VC AI Survey
“AI will impact nearly every industry, perhaps as much or even more than mobile”
Shelly Hod Moyal, iAngels’ Founding Partner, joined CTech for its VC AI Survey to share insights on how the technology has changed the investment process.
“AI will impact nearly every industry, perhaps as much or even more than mobile did. It’s going to change how people interact with products, with a shift toward conversational interfaces, personalization, and automation,” explained Shelly Hod Moyal, Founding Partner at iAngels. “Entire workflows will be redesigned. Even professional services — law, finance, healthcare — are already being disrupted. We may not know exactly how yet, but we can expect to see transformation not just in how products are built, but how they’re consumed.”
1 View gallery
Shelly Hod Moyal and Mor Assia, Co0CEOs and founding partners at iAngles
(Efi Sameach)
Hod Moyal joined CTech for its VC AI Survey to share insights on how the technology has changed the investment process and what investors can look for in founding teams.
You can read more below:
Fund ID
Name and Title: Shelly Hod Moyal, Founding Partner
Fund Name: iAngels
Founding Team: Shelly Hod Moyal & Mor Assia
Founding Year: 2013
Investment Stage: Early
Investment Sectors: AI, FinTech, Cyber, Healthcare, Software
On a scale of 1 to 10, how has AI impacted your fund’s operations over the past year - specifically in terms of the day-to-day work of the fund's partners and team members?
6 - 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. We’re experimenting with a range of AI tools that support our investment process, but the fundamentals of judgment, conviction, and decision-making remain human-led.
Have you already had any significant exits from AI companies? If so, what were the key characteristics of those companies?
Yes, we’ve had a few notable exits from companies with strong AI components. BioCatch is a good example: a cyber pioneer in behavioral biometrics, driven by deep AI and data science, who were recently acquired by Permira for $1.3b.
Oddity is another: Voyage81, the tech behind Oddity, was built on core computer vision and deep learning IP. Oddity (ODD), a now publicly traded company on the NASDAQ has a market cap of $4b.
eToro (ETOR), the world’s largest social trading platform, which went public last month, with a market cap of $5.5b, is another example of a portfolio company constantly integrating new AI technologies into their tech stack. These companies weren’t just “AI-native” — they built real defensible value by integrating AI in a way that created unique outcomes. That’s what drives returns.
Is identifying promising AI startups different from evaluating companies in your more traditional investment domains? If so, how does that difference manifest?
Not fundamentally. We’ve always looked for companies pushing the edge of innovation — and that includes AI. AI evolves in cycles: machine learning, deep learning, now large language models. Once a capability becomes widely adopted, it becomes standard and it takes on a new household name rather than “AI”. The companies we back have always used AI as a core part of their tech stack — it’s not a “nice to have,” it’s often the enabler of the product itself. We're not investing in the next foundational model; we’re backing founders building applications where AI delivers real differentiation and value.
What specific financial performance indicators (KPIs) do you examine when assessing a potential AI company? Are there any AI-specific metrics you consider particularly important?
Capital efficiency is key. With AI, a lean team can now accomplish what used to require dozens of engineers. We're looking at what founders can achieve per dollar of capital — how fast they iterate, how much product they've built, and what traction they’ve generated. The ability to scale with fewer resources is a major shift and a strong signal of operational excellence.
How do you approach the valuation of early-stage AI startups, which often lack significant revenues but possess strong technological potential?
Valuation is always about balancing risk and reward. We assess where the company is in its journey — what they’ve built, how differentiated their tech is, and what it will take to reach the next milestone. Proprietary data, defensible algorithms, and real IP matter. AI alone doesn’t justify a premium. If the product is easy to replicate — like generic AI assistants or workflow tools — that lowers the bar. But if the startup is solving a complex problem in a unique way, we’ll factor that into both valuation and conviction.
What financial risks do you associate with investing in AI companies, beyond the usual technological risks?
Barriers to entry are a big risk factor. AI lowers some barriers to execution, but that creates a different risk: competition can move faster, too. Speed to product-market fit becomes critical. Infrastructure costs, data dependencies, and regulatory headwinds can all create challenges. What we’ve seen work is companies that build strong communities or design partnerships early — like Base44 did with its developer ecosystem — because GTM and defensibility are just as important as the tech itself. Some companies ride the AI mania and may show a compelling revenue curve, but we’re seriously looking for signals that such revenue is there to stay.
Do you focus on particular subdomains within AI?
We’re active across all of them — from foundational layers to applied AI in verticals like computer vision and generative tools. Our view is that AI isn’t a vertical — it’s a layer that cuts across industries and product categories.
How do you view AI’s impact on traditional industries? Are there specific AI technologies you believe will be especially transformative in certain sectors?
AI will impact nearly every industry, perhaps as much or even more than mobile did. It’s going to change how people interact with products, with a shift toward conversational interfaces, personalization, and automation. Entire workflows will be redesigned. Even professional services — law, finance, healthcare — are already being disrupted. We may not know exactly how yet, but we can expect to see transformation not just in how products are built, but how they’re consumed.
What specific AI trends in Israel do you see as having strong exit potential in the next five years? Are there niches where you believe Israeli startups particularly excel?
Cybersecurity remains a clear strength. Israel also punches above its weight in infrastructure, DevOps, and chip design. But the real upside, I believe, will be in the application layer — where AI meets complex, real-world problems. That’s where Israeli ingenuity and multidisciplinary thinking can shine: integrating deep tech and complex algorithms with product intuition to deliver something truly differentiated.
Are there gaps or missing segments in the Israeli AI landscape that you’ve identified? What types of AI founders are you especially looking to back right now in Israel?
We’re not looking for “AI founders” as we’ve always invested in companies that incorporate elements of AI. We’re looking for outstanding founders, with experience, who are technically sharp, fast-moving, and deeply tuned into how technology is evolving. Agility and urgency are more important than ever. The rate of change in AI means that startups must continuously re-evaluate their stack and their strategy. We’re backing people who can move fast, execute well, and stay ahead of the curve — not just those riding a trend.
