“Israel’s AI potential is immense - but serious gaps threaten our ability to lead the global transformation”

“Israel’s AI potential is immense - but serious gaps threaten our ability to lead the global transformation underway,” said Yaniv Golan, Managing Partner at lool ventures. “As long as we remain focused on fulfilling ancient, irrelevant fundamentalist dreams, the world will continue building the future without us - and we risk being left behind.”

Golan joined CTech for its VC AI Survey, where prominent investors share what makes Israel a booming sector, but also how its tech ecosystem can thrive.

Yaniv Golan

“Without bold public-sector vision, coordination, participation of the entire workforce, and, most important of all, forward-looking education, Israel may follow rather than lead - and that’s a luxury we can’t afford,” he added. “These are the real gaps. Let’s fix them - our AI founders will easily take care of the rest.”

You can learn more in the interview below.

Fund ID
Name and Title: Yaniv Golan, Managing Partner
Fund Name: lool ventures
Founding Team: Avichay Nissenbaum and Yaniv Golan
Founding Year: 2012
Investment Stage: Pre-seed and Seed
Investment Sectors: AI, Fintech, Cyber, Mobility, Healthcare, Foodtech. lool ventures is sector-agnostic, and the team is made of curious people. We focus on inspiring teams who set out to solve problems worth solving, and not on specific sectors.

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?

7 - Over the past year, AI has fundamentally transformed our fund’s operations, significantly enhancing efficiency and productivity across virtually every aspect of our daily workflow. Specifically, AI-driven tools have been seamlessly integrated into:

• Market Research and Analysis: Quickly synthesizing vast amounts of market data, identifying trends, competitive landscapes, and opportunities with speed and accuracy that manual processes simply couldn't match.
• Due Diligence: Enhancing our capacity to perform comprehensive background checks, industry assessments, and technology evaluations, improving the depth and thoroughness of our investment analyses.
• Projections and Simulations: Enabling sophisticated predictive modeling and scenario planning to better anticipate investment outcomes, assess risk, and make more informed strategic decisions.
• Content Creation: Supporting the rapid production of high-quality thought leadership materials, presentations, investment memos, and reports, enabling us to communicate our insights and decisions more effectively.
• Legal and Contractual Processes: Accelerating the review and creation of agreements and contracts, significantly reducing turnaround times and minimizing human error.
• CRM and Relationship Management: Improving our ability to track interactions, manage deal flow, and maintain personalized, timely communications with entrepreneurs, co-investors, and other stakeholders.
• Email Processing and Internal and External Communication: Streamlining routine correspondence and prioritizing important conversations, allowing team members to focus on strategic interactions.

Overall, AI has become indispensable, enhancing not only the efficiency of our operations but also the quality and strategic value of the work performed by our partners and team.

Have you already had any significant exits from AI companies? If so, what were the key characteristics of those companies?

Yes, we've already experienced notable exits from AI-focused companies in our portfolio. Common characteristics among these successes include:

• Clearly Defined Problem-Solution Fit: Each company addressed significant market pain points with targeted AI solutions, solving tangible challenges faced by enterprises.
• Deep Technical Advantage: Their technology leveraged proprietary innovation and, at times, also proprietary datasets, making it challenging for competitors to replicate quickly or cheaply.
• Enterprise Market Traction: They rapidly secured meaningful traction with significant enterprise customers, validating both demand and commercial scalability.
• Strategic Value to Acquirers: Ultimately, their technology and market positioning provided immediate strategic value to industry-leading global players, catalyzing attractive acquisition opportunities.

Is identifying promising AI startups different from evaluating companies in your more traditional investment domains? If so, how does that difference manifest?

Fundamentally, evaluating AI startups shares the same core principles we apply when assessing opportunities in any other domain: the strength - and passion - of the founding team, and the relevance and urgency of the problem they're solving are paramount.

However, AI startups introduce an additional layer of complexity. Specifically, the evaluation process must pay close attention to the company's long-term competitive advantage or moat. Given the rapid and accelerating advancement of AI models and related tools, today’s technological edge can quickly become tomorrow’s standard commodity - particularly if next month's models provide similar capabilities out-of-the-box.

In general, this means our analysis must increasingly account for the exponential nature of technological progress. We must assess not only where the market is today but anticipate the accelerating rate at which AI innovations reshape competitive dynamics and market positions.

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?

When evaluating AI startups, we may track traditional financial KPIs such as gross margin, burn rate, and runway - recognizing that many AI companies typically face higher expenses not only due to compute infrastructure but also specialized talent costs. AI startups also employ usage-based pricing, making revenue predictability an important consideration.

In addition, depending on the nature of the specific business, we may focus specifically on:

• Cost of Compute: The cost per inference or prediction directly influences scalability and profitability.
• Data Costs: Expenses related to data acquisition, labeling, and licensing significantly affect margins.
• Model Performance & Efficiency: Technical metrics such as accuracy, latency, and reliability, which tie directly to customer retention and operational efficiency.

These AI-specific indicators help us determine whether a startup's business model and competitive advantage will remain viable amid rapid technological progress.

How do you approach the valuation of early-stage AI startups, which often lack significant revenues but possess strong technological potential?

Valuing early-stage AI startups - especially those with little or no revenue - combines traditional VC methods with special attention to AI-specific potential. Here's how we approach it:

• Qualitative Foundation & Peer Comparisons

We assess team quality, data exclusivity, model defensibility, and market opportunity. We also benchmark against recent valuations of comparable AI startups to adjust expectations.

• Scenario-Based Storytelling

Instead of precise maths, we envision upside, base, and downside outcomes - anchored in possible acquisition or exit scenarios - and weight them to derive a valuation range.

• Forward Multiples & Discounted Exit Thinking

We estimate where the company might land in a future exit (e.g. licensing, M&A) using AI-specific revenue or market multiples, then discount for risk.

• Early Traction & Product Engagement

Even pre‑revenue, metrics like pilot usage, partner interest, user retention, and freemium-to-paid conversion signal potential value.

We treat promising AI domains almost like discovering a new planet — securing early technological or data moats can justify premium valuations even before any revenue arrives.

In sum: we blend qualitative insight (team, defensibility), market benchmarks, scenario-based modeling, modest traction signals, and forward-looking exit thinking - recognizing AI’s potential to be not just disruptive, but transformational.

What financial risks do you associate with investing in AI companies, beyond the usual technological risks?

When investing in AI companies, many of the standard technological risks apply - but several distinct financial risks also deserve close attention:

• Infrastructure & Talent Burn

AI development and model serving demand heavy compute infrastructure and top-tier talent. Overspending on hardware or hiring can dramatically increase burn rates and shorten runway.

• Data Dependency Costs

AI startups sometimes rely on costly third-party datasets or labeling. Any increase in data prices, licensing changes, or supply disruption can quickly erode margins.

• Compliance & Regulatory Expense

The global regulatory landscape is evolving rapidly. Meeting evolving requirements for transparency, bias mitigation, and privacy can incur heavy compliance costs - sometimes a surprisingly large share of early-stage budgets.

• Competitive Commoditization

With open-source models improving fast and commoditizing core capabilities, pricing power and differentiation can evaporate rapidly, impacting projected revenues and valuations.

• Vendor & Infrastructure Concentration Risks

Dependence on a few cloud providers or infrastructure vendors carries risks. Outages or lock-in can disrupt operations and unexpectedly spike costs.

Do you focus on particular subdomains within AI?

We don’t think of AI in terms of distinct sub-domains like ML, NLP, CV, or generative AI. Instead, we see AI as a foundational enabler - a toolkit that empowers entrepreneurs to build breakthrough solutions across sectors.

As a sector-agnostic fund, our focus is on the problem being solved and the impact that passionate founders can generate, not on which AI technique they’re using.

Whether an entrepreneur is using large language models, computer vision, or reinforcement learning matters far less than whether they’re applying these technologies in a way that creates enduring value or addresses a real market need.

We care about technological defensibility, but always within the broader context of the business opportunity.

We view AI more as an industrial revolution than a catalog of verticals. We prioritize the founders’ vision and differentiation, not ticking box‑subdomain checklists.

How do you view AI’s impact on traditional industries? Are there specific AI technologies you believe will be especially transformative in certain sectors?

We suspect that almost no industry will remain untouched by AI. AI is a transformative force that will reshape each and every industry by enabling faster, smarter decision-making, automation, and entirely new business models.

We expect to see most sectors, from logistics to healthcare and manufacturing to finance, fundamentally transformed by AI-enabled innovation over the next decade.

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?

Israel’s strength stems from technical depth, problem-solving approach, rapid execution, and early military-to-commercial tech transfer. These traits make it fertile ground for building foundational tools in infrastructure, cybersecurity, biotech, and vertical AI.

• Vertical AI platforms in sectors like healthcare, real estate/proptech, energy, logistics, and industrial enterprise tools - where Israeli teams combine deep domain expertise with technical execution.
• AI-driven life sciences and drug discovery platforms, including genomics, antibody design, and molecular modeling.
• AI Infrastructure & Data Operations Tools: Startups building operator tools, data pipelines, and AI model management are gaining traction
• AI-powered cybersecurity and model security tools - Israeli teams are building novel systems to protect AI infrastructures

We see those areas as the most compelling exit corridors for Israeli startups in the coming years.

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?

Israel’s AI potential is immense - but serious gaps threaten our ability to lead the global transformation underway. As long as we remain focused on fulfilling ancient, irrelevant fundamentalist dreams, the world will continue building the future without us - and we risk being left behind. Without bold public-sector vision, coordination, participation of the entire workforce, and, most important of all, forward-looking education, Israel may follow rather than lead - and that’s a luxury we can’t afford.

These are the real gaps. Let’s fix them - our AI founders will easily take care of the rest.