AI Adoption Globally and in Israel
- September 8th
Israel-based Analysis: Startup Nation Central
Gili Horwitz, Data Analyst | Tal Sibony, Senior Manager Analytics and BI | Einat Ben Ari, Senior Director Data and Insights
Global Survey and Analysis: Georgian with NewtonX
Shaun Alphonso, Marketing, AI Research and PR
In Partnership with:
Foreword by Startup Nation Central
The AI Divide: Two Paths to Innovation and Growth
Yariv Lotan
VP of Product and Data, Startup Nation Central
In the relentless advance of technology, AI has emerged as a strategic force reshaping entire industries. This story of transformation is one of two distinct narratives unfolding across the globe. Established global companies are methodically integrating AI predominantly for efficiency, while in Israel, the startup nation, entrepreneurial fervor is leading innovation and growth. Beyond code and algorithms, this is about people, strategy, and the very future of how we create value.
The Global Story: A Quest for Efficiency
The global AI journey is a testament to the power of methodical implementation. Companies worldwide have moved past experimentation, with 83% now considering AI a top-five strategic priority. The focus is clear: to leverage AI for cost savings and internal productivity. This is evident in the adoption of AI tools to streamline operations in departments like HR, Legal, and IT. This cautious approach, however, has created a significant hurdle. Many businesses are struggling to connect their AI investments to concrete, measurable business value, with over half of R&D executives admitting they don’t have clear KPIs. The journey is further complicated by a persistent talent gap, with a lack of skilled professionals cited by 45% of R&D respondents as a primary barrier to scaling AI initiatives. This story is one of pragmatic progress – a steady, deliberate path that risks overlooking breakthrough innovation.
Israel's Story: The Applied AI Powerhouse
Israel, by contrast, is writing a different story of unprecedented AI density and an unwavering focus on applied innovation. Its exceptional entrepreneurial DNA has resulted in a vibrant ecosystem of AI-driven companies. While global giants focus on foundational AI, Israel distinguishes itself through applied AI, leveraging models to solve novel and specific challenges across diverse sectors. This approach has proven value, demonstrated by the fact that Israeli AI companies are four times more likely to be acquired by top multinational corporations compared to their non-AI counterparts. This success is fueled by a profound belief in the power of in-house development and a growth-first strategy. Israeli firms are less focused on operational efficiency and more focused on market expansion and redefining the user experience. This translates to a stronger conviction in AI’s business impact, as executives are more confident in its ability to drive measurable revenue gains. They see AI not as a tool for minor improvements, but as a catalyst for a fundamental re-imagination of product and service delivery.
The Path Forward: Redefining Value
The convergence of these two stories reveals a critical opportunity. The global focus on efficiency provides a solid foundation, while Israel’s pioneering approach offers a glimpse into the next wave of AI value creation. The future of AI will not be about incremental gains; it will be about redefining the user experience, ensuring data ownership and safety, and delivering sustainable business value. The need for predictability and clear guardrails for AI systems is vital to this new understanding of how data flows, which involves a bi-directional transformation between structured and unstructured data. This is the key to creating personalized applications that solve well-defined user needs.
For founders, this is the new playbook: the long-term value lies not only in the model itself, but in the data moat you build by creating systems that strategically capture and curate a unique combination of contextual data, user persona data, and application-specific data. It is this deep understanding of a user’s problem, powered by a profound plan for data ownership and safety, that creates true defensibility. This is also where investors will find their most compelling opportunities. The real power lies in the Applied AI Edge, found in ventures that move beyond generic augmentation to build solutions that apply these powerful models to solve highly specific, high-value problems in niche domains. These are the ventures with the clearest path to redefining an entire market and building a lasting advantage.
Foreword by Georgian
James Lamberti
Head of Go-to-Market, Georgian
At Georgian, we see AI adoption as central to both our investment thesis and the growth trajectory of our portfolio. Most of our companies today sit in the “walker” or “runner” stages of maturity, which aligns with our belief that competitive advantage increasingly depends on leveraging AI. “The companies that move fastest are the ones turning AI into real adoption and revenue,” James noted. Some of our portfolio companies are AI-first disruptors, others are embedding AI features into their offerings. Via Georgian’s AI Lab, we’ve also partnered with founders to build transformative solutions both with AI first portfolio companies and portfolio companies looking to add AI features to their existing platform quickly.
In the market more broadly, AI adoption is not uniform across sectors, but tends to cluster around specific “jobs-to-be-done.” Customer service was among the earliest areas to embrace AI, particularly in retail, e-commerce, and healthcare, where users were already accustomed to chatbots and the evolution to AI agents is a natural and more seamless use case. Sales and marketing are quickly following as indicated by the market trend around Vibe Go-to-market where AI plays a big role in content generation and outbound messaging. Cybersecurity, by contrast, has been more cautious, focusing on AI’s role in detecting and mitigating the new threat vector of AI itself. “It’s not about replacing humans everywhere, it’s about augmenting workflows where people struggle to keep pace without losing trust or reducing quality in the output,” James emphasized.
Our AI, Applied benchmark research, including surveys across global and Israeli ecosystems, reveals a striking polarization. Israel, for example, has more “crawlers” but also more “runners” than the rest of the world on average. This duality reflects differences in company size, leadership approach, and risk appetite. Larger organizations often focus on internal productivity use cases, while smaller, fast-moving startups push AI into core products and revenue drivers. Adoption often begins bottom-up, with individuals experimenting. “Many initiatives will ultimately fail to gain traction and this is OK, but the ones that do work can change a company’s trajectory overnight,” James explained. “This experimentation is vital and should continue with the goal of taking winning ideas and getting them into production more quickly.”
Looking ahead, Georgian sees the next waves of AI in infrastructure and developer tools enabling individual developer productivity to manifest in full R&D function productivity. Physical AI bridging robotics and AI software to transform industries like manufacturing and logistics is also an area to watch. “The companies that wait risk falling behind. AI is already changing competitive dynamics, those who adapt now will lead tomorrow,” James concluded.
Survey Background and Methodology
Over the past year, the global race to integrate artificial intelligence has accelerated, driven by advances in generative models and increasing organizational pressure to act. But how aligned are companies in their AI strategies? And where does Israel stand in relation to the rest of the world?
To answer these questions, this report draws on Georgian’s latest Global AI Adoption Survey, conducted in collaboration with NewtonX in June 2025. The study gathered insights from 634 senior technology executives across B2B and enterprise firms spanning R&D and go-to-market functions. For the first time, the survey includes data from Israeli companies, enabling direct regional comparisons with global peers.
The report benchmarks adoption patterns across both cohorts, Israel and the Rest of the World (RoW), highlighting strategic priorities, friction points, and what’s needed to shift from experimentation to impact.
Participants completed a comprehensive online questionnaire covering AI investment priorities, deployment progress, use cases, perceived benefits, and implementation challenges. The sample includes a mix of 634 global respondents, among them 73 Israeli executives.
The report includes both global findings as well as findings segmented into two cohorts – Israel and RoW – to surface alignment, divergence, and emerging opportunity areas in how organizations approach and scale AI.
Key Global Findings
AI Becomes a Top Priority for Nearly All Organizations
83% of respondents now rank one of three AI initiatives among their top organizational priorities: optimizing internal efficiency with AI tools, building AI/ML models in-house, or deploying external AI features. 81% of companies now use AI to drive internal efficiency, making it the most common initiative, followed by internal model development (63%) and third-party AI deployment (43%). Notably, 31% of respondents prioritized both building AI/ML capabilities internally and deploying external AI/ML models or features through third-party solutions. This hybrid approach underscores the trend toward flexible, multi-channel AI adoption strategies, where organizations combine internal development with external partnerships to maximize efficiency and innovation.
Top 10 Organizational Priorities: |
|---|
1. Use of AI tools by internal teams to improve efficiency |
2. Building AI/ML models or product features internally |
3. Major market expansion |
4. Deploying an External AI/ML model or feature using third-party software or services |
5. Diversification of Revenue Streams |
6. Customer Experience Enhancement |
7. Brand Development and Positioning |
8. Tech stack upgrade or other major operational change |
9. Restructuring or reorganization plan |
10. Agile Transformation |
Deployment Extends from R&D into Sales, HR, and Security
AI integration now spans nine enterprise functions, with Data (analysis and insights) and Sales & Marketing remaining the most mature use cases. While overall deployment rates are relatively stable since November 2024, operational domains such as IT & Security, Legal, Customer Success, and HR have seen modest increases, reflecting a shift from AI as a purely R&D asset toward a broader tool for enterprise efficiency. This diffusion suggests growing organizational confidence in applying AI beyond technical teams, though progress remains uneven.
Shift from Revenue Growth to Cost Savings Signals AI’s Operational Turn
Across functions, increasing team productivity and creating a competitive advantage are the top motivations for applying AI. At the same time, there’s a noticeable shift away from revenue generation and toward cost savings, signaling a broader focus on operational efficiency. This trend is reinforced by rising AI adoption in internal functions like IT, HR, Legal, and Customer Success, where AI is being used to reduce manual tasks, speed up workflows, and cut operational costs. As companies move beyond experimentation, AI is increasingly seen as a tool to strengthen the backbone of the organization- not just boost the top line.
AI Deployment in R&D Shifts Toward Scalable, Service-Oriented Functions
AI is increasingly being deployed in production for customer-facing and perception-driven use cases- notably in customer support and image and video recognition. These areas reflect a broader enterprise focus on improving real-time responsiveness, user experience, and automation at scale- aligning with macro trends in digital service delivery and content intelligence.
Meanwhile, adoption in personalization and risk management shows signs of retreat. As regulatory pressure mounts and scrutiny around data privacy and algorithmic fairness intensifies, organizations appear more cautious about deploying AI in sensitive decision-making contexts, especially where transparency and auditability are critical.
The R&D landscape is bifurcating: AI is scaling rapidly in visible, high-volume service functions, while risk-heavy domains are advancing more conservatively amid growing trust and compliance concerns.
Surge in Use of Owned and Public Data for AI Model Training
The near-universal use of owned data and sharp rise in public data usage signal a broader shift toward more accessible and governable training sources. As foundational data reaches saturation, companies are beginning to diversify- tapping into third-party, synthetic, and dark data to extend model capabilities and mitigate data limitations.
This signals a more mature data strategy: one that prioritizes control and compliance, while gradually layering in alternative sources to fuel next-stage model performance.
Israeli Partners Perspective
Aviram Hazak, Partner, Herzog Fox & Neeman,
Ariel Yosefi, Head of Technology Regulation, Herzog Fox & Neeman,
Ofer Sachs, CEO, Herzog Strategic
Investment & Deal, Making Implications
Aviram Hazak, Partner, highlights a gradual shift in how AI impacts investment deals. “Currently, we still don’t see investors requiring that companies they invest in have defined roles like ‘AI Compliance Officer’ or internal AI committees. But that may very well change fast, because investors as well as commercial partners expect not only to reflect the current legal requirements, but also the ones which are expected to apply, especially for companies targeting European or US markets. Startups that arrive with a clear understanding of AI risks, current trends and possible future trends, and how they plan to manage them, tend to build investor confidence more easily.”
Herzog advises clients to proactively embed responsible AI principles into their operations, not only to meet immediate legal standards but also to support long-term scalability and global market entry.
Regulation & Readiness
“We’re seeing growing awareness among tech companies, but actual implementation of AI governance frameworks is still limited. Many startups, especially in SaaS and cybersecurity, are integrating generative AI tools without any formal policies in place. With the EU AI Act entering into force in the EU, and new AI-related laws being enacted in many US states, the pressure is mounting. However, despite the significant awareness of the regulatory risks by Israeli companies, many don’t fully understand what’s coming and how to navigate their compliance efforts efficiently.” Ariel Yosefi, Head of Technology Regulation
While AI is increasingly adopted across Israeli tech companies, few have taken concrete steps to align with regulatory frameworks like the EU AI Act or set internal compliance protocols. Legal advisory work currently focuses on helping clients future-proof their contracts, audit trails, and data governance as international compliance becomes more urgent.
Read More
Contracts & Client Expectations
“It’s rare to see companies with defined roles like ‘AI Compliance Officer’ or internal AI committees. That’s going to change fast. Our role is to advise clients not just on what the law says today, but what it’s likely to become, especially for companies targeting European or US markets.” Ariel Yosefi, Head of Technology Regulation
A key concern is the gap between what clients demand (especially enterprise clients abroad) and what local startups currently practice.
There is growing demand for:
- AI, related clauses in contracts
- Transparency around AI, generated content
- Human oversight and validation
Herzog is proactively incorporating these elements into B2B contracts, particularly in healthcare, fintech, and platform SaaS.
National Strategy & Competitive Advantage
“AI is no longer just a tech issue, it’s national infrastructure. Countries that define AI governance effectively will gain lasting competitive advantages. In Israel, the private sector is moving faster than the public one.” Ofer Sachs, CEO, Herzog Strategic
Herzog Strategic, beyond the legal angle, partners with both government bodies and private enterprises to help shape AI policy as part of broader technological and organizational transformation. The rapid deployment of AI tools across sectors such as HealthTech, Finance, Agri, Tech, and Cybersecurity demands forefront governance and a holistic business strategy.
Their strategic focus includes:
- Aligning and realigning national policy with global AI frameworks and trends
- Supporting the development of innovation sandboxes
- Assisting policymakers and C-level executives on emerging AI risks and opportunities
Lotan Levkowitz
Co-Founder and General Partner, Grove Ventures
Grove Ventures has placed AI at the heart of its investment thesis, with enterprise-grade artificial intelligence acting as a cornerstone strategy across its portfolio. The firm prioritizes startups that not only adopt AI, but also embed it deeply into their product DNA, moving beyond experimentation to scalable, production-grade deployment. The focus is on leveraging AI for a measurable impact, including improved accuracy, a higher level of automation, and faster time-to-value for enterprise clients.
Two companies in Grove’s portfolio exemplify this approach. Navina, active for over six years, uses AI to extract and structure complex patient histories from unstructured medical data. This not only improves clinical accuracy and reduces errors, but also enhances the physician’s experience and the overall quality of care. Limitless.CNC takes a similarly transformative path in the manufacturing sector. Its AI-powered CAM (Computer-Aided Manufacturing) platform combines a proprietary foundation model, customer-specific fine-tuning, and reinforcement learning within digital simulations. This enables even junior programmers to achieve expert-level output, outperforming conventional automation tools.
AI’s role in driving business outcomes is also evident in ActiveFence, a leader in the trust and safety domain. The company supports major global players, including firms from the “MAG 7”, by replacing labor-intensive moderation workflows with AI-driven automation. The result is a scalable, high-revenue product now generating tens of millions annually. ActiveFence’s deliberate AI rollout strategy, starting with human oversight, validating accuracy, and gradually increasing automation, demonstrates a best-in-class adoption model that aligns technological evolution with client trust.
Read More
From Grove’s viewpoint, the current wave of AI transformation is unfolding in two acts. The first has already shown significant productivity gains in high-skill professions, law, medicine, software engineering, and content creation. The second act, now emerging, is focused on augmenting or replacing white-collar roles that require minimal onboarding and industry-specific expertise. This presents an enormous opportunity for startups to capture efficiency and scale across a broad swath of the workforce. Simultaneously, the firm sees tremendous potential in Physical AI, the application of AI to manufacturing, logistics, and robotics. This trend promises to catalyze the next industrial revolution, reshaping how physical goods are produced and moved.
Yet, Grove Ventures also observes several misconceptions that persist in early-stage startups. Many founders rely too heavily on customer feedback rooted in pre-AI mindsets, inadvertently solving yesterday’s problems instead of anticipating tomorrow’s needs. There’s also a tendency to underestimate how quickly incumbents can adapt when motivated by competitive threats. The myth of the “lean AI company”, building massive outcomes with minimal staff, is another fallacy, as Grove believes sustained success is still grounded in collective decision-making and operational depth. Additionally, startups often place excessive emphasis on model sophistication, when in reality, lasting value lies in data ownership and seamless workflow integration.
Adopting generative AI and LLM-based systems presents its own challenges. Unlike traditional deterministic software, these systems are probabilistic in nature, which demands a shift in how products are designed and governed. Grove encourages its portfolio companies to not only define what a system should do, but also invest in defining what it must not do. The creation of clear guardrails is critical to ensuring safe, reliable, and high-quality user experiences.
To help founders navigate the gap between AI hype and real-world value, Grove emphasizes a problem-first approach. Founders are urged to validate actual user pain points before embedding AI solutions. Once deployed, automation should be introduced with care, ensuring strong human-in-the-loop frameworks that build trust and create defensible market positions. On the go-to-market side, Grove works closely with teams to integrate AI into internal workflows, accelerating learning curves and competitive positioning.
While Grove’s strategy has always embraced AI, the recent surge in generative AI has sharpened its focus even further. Every portfolio company has been encouraged to reassess its positioning, to become disruptors rather than victims of disruption. While AI adoption isn’t a formal checkbox in investment decisions, Grove does look for startups with a clearly articulated, defensible plan for leveraging AI in ways that create compound advantage as foundational models improve.
Looking ahead, the firm predicts a major wave of innovation in Service-as-Software, digitally native replacements for professional services that are traditionally human-delivered. This vision extends beyond chatbots or surface-level automations, aiming to reinvent entire categories as scalable, AI-powered software products. Alongside this, Physical AI will continue reshaping industrial processes at scale. On both fronts, AI will play a central role in shrinking iteration cycles for startups and supercharging decision-making and diligence for investors. The winners will be those who balance technological sophistication with clear market need, execution discipline, and thoughtful governance.
Israel Findings and Comparison to Rest of World (RoW)
Israeli Firms Prioritize Market Growth Over Operational Optimization
While global peers largely view AI as a tool to improve internal productivity, Israeli firms are more likely to leverage it for revenue-generating initiatives and market expansion. This growth-oriented posture reflects Israel’s entrepreneurial culture and strong commercial focus, where AI is seen not only as a cost-saving mechanism but as a catalyst for capturing new markets and scaling innovative products. Compared to the RoW, Israeli companies show a greater willingness to push AI into front-line business strategies, signaling a bolder approach that blends technical excellence with ambitious go-to-market strategies.
AI Deployments in Israel Concentrate on Engineering and R&D
A striking 84% of Israeli organizations report production‑level AI use in R&D and engineering, compared with 60% globally, while operational areas such as Sales, HR, and IT Security lag by 10-15% points. This concentration reflects Israel’s deep engineering talent pool and product‑first ethos, suggesting that broader enterprise functions have yet to fully integrate AI into their workflows.
Here are some notable Israeli tech companies actively developing or integrating AI into software development, product innovation, and data analysis.
In‑House AI Development Reflects Israel’s Engineering DNA
A notable share of Israeli companies (38%) build or custom-stitch their AI solutions- surpassing the 33% global average. At the same time, Israeli firms are less likely than their global peers to rely primarily on turnkey solutions from third-party vendors. This preference for internal builds reflects Israel’s engineering-led culture and strong technical capabilities, enabling companies to develop tailored AI systems that align more closely with their specific needs. While many global firms prioritize speed and scalability through off-the-shelf platforms, Israeli organizations continue to favor flexibility, control, and in-house innovation.
AI Maturity in Israel Features More ‘Runners’ and Fewer ‘Walkers’
When benchmarked against the Georgian “Crawl-Walk-Run” AI maturity model, Israeli companies are more likely to classify themselves at the extremes- either in the early exploratory phase or in advanced production deployment. Just 32% of Israeli firms fall into the “Walk” category, compared to 42% in the rest of the world, while 19% identify as “Runners” actively scaling AI across functions, compared to 14% globally. This polarization reflects Israel’s engineering-led culture, where firms often push quickly from experimentation to execution, bypassing slower incremental rollouts. It also mirrors a broader pattern across the dataset: Israeli companies show sharper execution in technical domains but adopt AI less evenly across the organization.
Heightened Confidence in AI‑Driven ROI Among Israeli Executives
Approximately 26% of Israeli executives report being “very confident” that their AI initiatives will yield measurable revenue gains, compared with 20% of global peers. This elevated confidence suggests a greater emphasis on outcome-driven AI strategies, supported by more developed KPI frameworks and governance practices. It also reflects how AI is being positioned in Israel- not just as a tool for optimization, but as a lever for business growth. When combined with lean development practices and a hands-on approach to implementation, this mindset may help explain the country’s strong momentum in translating AI into practical, revenue-aligned outcomes.
Cost‑Efficient AI Deployment Enabled by Abundant Technical Talent in Israel
Unlike their global peers, Israeli firms face fewer roadblocks in scaling AI- thanks to deep technical talent and disciplined execution. Only 33% cite talent shortages vs. 48% globally, and just 28% report high training costs (vs. 46%). These disparities reinforce Israel’s consistent pattern of engineering-led adoption and lean, in-house development strategies. Rather than relying on vendor-heavy infrastructure, Israeli teams appear to capitalize on readily available technical talent and disciplined R&D execution, allowing them to advance AI initiatives with fewer frictions and reduced cost exposure.
Summary
AI is no longer experimental; it has become a core lever of enterprise strategy, with cost efficiency now rivaling competitive edge as the primary driver. While talent shortages remain a top global barrier, Israel is charting a differentiated course: engineering-led, growth-oriented, and confident in ROI delivery. This momentum is fueled by in-house development, disciplined R&D execution, and a strong technical talent base. Yet to fully capitalize on these strengths, Israeli firms must expand adoption beyond R&D teams and invest in research and talent.
Methodology Notes
- The report is based on the following sources:
- The Startup Nation Finder database.
- “The contribution of Israel’s High-Tech Sector to Economic Resilience and Macroeconomic Performance”, a paper published by the Aaron Institute for Economic Policy at Reichman University Policy Paper, April 2025.
- Pitchbook.
- The definition and criteria for companies, investors, and Multinationals (MNC’s) can be found in the Finder Glossary.
- Aggregate metrics may include rounds that are not visible in Finder, per the request of the profile owners.
- Funding Type definitions:
- Private Funding includes the following round types: Pre Seed, Seed, A, B, C, D, E, F, G Rounds, Convertible Debt, SAFE, Equity Crowdfunding, and Undisclosed rounds.
- Funding for Public companies includes the following event types: IPO (including IPO via SPAC or Reverse Merger), Non-Initial Public Offering, PIPE.
- The following events are excluded: Crowdfunding, Debt Financing, Secondary, and Grants.
More on the israeli tech ecosystem
About Startup Nation Central
Startup Nation Central is a free-acting NGO providing global solution seekers frictionless access to Israel’s bold and impatient innovators to help tackle the world’s most pressing challenges. Our free business engagement platform, Finder, grants unrestricted access to real-time, updated information and deep business insights into the Israeli tech ecosystem.