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When it comes to funding, AI has the capacity to handle nearly any task, enabling a venture capital firm to potentially operate with just 1 to 2 employees and still achieve substantial financial gains through investments.
Nonetheless, this is merely the beginning. According to a recent report by Earlybird enthusiast Andre Retterath, only 1% of VC funds presently engage in data-driven activities internally. These pioneering companies are paving the way, with numerous other venture capital firms expected to swiftly embrace AI in a similar fashion.
Leveraging AI for Startup Evaluation and Screening
The advent of advanced AI models and technologies, particularly since the introduction of ChatGPT, has simplified and reduced the cost of maintaining a robust deal flow for investors. Previously, a significant workforce was required to monitor thousands or even millions of businesses using data analysis, artificial intelligence, and machine learning.
As per a study by angel investor Bartosz Trocha, approximately 100 venture capital funds have already integrated AI tools into their operations, including prominent names like SignalFire, Episode 1, InReach Ventures, and EQT Ventures. Moreover, many VCs opt to develop their own tools due to the absence of a one-size-fits-all AI solution capable of addressing the multifaceted challenges faced by investment teams.
The procurement and due diligence phases of the investment process are critical. AI can expedite and streamline these traditionally laborious tasks within minutes.
AI has the capacity to sift through extensive datasets encompassing media coverage, social media insights, and pitch decks to identify promising startups aligning with a VC’s investment criteria. Post-selection, AI swiftly assesses a company’s financial statements, business models, and industry landscape.
InReach Ventures, a London-based venture capital firm that has leveraged AI for scouting opportunities since its establishment in 2015, developed the DIG software to streamline deal sourcing and due diligence processes. This tool aids the firm in identifying, analyzing, and evaluating hundreds of European startups on a monthly basis.
By harnessing conceptual AI models, the software compiles and evaluates startup information to determine their compatibility with the VC’s portfolio.
Moreover, this tool is integrated with InReach Ventures’ website, preventing the inundation of irrelevant pitches by efficiently organizing incoming applications.
The scalability of such platforms is significantly enhanced due to the flexible nature of this technology. For instance, EQT Ventures introduced the Motherbrain software for data scraping and machine learning, capable of processing information from two million companies daily.
Possessing such a tool is indispensable for VC firms as it enables them to unearth hidden gems ahead of the curve. InReach Ventures, for instance, utilized its platform to discover the Lithuanian startup Oberlo before other firms, leading to a lucrative investment. At the time, Oberlo was not actively seeking funding and was later acquired by Shopify for $15 million.
Related: 10 Essential AI Tools for Business Enhancement
AI for Startup Categorization
Post-investment, categorizing startups can be a time-intensive endeavor for investors. Manually categorizing 400 to 500 company profiles can be arduous. Conceptual AI models expedite this process by categorizing startups based on various parameters such as stage, industry, size, business model, etc., saving substantial time.
Episode 1’s data platform aggregates and organizes information on approximately 400 companies weekly for potential investments, drawing insights from diverse sources. Their “Iot” partner allows for the generation of customized lists of businesses aligning with the team’s current focus, be it B2B or startups.
AI for Monitoring High-Potential Ventures
Adhering to the “power law” principle in venture capital, overlooking a promising investment can be costly. SignalFire has developed software that flags rapidly expanding or high-performing startups on a dashboard for tracking purposes. This system scours data from sales records to academic publications and financial reports, monitoring eight million startups globally.
AI for Promoting Diversity
Despite advancements, the venture capital landscape remains predominantly male-dominated. In 2022, only 2% of total VC funding in the United States originated from startups with sole female founders, with a mere 16.1% of industry decision-makers being female, as per PitchBook. The scenario for other underrepresented groups is equally challenging.
To foster a more inclusive investment approach, several venture capital firms are leveraging AI. For instance, EFT Ventures is actively “amplifying underrepresented groups” by incorporating new functionalities into its Motherbrain application.
AI holds the promise of enabling VCs to make objective, less biased investment decisions by reducing reliance on referrals and warm introductions. By 2025, Gartner predicts that AI and data analytics will inform over 75% of VC investment decisions.
Cost-Effective AI Solutions
While developing and maintaining proprietary technology can be costly, with SignalFire reportedly investing around $10 million annually in its application, some VC firms are doubling down on AI and machine learning tools to stay competitive in the industry.
For investors not prepared to build custom data analysis platforms, a blend of off-the-shelf AI tools such as ChatGPT, Google Bard for market analysis, Tactiq for call transcriptions, Vimcal for scheduling meetings, and Superhuman for email management is a viable option.
