Punchy: This is essential reading for anyone in venture or startup scouting. The piece makes a clear, urgent case that AI is now infrastructure for investing — not an optional add-on — and that firms who orchestrate the right tools will redefine what being an investor means.
Source
Source: https://thenextweb.com/news/founders-takes-on-ai-for-investing
Key Points
- Venture remains inefficient: deal flow depends on intros, screening is uneven and diligence is slow and subjective.
- AI rewires the investment stack via data orchestration, micro-pattern detection and process acceleration.
- Practical tools include fine-tuned LLMs, vector databases and embeddings to query PDFs, CRM logs and memos semantically.
- Real-time monitoring of hiring, product launches and activity enables proactive sourcing and better portfolio foresight.
- Agents and AI copilots are evolving from assistance to autonomous actions like prioritising leads and drafting memos.
- Risks remain: noisy systems can magnify bias; human oversight and quality data are critical.
- Leading firms focus on integrating and orchestrating best-of-breed tools rather than building everything in-house.
Why should I read this?
Short version: if you invest, advise or scout startups, this explains the concrete ways AI will change how you find and judge opportunities. It’s not techno-optimism — it maps practical toolsets (LLMs, vectors, agents) to everyday tasks like sourcing and diligence. Read it because it saves you the time of parsing the hype and shows what winners are already doing. In plain terms: get familiar with these changes now, or you’ll be playing catch-up.