Kholoud Hussein
New playbook
Venture capital in Saudi Arabia is being fundamentally rewired by artificial intelligence. What once was a search for disruptive apps and platforms is now a race to fund companies that can build and defend algorithmic moats. Investors are no longer content with “AI-enabled” features bolted onto legacy models; they are chasing startups whose entire business logic is inseparable from data and AI. This shift is already visible in the numbers: according to MAGNiTT, Saudi Arabia attracted $860 million in venture funding in the first half of 2025, a 116% year-on-year jump, with deal counts up 31%. For the first time, Saudi matched the UAE as the region’s top investment destination during a half-year period. That momentum stands out against a global backdrop of caution in venture capital, underscoring that Saudi’s bet on AI-first entrepreneurship is not a marginal play—it is becoming central to the Kingdom’s economic diversification strategy.
Government policy has been crucial in shaping this trajectory. At LEAP 2025, Riyadh announced $14.9 billion worth of AI-related investments, ranging from hyperscale data centers to startup support funds. As Minister of Communications and Information Technology Abdullah Al-Swaha remarked at the event, “Our goal is not just to adopt AI technologies, but to produce them, to export solutions from Saudi Arabia to the world.” He highlighted that the local digital workforce had grown from 150,000 in 2021 to 381,000 in 2024, reflecting how the Kingdom has quickly built a foundation of talent that AI startups can tap into. This expansion in skills gives confidence to investors that early-stage ventures can scale without relying entirely on imported expertise.
Data over markets
Artificial intelligence has altered the very metrics that Saudi venture capitalists use to evaluate opportunities. Instead of relying on traditional total addressable market (TAM) models, investors are now considering what some describe as the “trainable addressable market.” This perspective asks: given Saudi regulations, data residency rules, and ethical frameworks, how much usable data can a startup access, label, and train on? The size of that trainable set directly affects how far a company’s model can improve and thus how much value it can capture.
Business owners in fintech, healthtech, and logistics confirm this shift. A Riyadh-based founder in digital health explained, “When we speak with VCs now, they don’t just ask how many clinics or patients we could serve. They ask how many hours of labeled diagnostic data we own, what our annotation process looks like, and how quickly our model improves with new inputs.” This level of technical due diligence signals that capital allocators in the Kingdom are now fluent in the economics of training data and algorithmic scaling.
This reframing also affects the startup lifecycle. A company that secures proprietary datasets through government partnerships, industry consortia, or user acquisition strategies becomes disproportionately attractive to investors, even at the seed stage. In Saudi Arabia, where public-private partnerships are a policy priority, startups that align with government initiatives—whether in smart cities, healthcare digitization, or financial inclusion—often gain preferential access to unique data streams. That, in turn, enhances their valuation and ability to secure follow-on capital.
Infra edge
Saudi Arabia’s decision to invest directly in AI infrastructure is perhaps the most consequential development for both startups and venture investors. In May 2025, the Kingdom launched Humain, a national AI company backed by the Public Investment Fund, with a mandate to develop domestic compute, models, and data-center capacity. Media reports indicate that Nvidia has committed 18,000 Blackwell chips to the project, with the first 100-megawatt data centers in Riyadh and Dammam expected to come online in 2026.
This matters for startups because compute scarcity has been one of the greatest bottlenecks globally. Access to high-performance GPUs in markets like the U.S. and Europe is constrained and expensive, and Saudi entrepreneurs often struggle to secure capacity at reasonable costs. By hosting this infrastructure locally, the Kingdom is effectively subsidizing the next wave of AI startups. As one venture capitalist in Riyadh noted, “When a founder can train models inside the Kingdom, on Saudi data, at predictable costs, it fundamentally changes the investment case. You reduce execution risk, regulatory risk, and margin pressure at once.”
Regulators, too, view local compute as essential. Sensitive sectors such as finance and healthcare require data to remain within Saudi borders. Having world-class capacity available in Riyadh allows startups to deploy solutions for banks, hospitals, and ministries without running afoul of compliance rules. This alignment between infrastructure and regulation is why many VCs now speak of compute availability as a national “comparative advantage.”
Startups lead
Saudi startups are not waiting for the infrastructure to mature; they are already showing how AI-native strategies can produce growth. Mozn, headquartered in Riyadh, began as a fintech analytics firm but has evolved into a leader in AI-driven fraud prevention. At LEAP 2025, Mozn unveiled new modules for agentic AI in financial crime prevention, expanding its offerings beyond traditional AML into real-time fraud detection. Partnering with banks like D360, Mozn has become an example of how Saudi startups can build for regulated industries and then scale regionally.
Another standout is Quant, which applies AI to big data problems across sectors, including retail, real estate, and government services. By tailoring models to Arabic and regional contexts, Quant provides insights that global platforms often overlook. As one retail client explained, “Quant’s AI models understand local consumer behavior in a way no off-the-shelf product can. That’s why we can optimize inventory and pricing with confidence.”
Beyond these, companies like Unifonic, Lean Technologies, Foodics, and Sary are integrating AI deeper into their platforms. Whether in customer engagement, financial connectivity, restaurant demand forecasting, or procurement optimization, these startups are weaving machine learning into core workflows, turning AI into an essential rather than optional feature. For VCs, such integration signals resilience: when AI drives the core economics of a business, customer stickiness and margins improve.
Policy and trust
While Saudi Arabia is moving fast, officials emphasize the importance of responsible adoption. Abdullah bin Sharaf Al-Ghamdi, president of the Saudi Data and AI Authority (SDAIA), has often stated that AI is not merely a technology but a “societal transformation.” Speaking at global forums, he pointed to pilot programs in water management and emissions reduction where AI delivered measurable sustainability gains, stressing that these successes must go hand-in-hand with ethical safeguards.
SDAIA’s launch of the National AI Readiness Index reflects this balance. By benchmarking government agencies on their ability to adopt AI responsibly, the state creates predictable demand pipelines for startups. For venture capitalists, this offers greater visibility: they can track which ministries are ready to procure AI solutions, in what domains, and on what timelines. This reduces uncertainty in sales cycles, a key concern for investors underwriting enterprise-focused startups.
VC craft shifts
The practice of venture capital itself is adapting. Technical diligence now includes model governance, data provenance, evaluation metrics, and cost-per-inference calculations. As one Saudi GP put it, “It’s not enough for a founder to show traction in users or revenues. We want to see model cards, red-teaming schedules, and evidence that the AI pipeline is production-ready.”
Portfolio construction is also changing. Many Saudi investors are adopting a barbell strategy—allocating to infrastructure plays like MLOps and inference orchestration on one end, and regulated application-layer companies on the other. The middle ground—generic AI platforms with weak moats—is less attractive unless the distribution advantage is overwhelming.
Perhaps most interesting is the rise of operator-led angel syndicates. Former Careem executives, now veterans of scaling tech across the region, are active in early-stage AI rounds. Their practical knowledge of distribution, compliance, and procurement is proving invaluable for young founders. This layer of operator capital shortens go-to-market timelines and reassures institutional investors.
Fintech lens
Fintech provides a clear example of how AI is reshaping venture logic in Saudi Arabia. Fraud prevention, AML, and sanctions screening are high-stakes accuracy problems that demand both speed and compliance. Mozn’s agentic AI solutions, launched in 2025, show how Saudi startups can deliver measurable results. Banks report lower false positives and faster processing times, directly improving ROI. For VCs, this kind of quantifiable impact justifies larger checks at higher valuations.
Events like Money 20/20 Middle East in Riyadh amplify the effect by bringing together regulators, banks, and startups. Vendors showcasing AI compliance tools that are tailored for Arabic and Saudi hosting requirements gain an immediate edge in procurement cycles. For investors, this is evidence that the ecosystem has reached a level of maturity where global capital and local demand intersect.
Bottlenecks
Despite the optimism, challenges remain. Compute costs, talent shortages, and capital efficiency are recurring concerns. Yet Saudi Arabia is actively addressing all three. Humain’s compute buildout and Nvidia’s chip shipments promise to ease capacity constraints. On the talent side, the government has grown the digital workforce by more than 2.5 times in three years, reaching 381,000 professionals. Special visa schemes also attract senior ML engineers from abroad.
Capital, meanwhile, is increasingly strategic. Sovereign-linked vehicles and corporate venture arms from banks, telcos, and industrial groups are investing in AI startups, not just for returns but to acquire capabilities. This dual role as both customer and investor reduces risk for VCs and accelerates time-to-revenue for startups.
Founder edge
For founders, the message is clear: competitive advantage in Saudi AI will belong to those who own unique Arabic data, can ship production-grade models with regulatory compliance built in, and exploit domestic compute to reduce latency and costs. These are the traits that shift a startup from being “AI-enabled” to “AI-essential.” Investors recognize this and are rewarding such companies with premium valuations and substantial follow-on commitments.
Risk priced
Risks are not ignored. Model brittleness, evaluation challenges in Arabic dialects, and global talent shortages are real. But local infrastructure, policy transparency, and concentrated demand all reduce the severity of these risks. Compared to global peers, Saudi AI startups are less likely to be binary bets and more likely to become durable, ROI-driven businesses.
Next 24 months
Looking ahead, three themes dominate Saudi venture theses:
- Arabic-first enterprise copilots in finance, logistics, and government workflows.
- AI safety and trust tools, including monitoring, red-teaming, and security solutions.
- AI and Industry 4.0 converge in Saudi industrial corridors, particularly as new data centers connect to edge infrastructure.
To conclude, Saudi Arabia’s venture market is not merely experimenting with AI; it is being rebuilt around it. With record-breaking VC inflows, policy-backed AI investments, and domestic compute capacity on the horizon, the Kingdom is setting the stage for compounding innovation. As Al-Ghamdi of SDAIA recently said, “AI is not just about technology—it is about shaping the future of our society and economy.” For investors, that future is already investable. For founders, the edge will belong to those who turn Saudi Arabia’s unique data, infrastructure, and policy alignment into globally relevant AI products.
