Artificial Intelligence is rapidly transforming the VC/PE landscape. The adoption of AI agents and advanced analytics is no longer experimental; it’s becoming standard practice. For forward-thinking venture capitalists, fund managers, and portfolio strategists, understanding how and why funds are turning to AI agents is essential for staying ahead.
This blog explores the rise of AI analyst agents in the VC and PE landscape, the driving trends behind their adoption, and offers direct insights with Eilla, an AI research platform providing AI analysts supporting human experts in VC, PE and M&A.
Artificial intelligence agents, also known as AI Analysts, refer to autonomous or semi-autonomous systems that perform complex tasks using algorithms, machine learning, and large-scale data analysis.
Traditionally, venture and private equity funds relied heavily on human analysts for tasks like due diligence, sourcing. However, as market complexity grows and data becomes more abundant, human resources alone can’t keep pace.
To bring additional insights, we've engaged with Eilla AI to explore some of the most critical questions shaping this space.
1. What areas of a VC fund’s workflow have seen the most significant optimization through AI over the past year? Can you share specific examples?
"Over the past year, AI has fundamentally reshaped the early stages of the venture workflow - transforming sourcing, screening, and first-pass diligence from manual bottlenecks into fast, scalable processes. AI analysts now scan millions of companies in seconds. What once took a full day of work can now be condensed into a focused five to ten minute review.
But it doesn’t stop at identification. AI Analysts dive into research mode as well - compiling competitor landscapes, building SWOTs, and extracting relevant news and signals from sources like LinkedIn, Crunchbase, and industry publications. One of our clients reported that what used to be a half-day task for junior analysts - identifying and filtering competitors - has been cut by over 80% using our AI research analyst.
Valuation has also seen a step-change. For example, “Lucas” - our AI-powered Valuation Analyst, automatically builds public and private comps lists and generates football-field valuation charts up to 18x faster than traditional workflows. What once required a patchwork of databases and Excel muscle now happens in minutes - with full transparency and source traceability built in."
2. What are the biggest challenges VCs face when adopting AI-driven insights, and how can firms foster team and LP buy-in for these new technologies?
"The biggest challenge in adopting AI isn’t the tech - it’s trust. Investors are wary of black-box outputs and accuracy while legal and compliance teams raise flags around data privacy. To facilitate adoption and build confidence - we decided to directly offer a 7-day free trial as we strongly believe the only way to trust these AI analysts is to work with them.
Also, we’ve focused on building tools for high value repetitive tasks like comps or competitor research. This enables VCs to measure the lift much more easily: time saved, speed to insight, quality of output, etc. Also, transparency is key. When every AI result comes with clear sources and the reasoning of the model, internal teams gain confidence quicker.
LPs respond the same way. Sharing hard numbers and live demos builds buy-in faster than slide decks ever could. Once they see that AI isn't replacing judgment, just accelerating it, it stops being a risk - and starts being an edge."
3. How can AI ensure trustworthiness, compliance, and transparency in investment decisions and due diligence processes?
"To expand on the answer to the previous question, AI earns trust the same way a great analyst does - by showing its work and explaining the logic behind it. The most effective tools don’t just give you answers - they show where every piece of information came from, link directly to the source data, and flag uncertainty or contradictions when there is such between different sources. This level of transparency makes it easier for deal teams and ICs to scrutinise and validate insights which is the exact reason for which on Eilla we’re listing the source or the logic behind every output and data point.
On the compliance side, trust starts with control - strict data retention policies, access control and audit logs that track every query and output."
4. For VCs looking to adopt AI in the coming years, what steps should they take to effectively integrate these tools into their operations?
"For VCs, the time to adopt AI isn’t “in the coming years” - it’s now. The market has already moved, and funds that wait risk falling behind. For firms just beginning their AI journey, the clearest path forward is to adopt tools which are purpose-built for VCs - solutions refined over multiple years through direct input from hundreds of investors.
Platforms like ours don’t just deliver speed - they mirror how deal teams actually work, across sourcing, diligence, valuation, memos, and portfolio monitoring. They’re structured, secure, and deployable in minutes. Building internally, by contrast, is slow, costly, and almost never moves beyond the pilot phase.
The modern playbook is simple - start with one use case, plug in a tool designed to handle the specific task, and demonstrate value in weeks. Then expand. The firms out in front today aren’t just exploring AI - they’re actively thinking of ways to implement it."
The integration of AI Analysts is fundamentally changing how venture and private equity funds operate. These tools enhance accuracy, speed, and scalability, helping funds identify opportunities, manage risk, and meet higher expectations from LPs and regulators alike.
The greatest value emerges when human expertise and AI-driven analysis work in tandem. Funds that cultivate this synergy will not only thrive but set the pace in an increasingly data-driven market.
If you're interested in applying AI Analysts to your fund, discover more here with Eilla. They offer a 7-day free trial to their platform that you can access by registering.
%20(1).png)
