Tech News
AI-powered personalized learning: The next frontier for Middle East education
By Isil Berkan, Marketing Director, Middle East, Africa & Turkey at Pearson
Artificial intelligence is no longer a distant promise: it’s already reshaping how we live, work, and learn. In the classroom, AI-powered tools are adapting lessons in real-time to each student’s strengths, gaps, and pace. That means less time marking, and more time for teachers to connect, coach, and inspire.
In the Middle East, governments are actively reforming education to build a digital-ready workforce. AI offers a unique opportunity to close skill gaps, increase engagement, and prepare youth not only for today’s jobs but for those yet to come. With thoughtful implementation and the right safeguards, AI-powered learning is reshaping education at an unprecedented scale and speed.
The current state of AI in Middle Eastern education
Across the region, governments are investing significantly in digital transformation in education. In the UAE, AI learning begins from kindergarten, part of its ambition to become a global leader in AI. The country now ranks third globally for attracting AI talent, according to Stanford’s 2024 AI Index report.
Saudi Arabia’s Vision 2030 includes a bold national strategy for data and AI, aiming to position the Kingdom among the world’s top AI-powered economies. Initiatives like “One Million Saudis in AI” and “Artificial Intelligence Hour” are already equipping hundreds of thousands of students with essential skills. Public-private partnerships are accelerating progress, especially in STEM and bilingual education.
Why AI-powered personalized learning is needed
Many traditional classrooms are constrained by fixed curricula and standardized teaching methods. This can make it difficult to meet the needs of individual students. AI can help close the gap—giving every student tailored support based on how they learn best. It doesn’t replace teachers; it gives them better tools to adapt, support, and engage.
The AI in education market is expected to grow to over $20 billion by 2027. Pearson’s own research found that 76% of teachers spend at least an hour a week planning lessons in their own time. This provided inspiration for innovations like our Smart Lesson Generator, which reduces admin and delivers curriculum-aligned content at the right level, in seconds.
Generative AI can identify at-risk learners early, recommend specific interventions, and dynamically adapt materials for better comprehension and retention. These tools tailor content to each learner’s unique needs by offering personalized explanations, summaries, and practice questions.
How it can be implemented and the benefits
AI needs more than access to devices; it works best when integrated into pedagogy. Tools like Mondly by Pearson let learners practise speaking and listening in realistic, role-based scenarios, powered by speech recognition and adaptive feedback.
This kind of real-time assessment is especially valuable for workforce preparation, where language skills, particularly English, directly influence employability. In Saudi Arabia, Pearson’s research shows a 40% gap in English skills across industries, something AI can help address at scale.
Challenges and considerations
In a world where 60% of educators are already implementing AI in the classroom, concerns around data privacy, digital literacy, and equitable access cannot be ignored.
Many schools still lack the infrastructure or teacher training needed to roll out AI programs effectively, with 61% of teachers indicating they would feel more confident using AI if they were properly trained. However, these challenges present opportunities for regional collaboration and innovation. Ethical frameworks, clear data policies, and inclusive curriculum design can mitigate risks.
AI-powered tools that are built on proprietary standards like the Global Scale of English can ensure precision and alignment with real-world learning outcomes. Rather than replacing educators, AI should be positioned as a tool that empowers them, providing real-time assistance during lessons, answering questions, and offering extra resources.
Government initiatives and national strategies
The UAE’s AI Strategy 2031 and Saudi Arabia’s Vision 2030 show a clear commitment to integrating AI across all levels of education. Programs like the King Abdullah Scholarship Program (KASP) are sending students abroad to study advanced technologies, while EdTech partnerships are multiplying across the region.
By 2030, AI is expected to contribute over $96 billion to the UAE’s economy and $135 billion to Saudi Arabia’s. To realise this, education must lead the way.
The road ahead
To make the most of AI in education, we need more than devices and dashboards. We need collaboration.
Educators need hands-on training. Policymakers need to create regulations that promote safe, equitable use of AI. And technology providers must build tools with—not just for—teachers and learners. That includes embedding AI into curricula and teaching the next generation how to use it responsibly.
The Middle East has momentum on its side. If governments, educators, and tech companies act together, the region can set a global example, building an education system that’s more personalised, more agile, and fit for the future.
Tech News
Cloudera and Mistral Partner to Bring Specialized, Sovereign Intelligence to Enterprise Data

Cloudera, the only company bringing AI to data anywhere, and Mistral, a global frontier AI lab, today announced a landmark strategic partnership to bring secure, sovereign AI directly to enterprise data wherever it resides.
Cloudera and Mistral will combine Cloudera’s hybrid data and AI platform with Mistral’s sovereign AI models to give enterprises a secure path to build, customize, and run AI using their own private data. The collaboration will enable organizations to bring intelligence directly to their data across cloud, on-premises, edge, sovereign, and air-gapped environments—without requiring sensitive information to leave their control.
For enterprises managing the world’s largest and most sensitive data estates, this approach provides greater control, choice, and flexibility over how and where AI runs. Organizations can run inference privately, customize AI using proprietary data, and deploy AI applications within their existing security and governance boundaries, while gaining greater control over the economics of AI at scale.
“Enterprise AI is entering a new phase where organizations need more than access to powerful models, they need the freedom to unlock specialized intelligence using their data, on their terms,” said Abhas Ricky, Chief Business Officer & GM, Applied AI at Cloudera. “Together with Mistral, we are giving enterprises the ability to run AI where their data lives, customize it with their own intellectual property, and maintain control over their data, infrastructure, and economics. That combination of intelligence and control is essential to moving AI from experimentation into production.”
Bringing Intelligence to the Data
For enterprises operating in highly regulated and data-intensive industries, moving sensitive or proprietary information to external AI services can introduce regulatory, security, and operational challenges.
Cloudera and Mistral are addressing these challenges by bringing secure, sovereign AI directly to the enterprise data perimeter.
Mistral’s suite of frontier models and tools will be integrated with Cloudera’s hybrid data and AI platform, enabling customers to run their own custom AI models and applications across 30 exabytes of data. Enterprises will have the deployment flexibility across public, private, on-premises, and fully air-gapped environments, while maintaining consistent governance and control over their context.
The partnership will span Mistral’s broad portfolio of frontier AI models and tools, including reasoning, chat, coding, document intelligence, and voice, giving Cloudera customers greater choice in how they apply AI to their enterprise data.
By enabling organizations to run inference within their own environments, the collaboration also gives customers greater flexibility over the economics of AI. Enterprises can choose the deployment model and infrastructure that best fit their workloads rather than depending exclusively on public API consumption models as AI usage scales.
From Private Inference to Proprietary Intelligence
Through the integration of Mistral Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge, organizations utilizing Cloudera’s platform will be able to customize and train models against large volumes of private enterprise data within controlled environments. For enterprises with petabytes of proprietary information, this creates an opportunity to transform decades of institutional data and domain expertise into differentiated AI while maintaining ownership and sovereignty over both the data and resulting intelligence.
Developers and practitioners will also be able to securely build AI-powered experiences using private enterprise data within local environments—from conversational access to governed data to AI-assisted software development and agentic workflows—without exposing sensitive business context or intellectual property to external environments.
Cloudera and Mistral also intend to collaborate on the next generation of AI at the edge, bringing increasingly capable inference closer to where enterprise data is created. This will enable organizations to explore intelligent applications across disconnected, latency-sensitive and resource-constrained environments where relying on centralized cloud infrastructure is not practical.
“Our mission is to make frontier AI available to enterprises without requiring them to give up control over their data, infrastructure, or intellectual property,” said Kamal Brar, SVP of Partnerships and Alliances at Mistral. “Cloudera manages some of the world’s most valuable enterprise data estates, making this partnership a powerful opportunity to bring our technology directly to where that data lives. Together, we can give customers the ability to build AI that reflects their own data and expertise and deploy it securely wherever their business requires.”
Expanding Choice for Enterprise AI
The partnership also expands the Cloudera Enterprise AI Ecosystem, through which Cloudera works with leading AI models, infrastructure, application, and technology providers to give customers flexibility in how they build and deploy enterprise AI.
Mistral adds a significant new dimension to that ecosystem by enabling customers to access and customize its models and AI capabilities directly alongside their governed enterprise data. The partnership reinforces both Cloudera’s and Mistral’s commitment to an open approach to enterprise AI, giving customers choice across models, infrastructure, and deployment environments rather than locking their data or AI strategy into a single technology stack.
The joint Cloudera and Mistral solutions will be available through Cloudera’s enterprise sales team and partner ecosystem, with additional integrations and capabilities rolling out over time.
Spotlight
New Cequence & EMA Research: 94% of Enterprises Trust Their AI Agents Aren’t Over-Provisioned. Only 33% Actually Enforce It.
Nearly every enterprise believes its AI agents are properly scoped. Only a third have actually made sure of it.
Today, new research from Cequence Security, the leader in application, API, and agentic AI protection, and Enterprise Management Associates (EMA) found that 94% of enterprise IT and security leaders are confident their AI agents do not have more access than they need, yet only 33% actually provision agents with least-privilege access. The remaining two-thirds run on broad standing permissions that are reviewed periodically, rarely reviewed, or never reviewed at all.
That gap between confidence and practice is already showing up in production, not a theoretical risk, but as incidents enterprises are living with right now. Among the organizations surveyed:
- 65% have experienced an AI agent take an action outside its intended scope, including 29% with measurable business impact, including data exposure, financial loss, operational disruption, or reputational damage. Another 36% caught a near-miss before it caused damage.

- Only 32% can detect and contain an out-of-scope agent action within minutes through automated means; 55% need hours and manual steps to respond.
- In approximately 4% of organizations surveyed, the first sign of trouble came from a customer or outside partner, not an internal system.
The findings point to one clear story. Governance has not kept pace with the speed of agentic AI deployment, and that gap is showing up at every stage of the agent lifecycle, from how agents are provisioned, to how their actions are authorized, to how they are decommissioned once a pilot ends. Other key findings from the report include:
Enterprises Have Moved Past the Pilot Stage
The scale of deployment makes the gap more urgent. 46% of organizations report they are already scaling agentic AI across multiple departments and production workflows, and 79% are running generative and agentic AI simultaneously. Further, more than 92% report an increase in AI and bot-driven traffic targeting customer-facing applications and APIs.
Authorization is Checked at the Wrong Time, Or Not At All
That governance gap extends to how access is enforced in the moment an agent acts. Only 34% of organizations evaluate an AI agent’s authorization at the moment it attempts a specific action. The majority rely on periodic policy reviews or standing permissions set once at provisioning and never revisited, meaning an agent’s access can quietly outlive the task it was originally granted for, and keep working long after anyone signed off on it.
Abandoned Pilots Are Leaving Live Credentials Behind
Additionally, there’s an increasing risk in how enterprises manage agents that don’t make it to production. 31% of agentic AI pilots have been paused indefinitely, discontinued, or abandoned. Many were real deployments with real system access and credentials that were never cleaned up. Every abandoned pilot with live credentials is exposure nobody is actively watching.
External Connectivity Carries the Same Risk
14% of organizations allow AI agents to connect to outside tools and data sources via the Model Context Protocol (MCP) without restriction. Among the majority who do limit those connections to an approved list, fewer than half, just 49%, have a dedicated team actively maintaining and auditing that list on a regular basis.
Christopher M. Steffen, CISSP, CISA, VP of Research at EMA, said: “This research shows enterprises have moved well past experimentation with agentic AI right into production, and governance has not kept pace with that shift. The gap isn’t a lack of awareness; most organizations have policies in place and express real confidence in them. The gap is between what’s written down and what’s enforced when an agent takes an action nobody approved. That disconnect shows up most clearly in how organizations authorize agent actions and monitor them once they’re live, and it’s the reason incidents are happening at a rate the industry hasn’t fully reckoned with.”
Shreyans Mehta, Co-founder and CTO at Cequence, said: “The number that jumped out to me is the 92% being confident in their governance frameworks. Confidence like that is a trap; it’s exactly why organizations stop looking for problems, stop investing in monitoring, and let authorization checks lapse until an incident forces the conversation. This is the exact blind spot Cequence is built to close, giving security teams real-time visibility into what AI agents are actually doing and enforcing authorization at the moment an agent acts, not after the fact.”
Tech News
Anomali to Address the Next Phase of AI-Led Cyber Defense at GISEC 2026
Anomali, the leading global Managed Intelligence and Agentic SOC platform, announced its participation at GISEC Global 2026, taking place through 16-18 September at Dubai Exhibition Centre (DEC), Expo City.
The company’s discussions at GISEC will center on Autonomous SOC with Governed AI, Agentic AI, Actionable Threat Intelligence and Unified Security Data Lake capabilities that are changing the manner in which security teams investigate threats, manage workflows and make decisions.
Samer Jadallah, Vice President, Middle East & Africa at Anomali, will represent the company at GISEC and will focus on the growing impact of AI on both attackers and defenders, emerging shifts in the threat landscape, including the need to counter CEO impersonation attacks as well as key challenges facing modern security teams. He will also highlight AI’s role is helping organizations respond more effectively to evolving threats, Anomali’s commitment to the region and ongoing product innovation and plans to expand adoption of the Anomali platform across global enterprises and government organizations.
A key focus at this year’s event will be the changing nature of cyberattacks. As threat actors promptly adopt AI to scale campaigns and further accelerate attacks, security operations centers (SOC) are under growing pressure to process rising volumes of alerts with limited resources. To help with this, Anomali will demonstrate how AI can support analysts in multiple ways like surfacing higher- value insights, reducing manual effort and enabling quicker, informed responses.
Visitors can find Anomali at Booth E156 and Booth A80.
- Event: GISEC Global 2026
- Booths: E156 and A80
- Location: Dubai Exhibition Centre (DEC), Expo City
- Dates: 16 th to 18 September 2026
- Time: 9:00 am to 5:00 pm GST
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