In a remarkable sign of the growing importance of artificial intelligence in the tech industry, AI companies worldwide raised a staggering $100 billion in venture capital in 2024, according to Crunchbase data. This represents an 80% increase compared to 2023, with AI investments now accounting for nearly a third of total venture capital dollars invested last year.

The AI industry has experienced explosive growth over the past two years, leading to a crowded landscape filled with overlapping companies, startups relying on AI for marketing purposes only, and genuine innovators working on groundbreaking AI solutions. As a result, investors face a daunting task in identifying the startups with the potential to become category leaders.

To better understand what sets successful AI startups apart, TechCrunch surveyed 20 venture capitalists who back startups building for enterprises. The survey revealed that more than half of the respondents believe that proprietary data is the key differentiator for AI startups, giving them a competitive edge in the market.

Paul Drews, a managing partner at Salesforce Ventures, emphasized the importance of differentiated data, technical research innovation, and a compelling user experience in creating a moat for AI startups. Jason Mendel, a venture investor at Battery Ventures, concurred, stating that access to unique, proprietary data enables companies to deliver better products than their competitors, while a sticky workflow or user experience allows them to become core systems of engagement and intelligence.

Having proprietary data becomes increasingly crucial for companies building vertical solutions, according to Scott Beechuk, a partner at Norwest Venture Partners. Andrew Ferguson, a vice president at Databricks Ventures, added that rich customer data and data that creates a feedback loop in an AI system can make a significant difference in a startup's effectiveness.

Valeria Kogan, the CEO of Fermata, a startup utilizing computer vision to detect pests and diseases on crops, attributed her company's success to its model being trained on both customer data and data from its own research and development center. The fact that Fermata performs all its data labeling in-house also contributes to the accuracy of its model.

Jonathan Lehr, a co-founder and general partner at Work-Bench, highlighted the importance of not only having access to data but also being able to clean and utilize it effectively. He emphasized that his fund focuses on vertical AI opportunities that require deep domain expertise and where AI is mainly an enabler of acquiring previously inaccessible data and cleaning it in a way that would have taken hundreds or thousands of man-hours.

Beyond proprietary data, venture capitalists also look for AI teams led by strong talent, existing strong integrations with other tech, and companies that have a deep understanding of customer workflows. As the AI industry continues to evolve, these differentiators will play a critical role in separating the winners from the losers.

The record-breaking investment in AI companies in 2024 underscores the growing recognition of AI's transformative potential across industries. As investors and entrepreneurs navigate this rapidly changing landscape, identifying and supporting the most promising AI startups will be crucial to unlocking the full potential of this technology.