While AI has been around for decades, over the past few years, AI has evolved almost beyond imagination. Regulations that seemed sufficient a few short years ago are now entirely outdated and unequipped to regulate AI’s current capabilities. For countries seeking to expand into the tech industry and grow their global reputation, this development presents equal parts of risk and opportunity.
The Middle East is a particularly good representation of this phenomenon, as countries in the region seize the opportunity to cement their position in the tech market and become AI superpowers. By 2030, AI could contribute $320 billion to the Middle East. The Middle East’s legislative framework is characterized as much by support for innovation as by data protection.
In this article, we explore the existing AI regulatory framework across the UAE, Saudi Arabia, and Israel, and how these respective regulations affect tech companies operating in the region.
The UAE: superpower aspirations
The UAE has made clear its aspirations to become an AI global superpower by 2031 and it pushing itself to embrace AI’s potential as a cornerstone for economic growth. This ambition is outlined in the National AI Strategy 2031, which outlines the UAE’s future strategies for AI development and management. Local companies like G24, an AI group that received a $1.5 billion investment in 2024, are taking the lead in developing a powerful AI ecosystem across high-priority sectors, including technology, healthcare, energy, logistics, and education. US-UAE private sector partnerships help power such progress and will play a significant role in cementing the UAE’s reputation as an AI leader and increasing its AI assets.
To make sure these goals are met securely and ethically, the UAE is creating an innovation-friendly regulatory environment that will support R&D, startups, and exports. Although there is no single law concerning AI in the UAE at this moment, various decrees, including Law 25 from 2018, which establishes a foundational framework for technology use and data protection in the UAE, function as partial frameworks regarding the usage of new technologies that have so far developed. While not AI-specific, Law 25 includes preventive measures that influence how AI systems handle data, and the Law can serve as a baseline for future AI-specific laws. Additionally, a number of new, non-binding frameworks, like the AI Ethics Guide of 2022 and the AI Adoption Guideline in Government Services of 2023, have also been issued as part of the attempt to establish standards that are ethical and practical.
The DIFC (Dubai International Financial Center) has also created its own set of Data Protection Regulations and amended them in 2023 to extend to the use of data by AI applications. This amendment included Regulation 10, the very first enacted regulation in the Middle East to regulate data usage by an autonomous system such as AI. In 2024, the UAE issued an AI Charter, which further encourages the use of ethical AI by detailing the principles of governance, transparency, and privacy.
Saudi Arabia: investing in innovation and data management
Like many other Gulf states, Saudi Arabia has chosen to take a business-friendly approach to AI by minimizing regulations restricting its development. With the recent announcement that the government plans to invest 40 billion US dollars into AI development, supporting the goals of specific sectors such as smart cities and energy, and the country’s plans for a digital economy plainly outlined in Saudi Arabia’s Vision 2030, it’s clear that supporting AI growth is a top priority.
Despite the government’s permissive stance and current lack of enforceable AI-specific regulations, the Saudi Data and Artificial Intelligence Authority (SDAIA) has acknowledged that while data and AI are essential to achieving the goals outlined in Vision 2030, responsible use is critical. The National Data Management Office (NDMO) is a data regulator linked to the SDAIA, which has introduced some optional regulatory standards, such as its primary framework, the Data Management and Personal Data Protection Standards. These standards place a strong emphasis on compliance with data localization mandates, specifically requiring data, particularly data used by public sector and government entities, to be processed and stored locally.
In 2023, SDAIA itself issued a public draft of the AI Ethics Principles, while in 2024, the Generative AI Guidelines were issued publicly to guide ethical AI practices. Neither is legally binding, yet they do provide businesses working with AI clear guidelines that will help make sure responsible practices are applied and further reduce potential data security risks associated with AI technology.
Israel: balancing restriction with innovation
As a world leader in developing technology, including AI, Israel’s reputation hinges on the importance of enabling innovation. Instead of formal legislation, Israel supports flexible policies built upon existing laws, like the Privacy Protection Law (PPL). These laws form the foundation on which Israel has built up its entire regulatory framework and affect data use in applications related to AI, especially those involved in cybersecurity and defense, two areas where Israel has established a global presence. By leveraging the PPL and other “soft law” frameworks, Israel reduces the pressure on organizations to comply with rigid regulations enabling AI innovation while maintaining a strong stance on data privacy and ethical standards.
This law was amended in August 2024 to better align with existing standards, such as the EU’s GDPR, and address modern data management challenges. This includes expanding its definition of “Personal Data” and “Highly Sensitive Data” to include a broader range of personal information, such as biometric identifiers and medical data. Similarly, its database registration requirements expanded to include major commercial databases in the possession of public frameworks. In addition, this amendment gives the PPA powers to issue preliminary opinions on data practices, impose administrative penalties, and seek court orders for violations.
In December 2023, the Israeli Ministry of Innovation, Science, and Technology, in collaboration with the Ministry of Justice, published its first comprehensive policy on AI regulation and ethics. This policy aims to balance technological advancement with human rights, reflecting the high-tech sector’s significant contribution to Israel’s economy, accounting for nearly 20% of GDP. The policy emphasizes a unified regulatory framework to foster AI innovation while managing associated risks. It proposes the establishment of an AI knowledge and coordination center within the Ministry of Innovation, Science, and Technology. This center, along with a steering committee, is intended to guide regulatory coordination, facilitate knowledge sharing, and advise on policy development. However, enforcement authority remains with existing regulatory bodies, with the center serving as a supportive mechanism.
The effectiveness of this framework depends on adequate resources and inter-agency cooperation. Challenges may arise due to potential budget constraints and the capacity of existing regulators, who might lack specific expertise or resources to oversee AI-related matters effectively.
Navigating AI regulations across the Middle East: similarities and distinctions
Middle Eastern nations are making distinct choices in AI regulation to support innovation while addressing their unique priorities around security and privacy. The UAE and Saudi Arabia, for instance, emphasize data localization, requiring that data generated within their borders be stored and processed locally. This strategy supports their drive for digital sovereignty and control over infrastructure, reinforcing their ambitions to establish strong AI ecosystems. In contrast, Israel, with its established expertise in cybersecurity, has opted for a flexible regulatory framework anchored in existing privacy laws, such as the Privacy Protection Law. This approach aligns with Israel’s tech-centric economy, allowing for innovation within a more stringent privacy context.
Other Gulf countries, like Qatar and Bahrain, are also shaping their AI landscapes. Qatar’s National AI Strategy emphasizes ethical AI deployment and capacity building with a focus on education and research to foster a sustainable AI ecosystem. Bahrain has adopted a business-friendly regulatory environment that prioritizes training programs and encourages openness to AI innovation while maintaining alignment with international data protection standards.
These differing frameworks create both opportunities and hurdles for companies aiming to work across the region. While the UAE and Saudi Arabia’s regulatory environments encourage rapid AI adoption and a streamlined business climate, Israel’s strong emphasis on data protection and ethical practices introduces a more measured approach. This focus on privacy may add complexities for businesses handling personal data or deploying AI solutions across borders within the region.
Thrive in the Middle East with Gcore
To navigate the complex landscape of AI regulation in the Middle East, companies must consider local compliance standards and leverage solutions that support secure and compliant data practices. This region is a hotbed of innovation, offering exciting opportunities to businesses ready to meet local regulatory requirements. When compared with stricter standards such as Europe’s GDPR, which prioritizes privacy and accountability, and the US which adopts a more sectoral and flexible approach, the Middle East prioritizes supporting innovation and favors more flexible, innovation-friendly approaches.
At Gcore, we provide sovereign AI and cloud solutions that offer localized data processing and storage tailored to meet current and future AI laws. These solutions help businesses align with regional requirements for data processing and sovereignty. Particularly for industries with stringent data regulations, like healthcare and finance, Gcore edge solutions are a powerful tool, enabling companies to store and process data closer to users while adhering to each region’s data localization and privacy mandates. With numerous points of presence in the Middle East—and beyond—Gcore is an obvious partner for businesses seeking simplified AI compliance in the region.
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Introducing Gcore for Startups: created for builders, by builders
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GTC Europe 2025: watch Seva Vayner on European AI trends
Inference is becoming Europe’s core AI workload. Telcos are moving fast on low-latency infrastructure. Data sovereignty is shaping every deployment decision.At GTC Europe, these trends were impossible to miss. The conversation has moved beyond experimentation to execution, with exciting, distinctly European priorities shaping conversations.Gcore’s own Seva Vayner, Product Director of Edge Cloud and AI, shared his take on this year’s event during GTC. He sees a clear shift in what European enterprises are asking for and what the ecosystem is ready to deliver.Scroll on to watch the interview and see where AI in Europe is heading.“It’s really a pleasure to see GTC in Europe”After years of global AI strategy being shaped primarily by the US and China, Europe is carving its own path. Seva notes that this year’s GTC Europe wasn’t just a regional spin-off. it marked the emergence of a distinctly European voice in AI development.“First of all, it's really a pleasure to see that GTC in Europe happened, and that a lot of European companies came together to have the conversation and build the ecosystem.”As Seva notes, the real excitement came from watching European players collaborate. The focus was less on following global trends and more on co-creating the region’s own AI trajectory.“Inference workloads will grow significantly in Europe”Inference was a throughline across nearly every session. As Seva points out, Europe is still at the early stages of adopting inference at scale, but the shift is happening fast.“Europe is only just starting its journey into inference, but we already see the trend. Over the next 5 to 10 years, inference workloads will grow significantly. That’s why GTC Europe is becoming a permanent, yearly event.”This growth won’t just be driven by startups. Enterprises, governments, and infrastructure providers are all waking up to the importance of real-time, regional inference capabilities.“There’s real traction. Companies are more and more interested in how to deliver low-latency inference. In a few years, this will be one of the most crucial workloads for any GPU cloud in Europe.”“Telcos are getting serious about AI”One of the clearest signs of maturity at GTC Europe was that telcos and CSPs are actively looking to deploy AI. And they’re asking the hard questions about how to integrate it into their infrastructure at a vast scale.“One of the most interesting things is how telcos are thinking about adopting AI workloads on their infrastructure to deliver low latency. Sovereignty is crucial, especially for customers looking to serve training or inference workloads inside their region. And also user experience: how can I get GPU capacity in clusters, or deliver inference in just a few clicks?”This theme—fast, sovereign, self-service AI—popped up again and again. Telcos and service providers want frictionless deployment and local control.“Companies are struggling most with data”While model deployment and infrastructure strategy took center stage, Seva reminds us that data processing and storage remains the bottleneck. Enterprises know they need to adopt AI, but they’re still navigating where and how to store and process the data that fuels it.“One of the biggest struggles for end customers is the data: where it’s processed, where it’s stored, and what kind of capabilities are available. From a European perspective, we already see more and more companies looking for sovereign data privacy and simple, mature solutions for end users.”That’s a familiar challenge for enterprises operating under GDPR, NIS2, and other compliance frameworks. The new wave of AI infrastructure has to be built for performance and for trust.AI in Europe: responsible, scalable, and localSeva’s key takeaway is that AI in Europe is no longer about catching up, it’s about doing it differently. The questions have changed from “Should we do AI?” to “How do we scale it responsibly, reliably, and locally?”From sovereign deployment to edge-first infrastructure, GTC Europe 2025 showed that inference is the foundation of how European businesses plan to run AI. “The ecosystem is coming together,” explains Seva. “And the next five years will be crucial for defining how AI will work: not just in the cloud, but everywhere.”If you’re looking to reduce latency, cut costs, and stay compliant while deploying AI in production, we invite you to download our free ebook, The inference optimization playbook.Download our free inference optimization playbook
Gcore and Orange Business launch innovation program piloting joint solution to deliver sovereign inference as a service
Gcore and Orange Business have kicked off a strategic co-innovation program with the mission to deliver a scalable, production-grade AI inference service that is sovereign by design. By combining Orange Business’ secure, trusted cloud infrastructure and Gcore’s AI inference private deployment service, the collaboration empowers European enterprises and public sector organizations to run inference workloads at scale, without compromising on latency, control, or compliance.Gcore’s AI inference private deployment service is already live on Orange Business’ Cloud Avenue infrastructure. Selected enterprises across industries are actively testing it in real-world scenarios. These pilot customers are exploring how fast, secure, and compliant inference can accelerate their AI projects, cut deployment times, and reduce infrastructure overhead.The prototype will be demonstrated at NVIDIA GTC Paris, at the Taiga Cloud booth G26. Stop by any time to see it in action.The inference supercycle is underwayBy 2030, inference will comprise 70% of enterprise AI workloads. Telcos are well positioned to lead this shift due to their dense edge presence, licensed national data infrastructure, and long-standing trust relationships.Gcore’s inference solution provides a sovereign, edge-native inference layer. It enables users to serve real-time, GPU-intensive applications like agentic AI, trusted LLMs, computer vision, and predictive analytics, all while staying compliant with Europe’s evolving data and AI governance frameworks.From complexity to three clicksEnterprise AI doesn’t need to be hard. Deploying inference workloads at scale used to demand Kubernetes fluency, large MLOps teams, and costly trial-and-error.Now? It’s just three clicks:Pick a model: Choose from NVIDIA NIMs, open source, or proprietary libraries.Choose a region: Select one of Orange Business’ accredited EU data centers.Deploy: See your workloads go live in under 10 seconds.Enterprises can launch inference projects faster, test ideas more quickly, and deliver production-ready AI services without spending months on ML plumbing.Explore our blog to watch a demo showing how enterprises can deploy inference workloads in just three clicks and ten seconds.Sovereign by designAll model data, logs, and inference results are stored exclusively within Orange Business’ own data centers in France, Germany, Norway, and Sweden. Cross-border data transfer is opt-in only, helping ensure alignment with GDPR, sector-specific regulations, and the forthcoming EU AI Act.This platform is built for trust, transparency, and sovereignty by default. Customers maintain full control over their data, with governance baked into every layer of the deployment.Performance without trade-offsGcore’s AI inference solution avoids the latency spikes, cold starts, and resource waste common in traditional cloud AI setups. Key design features include:Smart GPU routing: Directs each request to the nearest in-region GPU, delivering real-time performance with sub-50ms latency.Pre-loaded models: Reduces cold start delays and improves response times.Secure multi-tenancy: Isolates customer data while maximizing infrastructure efficiency.The result is a production-ready inference platform optimized for both performance and compliance.Powering the future of AI infrastructureThis partnership marks a step forward for Europe’s sovereign AI capabilities. It highlights how telcos can serve as the backbone of next-generation AI infrastructure, hosting, scaling, and securing workloads at the edge.With hundreds of edge POPs, trusted national networks, and deep ties across vertical industries, Orange Business is uniquely positioned to support a broad range of use cases, including real-time customer service AI, fraud detection, healthcare diagnostics, logistics automation, and public sector digital services.What’s next: validating real-world performanceThis phase of the Gcore and Orange Business program is focused on validating the solution through live customer deployments and performance benchmarks. Orange Business will gather feedback from early access customers to shape its future sovereign inference service offering. These insights will drive refinements and shape the roadmap ahead of a full commercial launch planned for later this year.Gcore and Orange Business are committed to delivering a sovereign inference service that meets Europe’s highest standards for speed, simplicity, and trust. This co-innovation program lays the foundation for that future.Ready to discover how Gcore and Orange Business can deliver sovereign inference as a service for your business?Request a preview
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