There is a particular kind of optimism that feels almost out of place in Israel these days, something stubborn: the belief that periods of rupture can still produce invention. It is this kind of optimism that defines Mor Assia.
The founding partner of iAngels sits at the intersection of several Israeli archetypes at once: the Technion graduate who began as an engineer, the former Unit 8200 technologist, the investor who moved through SAP, IBM, and corporate strategy before returning home to build something from scratch.
Fourteen years ago, she founded iAngels with an ambitious thesis: opening Israeli early-stage technology to global investors before companies crossed the Atlantic and became obvious bets. Today, the firm has invested in more than 120 startups and deployed roughly half a billion dollars. Yet Assia speaks less like a financier and more like an engineer still fascinated by systems. And right now, the system she is most interested in is AI.
Not because she believes it will replace people, quite the opposite. “Most CEOs I speak to don’t want to fire everyone,” she says. “They don’t want fewer employees, they want every employee to create value every day and feel he or she has an army of employees working for them.” That framing, AI as an amplification, runs counter to the darker narrative that has dominated much of the public conversation.
Where headlines warn of displacement and extinction, Assia sees leverage, speed and a new entrepreneurial opening. “There’s been so much talk about AI like it’s the beginning of the apocalypse,” she says. “I don’t see it that way. I see it as a change in narrative."
Still, hers is not blind enthusiasm. It is the optimism of someone who has lived through enough technology cycles to know how easily industries can misread the future. Over nearly a decade and a half at iAngels, Assia has watched entire sectors rise with evangelical certainty only to stall under the weight of reality.
Frontier technologies promised revolutions but struggled with manufacturing dependencies and logistics. Climate and food technologies produced genuine innovation, particularly in Israel, but often collided with regulatory complexity and operational burdens. “We’re very tech-driven, very optimistic about adoption,” she says. “But sometimes it simply takes longer than expected, and the challenge is quickly adapting to market conditions.” Israel excelled in water technology and food innovation, she notes, yet scaling these businesses required more than brilliant engineering.
They demanded factories, certifications, joint ventures, distribution networks, all the machinery that software startups are often designed to avoid. “We became Startup Nation, then Scale-Up Nation,” she says. “But maybe sometimes collaboration, or even earlier acquisitions, are necessary because we’re a small country. It is our moment to step up and become the AI Nation” AI, she argues, is different. Not because the technology itself is new, as machine learning, and large language models, but because the economics of building have changed. “The number one reason startups die is they run out of money,” she says.
Historically, founders raised seed capital with one chance to get it right: build an MVP, secure a pilot customer, survive long enough for the next round. Now, that equation is changing. “If before a startup had one shot, now maybe they can try several times,” Assia says. “Something that took six months can take one month. You can test it, try another version, run experiments in parallel.” For investors, this creates a new kind of capital efficiency. “What a startup could do before with one million dollars,” she says, “today that same million can feel like three or four. We also must not forget that today the USD NIS ratio has changed dramatically. Companies raise capital and produce revenues in Dollars, but we pay employees with Shekels. It means that every employee just got a 20% raise but the companies don't earn that much more overnight. Layoffs might be more assiciated with currency risk, but this is where AI kicks in."
The implications extend beyond balance sheets. Assia describes AI as almost a democratizing force for entrepreneurship itself, enabling founders who once spent years building side projects after work to dramatically compress development cycles, in other words, the barrier to entry is falling. “There were founders who worked nights and weekends for two years before leaving their old jobs,” she says. “And by the time they launched, the market had already moved.” She argues that now, even less technical entrepreneurs may become builders. “People who are much less technical are going to create things they couldn’t create before.”
The house renovation problem
Yet Assia is careful not to romanticize startups at the expense of incumbents. One of the defining questions of the AI era is whether disruption will favor newcomers or strengthen established companies. Her answer is: both. Startups have the advantage of being AI-native. “It’s easier to start a company today that is AI-first,” she says. “You build from the ground up using AI tools. You can add features overnight.”
Large organizations, by contrast, face inertia. “When you have 20,000 employees,” she says, laughing, “asking every employee, ‘What did you do with AI today?’ is very difficult.” Legacy code, managerial layers, and decades-old systems create friction. But Assia resists the simplistic “David versus Goliath” framing. The giants still possess distribution, customers, regulation, capital, and global reach. And so she reaches for a metaphor. Replacing old enterprises with startups, she says, is not like tearing down a house. “It’s more like installing solar panels on the roof and getting free electricity for life.”
The goal is not destruction. “Let’s make the house smarter,” she says. “Let’s add value without breaking everything.” For founders, that means finding narrow points of leverage: specialized datasets, industry-specific tools, workflow improvements. Not replacing Anthropic or OpenAI, but building defensible layers on top. “We’re not trying to replace the foundation models,” she says. “We’re trying to create value around them.”
That value increasingly lies in data. “Who owns the unique dataset? Who has information that isn’t public?” she asks. “That’s where moats get built.” The optimism, however, comes with caveats. Assia becomes noticeably more serious when discussing the risks of AI-heavy startups.
People imagine AI development as effortless, she says, the TikTok version of reality where software appears with a few prompts. “It’s not like that,” she notes flatly. Systems require architecture, infrastructure, and governance. “If you don’t do it properly, you risk cyber threats, data leaks, exploitation.” At iAngels, where investor information and legal records sit inside internal systems, the stakes are existential. “We invested half a billion dollars,” she says. “I’m not giving unrestricted access to something that can move money around.”
Founders often get caught up in the rush and overlook this critical layer. “You don’t want to move one step forward and risk losing your core asset underneath.” While AI reduces barriers to building, it also emphasizes the need for sound judgment. This is where Assia’s focus shifts back to the founders themselves. She notes that early-stage investing is still about “teams and dreams,” but the criteria are evolving.
Her first and most important question now is brutally straightforward: Will this become commoditized? “Can I just download this from Anthropic in two years?" If so, she walks away. Assia believes the future belongs to founders tackling ideas too complex or ambitious to be easily commodified. “Founders tend to fall in love with solutions,” she says, "adding just one more feature, one more quarter." Instead, she encourages going to market, testing, and acting swiftly.
Which inevitably brings the conversation back to Israel. Assia speaks about the country with the same combination of realism and faith that characterises her view of technology. The war is never far from the background- reserve duty, economic pressure, and uncertainty have reshaped daily life, and this in turn creates an interesting pattern. “There’s always this innovation boom after periods of challenge,” she says. “A baby boom and an innovation boom.”
Then she reaches for one final metaphor. “The train is leaving the station,” she says. “You don’t want to jump on when it’s already going 200 miles an hour.” For Israel, she argues, AI is not optional. “We cannot ignore this cycle. We have to lead it.” “If you’re not part of the solution, you’re part of the problem,” Assia concludes. The train, in other words, is already moving, her advice is simple:
This article was written in cooperation with IANGELS