How AI is rewriting the playbook for investing

"Founders' takes is a new series featuring expert insights from tech leaders transforming industries with artificial intelligence. In this edition, Cem Ötkün, CEO and co-founder of startup scouting platform Bounce Watch, shares his views on how AI is reshaping investing. Venture capital, once built on networks and narratives, is now undergoing a structural shift. AI is no longer a futuristic add-on to the investment process - it's becoming an operating system. And for those investing in the opaque world of private markets, it's not optional."

"Despite all the capital flowing through venture, much of the machinery remains outdated. Deal flow still relies heavily on intros. Screening is inconsistent. Diligence is time-consuming and subjective. Too often, the loudest signals win - not the most promising ones. This inefficiency creates three core risks: Missed opportunities, especially in under-networked geographies. Biased capital allocation, driven by pattern-matching rather than real traction. Time dilution, with analysts spending more time gathering data than interpreting it."

"The modern investment team increasingly resembles a hybrid between a research lab and a software company. Instead of asking "Who do we know?", the question is "What signals are emerging that others haven't seen yet?" AI enables this shift in several ways: Data orchestration: Tools now unify disparate sources - talent movement, product launches, market activity - into coherent, queryable insight. Micro-pattern detection: Models surface weak signals that precede big movements."

Venture capital historically depended on networks, intros, and narrative-driven screening, leaving deal flow inconsistent and diligence slow and subjective. These dynamics lead to missed opportunities in under-networked regions, biased capital allocation based on pattern-matching, and analysts spending excessive time gathering rather than interpreting data. AI is becoming the operating system for investment teams by unifying disparate data sources, surfacing micro-patterns that signal upcoming shifts, and compressing research workflows from memo drafting to competitor mapping. Investment teams are evolving into hybrids of research labs and software firms, making AI adoption existential for effective private-market investing.

Read at TNW | Ecosystems