“AI has impacted all walks of life, and investing is no exception. We see AI transforming all elements of the investment process,” declared Rotem Shacham, Director at PSG Equity. This statement encapsulates the profound shift occurring within venture capital firms, as artificial intelligence moves beyond a mere buzzword to become an indispensable tool deeply integrated into the day-to-day work of partners and team members.
The recent VC AI Survey by CTech – held in recent weeks among dozens of senior managers at Israeli venture capital funds – has turned the spotlight to this transformation, revealing how Israeli investment funds are leveraging AI to revolutionize their operations, from initial deal sourcing to intricate portfolio management.
2 View gallery
Nadav Shimoni (from left), Rotem Shacham, and Yonatan Sela.
(Credit: Eric Sultan, Omer Hacohen)
The consensus among the surveyed funds highlights a significant operational impact over the past year. On a scale of 1 to 10, the majority rated AI’s influence on their daily work at 7 or higher, with several funds like PSG Equity, TPY Capital, Flashpoint Venture Growth, and J-Ventures assigning scores of 9 or 10, indicating a near-complete operational overhaul. Even funds with slightly lower scores, like iAngels at 6 and Q Fund at 6, acknowledged substantial efficiency gains. This widespread adoption reflects AI’s capacity to streamline processes, enhance decision-making, and boost overall productivity.
Deal Sourcing and Pipeline Management
One of the most frequently cited areas of impact is in deal sourcing and the management of investment pipelines. AI tools are acting as “force multipliers,” enabling funds to sift through an unprecedented volume of potential opportunities and identify promising startups more efficiently than ever before.
Flashpoint Venture Growth, for instance, has extensively used AI for its deal flow, developing an automated sourcing machine that tracks and qualifies startups meeting their investment criteria. This system analyzes multiple data points, including employee numbers, sectoral information, and founder locations, to prioritize engagement with specific teams. Guy Yamen, Managing Partner at TPY Capital, noted that their custom AI agents have significantly scaled sourcing, with automated scouts surfacing “3-4× more qualified leads each week – growing the top of the funnel without increasing headcount”. This newfound capacity allows funds to expand their reach while maintaining lean operational structures, a crucial advantage in the competitive VC landscape.
Similarly, J-Ventures has built, and continues to develop, an internal AI-based platform designed to improve sourcing and screening. This platform, shared with another fund, has proven “much more effective in finding promising founders” and has helped them actively source deals more efficiently. Israeli Mapped in NY Ventures also uses AI-driven tools to enhance deal sourcing and map the Israeli tech ecosystem, identifying new companies and tracking growth.
Beyond sourcing, AI is dramatically streamlining and accelerating the due diligence phase, a process traditionally known for its lengthy, intuition-driven nature. Funds are leveraging AI to automate large portions of their due diligence checklists, enhancing both speed and depth of analysis.
Data Synthesis and Analysis: Key1 Capital, a growth-stage fund, reports that AI has a “tangible impact” on speeding up diligence and deepening its quality by enabling them to “synthesize vast amounts of data into faster, sharper decision-making,” as Sarel Eldor, Co-Founder & Managing Partner at Key1 Capital noted. IL Ventures echoes this, stating that AI tools help them “crunch a lot of data quickly and get bottom lines” in tasks ranging from screening to market intelligence.
Background Research and Competitive Analysis: Notable Capital utilizes AI to provide “quick yet in-depth background information” on companies and markets, helping them prepare for meetings and map out competitive landscapes. J-Ventures also uses generative AI to produce “high-quality research on companies and sectors,” identify competitive dynamics, and benchmark technical capabilities.
Technical Evaluations: Horizon Capital specifically leverages AI-driven tools for “early-stage technical evaluations,” while Israeli Mapped in NY Ventures employs them to “evaluate technical depth” in startups.
Financial Analysis: PSG Equity, has seen “productivity gains from AI” in financial analyses, and NightDragon’s Dorin Baniel regularly uses ChatGPT for performing “financial analysis” and running “quick calculations”.
Catalyst Private Equity reported that AI-powered tools for market analysis, competitive intelligence, and due diligence have “accelerated our decision-making timeline by approximately 25%-30%.” This acceleration means fund managers can be “proactive business partners” rather than merely reactive investors, intervening early to address potential issues within their portfolio companies.
2 View gallery
Dorin Baniel (from left), Judah Taub, and Oren Yunger.
(Credit: Ofir Abe, David Garb, Notable Capital)
Optimizing Internal Workflows
The impact of AI extends to the everyday, internal operations of the funds themselves, making teams leaner and more efficient. This ranges from administrative tasks to knowledge management and content creation.
Miri Fenton of Maverick Ventures Israel highlighted that “note-taking tools that accurately summarize and create action items for meetings in Hebrew is a game-changer.” AnD Ventures uses AI “quite heavily for back-office efficiency: drafting investment memos, LP updates, and portfolio analyses have become much faster.”
Swish Ventures confirms AI “helps draft memos, checks numbers, speeds up research, and takes care of daily administrative work,” allowing their boutique fund to reallocate saved time to working closely with founders. Dorin Baniel of NightDragon relies on ChatGPT for drafting emails, parts of investment memos, and reviewing work.
PSG Equity uses AI for “internal process optimization,” leveraging proprietary data on “what good internal process looks like” to generate insights for better portfolio management. Key1 Capital has also integrated AI into its fund administration, even using Base44 to create a program for training employees on compliance and data security.
Knowledge Management: Horizon Capital has embedded AI into their “knowledge management systems and content workflows, significantly boosting both speed and quality.” J-Ventures views their internal AI platform as a “neural network” connecting insights across their community of over 400 professionals, surfacing relevant expertise faster.
This pervasive integration of AI helps funds stay lean, expand their reach, and sharpen their decision-making, as emphasized by Guy Yamen of TPY Capital, who stated that AI has “reshaped the day-to-day work of every partner and team member, helping us stay lean while expanding our reach and sharpening our decision-making.”
AI’s role in portfolio management is equally transformative, enabling funds to provide more proactive and data-driven support to their portfolio companies. AI platforms can monitor key performance indicators (KPIs) in real-time, alerting investors to anomalies or risks and providing strategic recommendations for growth, customer acquisition, and potential partnerships.
Key1 Capital uses AI to support portfolio companies in areas like “financial modeling, strategic options analysis, and much more,” giving them “leverage to do more with the same team, especially when it comes to parsing data and developing insights”. Catalyst Private Equity’s launch of the Catalyst Investors’ Club platform incorporates “AI-driven video analysis and investor matching algorithms,” revolutionizing how they democratize access to Israeli tech investments and supporting their portfolio. Arkin Digital Health also leverages AI to “work more efficiently with our portfolio companies and network.”
Despite the extensive integration and high ratings, a recurring theme among the VCs is that AI serves as a powerful augmentation tool rather than a replacement for human judgment. Shelly Hod Moyal, Founding Partner at iAngels, articulated this, saying AI “has definitely made our day-to-day more efficient, from research and diligence to internal operations and content generation, but it’s still augmenting, not replacing, human insight.” She further emphasized that “the fundamentals of judgment, conviction, and decision-making remain human-led.”
Notable Capital’s Oren Yunger echoed this sentiment, stating that while AI supports routine tasks, it is “not a replacement for the core of our business—our investment decisions and interactions with founders.” He sees AI as a tool to “deepen, not replace, the human judgment and trust that define our work,” reinforcing the idea that venture capital remains fundamentally a “people business” rooted in conviction and relationships. Yonatan Sela of Square Peg affirmed that “some parts of the job will always stay human, like relationship building or fundraising.”
However, the adoption of AI is also fostering a new “AI mindset” among VC teams. At Square Peg, “Every team member (investment, operations, etc) is adopting an AI mindset” and is “encouraged to mock up and test their own ideas.” This shift pushes for faster adaptation and continuous experimentation, critical in a rapidly evolving technological landscape. Hetz Ventures’ Judah Taub noted that their technically inclined investment team has been “quick to adopt and experiment” with AI tools across internal workflows, which helps them be “sharper partners to the founders we back.”
While the benefits are clear, the full potential of AI in fund management is still being realized. Nadav Shimoni of Arkin Digital Health, despite a high rating, acknowledged that they are “constantly learning and feel there are many opportunities we have yet to materialize.” Key1 Capital also admitted they are “just getting started,” with some core functions like relationship-based sourcing and LP communications still predominantly human-driven. Catalyst Private Equity anticipates their AI adoption score will rise significantly in the coming year, expecting AI agents to become an integral part of their daily operations.
There are still challenges such as the shortage of skilled personnel with deep technological expertise, and the critical importance of data quality. Some AI systems function as “black boxes,” necessitating an understanding of the assumptions made by the system. These factors underscore that while AI offers immense capabilities, its effective integration requires ongoing learning, strategic planning, and a nuanced understanding of both its strengths and limitations.
“Artificial intelligence is poised to reshape nearly every aspect of our lives,” said Itay Ben Ari, CEO of Elephant Brokerage. “As organizations embed AI more deeply into their operational environments, tailored to their workflows, data systems, and operations, its impact will accelerate, driving efficiency and adaptability across industries. Tasks that currently require significant human effort and cost will increasingly be handled by a fleet of autonomous, self-learning and adaptive agents, delivering faster and more cost-effective results. Yet, it also raises serious challenges for workers in roles that may become obsolete, underscoring the need for thoughtful transition strategies,” he concluded.