As the Middle East accelerates its push toward becoming a digital economy, global consumer electronics brands are being forced to rethink their role beyond simply selling devices. For Hisense, that shift is already underway.

From building connected living ecosystems to strengthening regional manufacturing and R&D, the company is positioning itself not just as a technology provider, but as a long-term partner in the region’s transformation.

In this conversation, Jason Ou, President of Hisense Middle East, Africa and India, outlines how localisation, supply chain investments, and a sharper focus on consumer relevance are shaping the company’s next phase of growth in the region—and why the Middle East is emerging as more than just a consumption market.

The region is increasingly positioning itself as a hub for digital economies. How can consumer electronics brands contribute to this broader transformation beyond simply selling devices?

Consumer electronics brands today play a much bigger role than just providing devices. Our real impact comes from shaping how people live in an increasingly digital world. At Hisense, we focus on anticipating consumer shifts and building our innovation around the needs of modern, connected lifestyles. It’s not only about technology, but about how that technology integrates seamlessly into everyday life.

We see this clearly through connected living. A TV today is no longer just a screen, it becomes part of a wider ecosystem, connecting with appliances, enabling intuitive control, and helping consumers manage comfort, energy, and daily routines more efficiently. At the same time, localization is key. Through regional R&D, partnerships, and a stronger presence on the ground, we ensure our innovation is relevant to local lifestyles and market realities. Ultimately, our role is to translate innovation into meaningful, practical value, supporting the region’s digital transformation in a way that is tangible for both consumers and communities.

Technology companies often struggle between being engineering-led and market-led. How does Hisense maintain that balance internally?

For us, it is not a question of choosing between engineering-led or market-led. The strongest companies are built on both, working hand in hand. At Hisense, we combine strong engineering capabilities with a deep understanding of consumer needs and local markets. Our innovation is driven by technology, but always shaped by how people actually live, interact, and use our products. We focus on one simple principle: every innovation must translate into a better user experience. That is where engineering excellence meets real market relevance, allowing us to stay both forward-looking and grounded in consumer value.

You have led Hisense’s expansion in the Middle East through a period of rapid technological change. What leadership principles have helped you balance global innovation with local market realities in this region?

The starting point has always been staying true to Hisense’s vision and values. That gives us a clear direction, especially during periods of rapid change. The second element is people and partnerships. Building the right team on the ground, and working with the right partners, has been essential to understanding the region and executing effectively across markets.

Third is localization with discipline. While we benefit from strong global innovation, success in this region comes from adapting that innovation to local lifestyles, climate, and consumer expectations in a consistent and structured way. And finally, long-term commitment. We have approached the Middle East as a strategic growth market, continuing to invest in technology, operations, and relationships. That long-term view allows us to balance global ambition with local relevance and build sustainable growth over time.

As most global supply chains and manufacturing ecosystems for consumer electronics remain concentrated outside the Middle East, what role do you see the region playing in the future production and innovation landscape of this industry?

I believe the region will play a much bigger role over time, especially as a center for localization, strategic manufacturing, regional distribution, and application-led innovation. We are already seeing that evolve. Hisense has been strengthening its regional manufacturing footprint, including operations in Algeria and Egypt, alongside localized R&D in Dubai. Our recent export milestone from Algeria into Egypt and Tunisia shows that the region is not only a consumption market, but increasingly part of a broader industrial and supply-chain ecosystem.

Going forward, I see the Middle East and wider MENA region becoming more important in three areas: as a faster response hub for regional supply and customization; as a testing ground for technologies suited to local environmental and lifestyle conditions; and as a bridge between global innovation and emerging-market demand. The opportunity is not just to manufacture more, but to shape products and solutions that are more relevant to this part of the world.

If we fast forward ten years, what will the concept of “home entertainment” look like compared to today?

We are currently witnessing a significant wave of innovation, particularly driven by AI capabilities. I believe this will continue to evolve, becoming smarter, more intuitive, and more seamlessly integrated into everyday life. Home entertainment will not only improve in terms of quality, with better visuals, sound, and performance, but it will also become more personalized and adaptive to each user.

At the same time, we will see more robotic and automated technologies becoming part of the home, supporting everyday tasks and enhancing convenience, creating a more connected and intelligent living environment. Ultimately, the experience will shift from simply watching content to enjoying a smarter, more immersive, and fully integrated home experience.

Finally, if you had to describe the next chapter of Hisense in the Middle East in one word, what would it be and why?

Reliable. We aim to become the most reliable brand in the region, in line with our longterm vision. This means continuously strengthening our position across technology development and market penetration, while keeping consumer needs at the center of everything we do. At the same time, we will further invest in localized solutions to ensure our innovation remains relevant, practical, and impactful for the region.

In recent years, Big Ticket has become more than just a raffle, it has gained the reputation of being a brand built around rewarding dreams and celebrating ambition, growing into one of the region’s largest and one of the most anticipated monthly draws in the UAE.

DP World ILT20 – the 34-match cricketing extravaganza – the biggest T20 tournament in the region featuring some of the most renowned global cricket stars is currently being played at the Dubai International Stadium, Zayed Cricket Stadium, Abu Dhabi and Sharjah Cricket Stadium.

DP World ILT20 Head of Partnerships Ishan Chopra: “We are delighted to welcome a UAE born raffle giant like Big Ticket as an Official Partner of the DP World ILT20. Their legacy of helping dreams come true aligns perfectly with our vision of delivering unforgettable, fan-first experiences across the league. This partnership strengthens our commitment to creating moments of excitement both on and off the field, and we look forward to elevating Season 4 together. With a household name like Big Ticket on board, we are confident of unlocking even more opportunities for fans to engage, celebrate and go All In for Cricket.”

Meanwhile, DP World ILT20 match tickets across all categories are available for the remaining tournament matches. Various spectator stand tickets start at AED 20 and hospitality packages start from AED 325. Fans can also book the new Sixes Lounge experience for AED 395, which includes unlimited food and beverages. Tickets can be purchased by visiting tickets.ilt20.ae or Virgin Megastores.

“By tightly integrating SAP and Snowflake, we’re making it simple for enterprises to connect their critical business data with its rich context in SAP with the power of seamless AI app and data agent development at scale in Snowflake,” added Christian Kleinerman, EVP of Product, Snowflake. “Enterprises can now innovate faster with Snowflake and SAP BDC and seamlessly share data between the platforms —zero-copy and fully governed.”

SAP Snowflake brings Snowflake into the open data ecosystem of SAP BDC and the business data fabric–empowering customers with greater openness and choice, while extending SAP BDC with Snowflake’s AI, analytics, data engineering, Marketplace, and collaboration capabilities. Customers can use SAP BDC with SAP Snowflake as a cloud-scale compute and storage option to extend the value of their data. Leveraging bidirectional, zero-copy data access, data and AI teams can work with semantically rich SAP data products in real time, within a unified governance framework. As a result, customers can harmonize SAP and non-SAP data while optimizing total cost of ownership across workloads and build agents and AI applications in SAP Snowflake fueled by trusted SAP data products.

“Bringing Snowflake to SAP Business Data Cloud empowers our customers with openness and choice,” said Irfan Khan, President and Chief Product Officer for SAP Data and Analytics, SAP SE. “Together, we combine SAP’s decades of leadership in mission-critical business applications with Snowflake’s modern data platform to deliver a unified, enterprise-ready, and SAP-supported experience that extends the value of business data across the entire ecosystem.”

With SAP Snowflake, customers can:

• Build a trusted, AI-ready data foundation to harmonize SAP and non-SAP data: Unify their data landscape with an integrated business data fabric—enabling more seamless zero-copy sharing, enriched modeling, and a complete, business-ready view of their data in real time for all data engineering, analytics, and AI and machine learning workflows across the enterprise.
• Accelerate AI business value with semantically rich data: Simplify AI governance, ground AI in organizational knowledge, and build tailored agents—helping to ensure more secure, context-rich, and intelligent applications across the enterprise.
• Develop intelligent applications grounded in mission-critical business data: Build, deploy, and continuously optimize intelligent applications faster with a harmonized and democratized data foundation powered by semantically rich, trusted data products that accelerate the pace of innovation and production.

In addition to SAP Snowflake, the partnership also includes SAP Business Data Cloud Connect for Snowflake, a capability enabling bidirectional, zero copy data sharing with Snowflake. Enterprises already using Snowflake can leverage SAP BDC Connect to integrate their existing instances of Snowflake with SAP Business Data Cloud for more seamless, zero‑copy access, providing Snowflake users with real-time access to semantically rich SAP data products—without duplication.

SAP and Snowflake are supporting thousands of customers, including industry leaders like AstraZeneca, as they transform their industries with this partnership.

“AstraZeneca is constantly pushing the boundaries of science and is pioneering in life-changing medicines,” said Russell Smith, Vice President of ERP Transformation Technology, AstraZeneca. “Data and AI are central to achieving this aim, and our close collaboration with SAP and Snowflake complements our ability to access, process and analyze real-time data. This announcement will accelerate our mission and recognizes that every minute matters to make breakthroughs for patients.”

SAP Snowflake is planned to be generally available in Q1 2026. SAP BDC Connect for Snowflake is planned to be generally available in H1 2026.

The survey highlights that 58% of GCC respondents expressed optimism (up 9 percentage points from 2024) and 45% reported confidence. These figures surpass global averages, indicating a strong regional embrace of AI.

The study, in collaboration with BCG X, BCG’s tech build and design division, included respondents from Kuwait, Qatar, Saudi Arabia, and the UAE, ranging from executive suite leaders to frontline employees. It highlights the region’s rapid advancement in AI adoption, in line with national strategies aimed at digital transformation and economic diversification.

Dr. Lars Littig, Managing Director and Partner at BCG, said:

“The GCC is emerging as a global leader in AI deployment, with high frontline adoption and leadership support nearly twice the global average. For companies and public sector entities alike, this signals a clear mandate: strategic investment in AI, paired with strong leadership and training, offers a blueprint for enterprise-wide transformation.”

The GCC showed a strong adoption in regular AI usage, with 78% of frontline employees using GenAI frequently, 27 percentage points above the global average. Among managers and leaders, usage is even higher, reaching 90% and 92% respectively, compared to global averages of 78% and 88%. This widespread adoption reflects a strong regional commitment to integrating AI into daily workflows.

About 45% of respondents in the GCC found their AI training satisfactory (versus 36% globally), and 54% of frontline employees received clear guidance from leadership (compared to 25% globally). However, this also correlates with a higher risk of “shadow AI” use, with 63% expressing they would use AI tools even if not authorized by the company, compared to 54% globally.

AI is also delivering tangible productivity benefits. Over half (53%) of the report’s respondents save more than an hour daily through AI, with time reallocated to a variety of tasks. These include performing more tasks (58%), working on strategic initiatives (38%), finishing work earlier and with better quality (58%), and pursuing professional development (38%). Others use the time to experiment with GenAI (43%), connect with coworkers (43%), or engage in non-work activities (33%). However, only half receive guidance on how to best use this saved time, which may limit the full impact.

The real transformation lies ahead with two critical developments: agentic AI systems that can operate autonomously to complete complex workflows and make decisions, and the emerging opportunity to invent entirely new business solutions with AI that go beyond efficiency gains to create novel value propositions and revenue models.

“AI is undoubtedly already a powerful driver of performance, which will only get more embedded in organizations, enhancing workflows and how teams operate and collaborate. Indeed, in the GCC, over half of employees are saving more than an hour daily and re-investing that time into strategic initiatives, innovation, and employee well-being. For business leaders, this makes a powerful case for scaling AI not just for efficiency, but for unlocking sustainable growth and talent potential,” added Rami Mourtada, Partner and Director at BCG.

As the GCC continues to lead in GenAI adoption and confidence, the BCG study underscores how strong leadership, effective training, and high awareness are driving productivity and innovation, while also flagging risks like unauthorized AI use. It offers valuable insights for policymakers and business leaders to shape responsible, future-ready AI strategies by benchmarking against global data.

The new leadership structure combines deep local market insight with global brand-building expertise.

Teodora brings extensive experience from iconic Abu Dhabi properties, including The Abu Dhabi EDITION, Marriott Downtown Abu Dhabi, and Aloft Abu Dhabi, applying a strategic and client-centric approach to unlock revenue opportunities across corporate, government, and MICE segments.

Jennifer joins from Germany, where she honed her expertise in brand strategy, digital innovation, and creative storytelling for luxury and lifestyle destinations, bringing a fresh international perspective to the hotel’s marketing and communications strategy.

Together, their complementary strengths in strategic planning, commercial execution, and people-first leadership will be pivotal in enhancing Marriott Al Forsan’s market positioning, driving revenue growth, and delivering elevated guest experiences.

“Strengthening our commercial leadership is central to our strategy of driving sustainable growth and supporting Abu Dhabi’s vision for world-class hospitality,” said Catalina Silvana Susan, General Manager, Marriott Hotel Al Forsan, Abu Dhabi. “Teodora’s deep understanding of the local landscape, combined with Jennifer’s international perspective and innovative marketing approach, creates a powerful synergy. Their leadership will directly contribute to expanding strategic partnerships, increasing market share, and enhancing the hotel’s brand reputation, while supporting the capital’s broader tourism and economic objectives. We look forward to achieving new milestones together.”

This collaboration aims to elevate digital connectivity spanning Europe, North Africa, the Middle East, Gulf Cooperation Council (GCC) countries, and Asia.  Through this agreement, Etihad Salam becomes the primary landing and interconnection hub for the Medusa system within Saudi Arabia through Aqaba (Jordan), solidifying the Kingdom’s position as a pivotal digital gateway connecting Asia, Europe, and Africa.

The partnership introduces resilient, high-bandwidth, and low-latency pathways from the Mediterranean to the Arabian Peninsula, fostering expansion for hyperscale data centers, cloud service providers, and digital operators throughout the region. 

With this partnership, Etihad Salam will deliver terrestrial backhaul services and capacity swapping to seamlessly incorporate Medusa’s network into Saudi Arabia and the broader GCC, and onward to Asia. This initiative represents a significant advancement in Etihad Salam’s global cable strategies and underscores its dedication to Saudi Vision 2030’s goals for digital innovation and economic diversification. 

Medusa Submarine Cable System is an 8,760 km undersea cable network linking critical points in the Mediterranean, such as Spain, France, Italy, Malta, Greece, Cyprus, Morocco, Algeria, Tunisia, Libya and Egypt. Engineered for high-speed, reliable data transfer between Europe, North Africa, and the Middle East, Medusa delivers up to 480 Tbps of capacity, serving as a vital conduit for surging intercontinental data flows. 

Quote from Salam

“Our partnership with Medusa underscores Salam’s commitment to positioning Saudi Arabia as a central hub for regional connectivity,” stated Amjad Arab, Chief Wholesale and Alliances Officer at Etihad Salam. “By linking the Medusa cable to our robust infrastructure, we’re creating innovative international routes that expand our worldwide presence and meet the surging needs for digital and cloud services in the Kingdom. Through this partnership, we seek to offer enriched connectivity services, experiences and bring the world closer, ultimately empowering businesses to scale and innovative in an increasingly digital landscape.” 

Quote from AFR-IX telecom

“We’re excited to collaborate with Etihad Salam, whose expertise and network complement our objective of providing secure, expansive, and high-performance connectivity from the Mediterranean outward,” said Norman Albi, Chief Executive Officer of AFR-IX. “This partnership elevates reliability and coverage for carriers worldwide, driving forward digital advancement across Europe, Africa, and the Middle East.” 

Semantic representations of information are crucial for the functionality of large language models (LLMs), which is fuelling a heightened focus on semantics within data and analytics (D&A) and AI. 

Data silos become entrenched and limit an organization’s capacity to draw insights from its data. Without understanding the relationships within data, the individual pieces of information become less useful.

Semantic approaches facilitate a shared understanding of business terms and their interrelationships, which is vital for providing the necessary context for generative AI (GenAI). In a Gartner survey on the evolution of data management, 44% of the respondents from AI-ready organizations reported that semantic alignment is a key factor in assessing the AI readiness of their data.

D&A leaders can enhance and expand their semantic understanding by leveraging emerging technologies such as knowledge graphs and augmented data catalogs, thereby unlocking greater value from their information resources.

What is Data Semantics?

Data semantics refers to the meaning and interpretation of data within a business-specific context, as opposed to focusing on the physical representation of data through a data dictionary or a business glossary. It involves understanding what a data element represents, how it should be used, and its relationships with other data elements. Without this understanding, data is of limited use for AI use cases.

Semantic modeling is a practice of connecting technical metadata with business metadata.

A business glossary serves as the foundation for all things “semantic,” documenting the meanings of business-related terms. When the semantics and rules of a business glossary are well-understood, it leads to better data quality, easier integration and greater usefulness, supporting interactions with LLMs. The glossary also supports business goals like reducing costs and managing risks by making definitions clear, consistent and easy to trace back to their sources.

Top Recommendations for D&A leaders

• -Upskill your data engineers with semantic modeling techniques such as the use of knowledge graphs in building business ontologies.
• -Introduce DataOps practices to “deliver value from data” more easily, quickly and broadly. Take a people-, product- and governance-centric approach.
• -Invest in converged data management platforms. Establish a platform engineering team that produces platform services for platform tenants.

Key Benefits of Data Semantics

Leveraging and governing semantics effectively enables:

• –Improved Data Understanding: Both people and applications gain a unified view of data and its structure. For example, if several medical e-commerce sites use consistent relationships between terms, applications can extract and aggregate information across these sites to support user queries or serve as input for other applications.
• –Knowledge Reuse: Relationships uncovered by one group can be reused or built upon by others for new use cases, allowing previously identified connections to be embedded in future work.
• –Enhanced Accuracy with LLMs:  Incorporating knowledge graphs into the training and inference processes of LLMs serves as a factual base (i.e., data and metadata source) for mitigating errors and hallucinations.
• –Enhanced Interoperability and Innovation: By adopting semantic modeling, organizations open themselves to a wider range of use cases and enable more effective data interchange.

Link Data from Different Sources to Derive Data Relationships

Semantic reconciliation plays a crucial role in effectively linking data from different sources. It is also essential for inferring relationships between disparate datasets. Without a clear understanding of the relationships, correlations and distinctions among the meanings of data from different modalities such as text, videos, images and structured data, organizations cannot fully realize the potential of their data assets.

Modern semantic tools use algorithms to find connections in data. These tools recommend the best ways to clean, organize and analyze information. They also track where data comes from and how it is used for better governance.

With augmented data discovery, algorithms automatically detect correlations, segments, clusters, outliers and relationships, presenting the most statistically significant and relevant results. By using these semantic approaches, organizations can connect information from different sources, uncover relationships and gain valuable insights that drive better decisions.

In business ecosystems, the degree of openness is driven by members’ strategies, common goals and shared interests. For example, governments, nongovernmental organizations, charities and community groups can collaborate on health or public policy issues, or in open-source developer communities. This creates an opportunity for exploiting the knowledge of data and the meaning of data in terms of what can be applied to several digital business moments.

Lastly Think Data Semantics Before Introducing Large Language Models

Organizations are spearheading transformative initiatives to implement large language models in order to transform their operations. However, data and analytics leaders often rush to integrate LLM capabilities without first ensuring these tools are aligned with real business outcomes. To maximize value, it’s essential to connect LLMs with robust semantic frameworks.

Knowledge graphs are a powerful foundation for leveraging LLMs in business contexts. These machine-readable data structures capture semantic knowledge about both physical and digital entities. These worlds include entities and their relationships, which adhere to a network of nodes and links forming the graph data model.

LLMs can streamline the creation of ontologies, which define categories and relationships within data. By using “few-shot” learning prompts—providing just a handful of examples—users can guide LLMs to generate base ontologies in open formats that suit their needs. These initial frameworks can then be refined for greater detail as required.

Additionally, LLMs support ontology mapping by helping users align entities and relationships across different datasets or systems. With targeted prompts and sample mappings, organizations can extract relevant connections from their data and improve accuracy through iterative refinement.

By adopting large language models alongside semantic representations like knowledge graphs and ontologies, organizations position themselves for faster deployment of advanced analytics solutions that deliver meaningful business value.

Check out our previous post NMK Interactive 2025 Sets New Middle East AV Benchmark

A New Approach to Industrial AI

At the heart of the collaboration lies Nybl’s n.vision platform, now combined with IBM’s WatsonX AI and governance capabilities. Together with IBM Maximo, the platform equips enterprises with secure and intelligent asset management. As a result, companies can reduce costs, increase reliability, and improve safety outcomes while maintaining compliance with international standards.

IBM’s Watsonx.Governance provides transparency, lifecycle management, and regulatory alignment, ensuring that AI adoption remains both responsible and effective. Meanwhile, Nybl brings deep sector knowledge, making the solutions highly adaptable to the complex needs of industries such as energy, water, and utilities.

Visual Intelligence in Action

A key component of the new solution is IBM Maximo Visual Inspection (MVI). When combined with Nybl’s n.vision, the platform analyzes large volumes of imagery from drones and cameras. Consequently, organizations can detect faults earlier, predict equipment failures, and recommend prescriptive actions that minimize downtime.

By automating quality checks and defect detection, the approach not only enhances safety but also streamlines workflows. Furthermore, it ensures that industries can uphold high operational standards without overburdening their teams.

Empowering Smarter Decisions

The collaboration also introduces two powerful modules within the NYBL ecosystem. Director powers real-time analytics and decision-making, while Stage provides intuitive visualizations for rapid response. Together, these tools enable leaders to make smarter operational choices and drive efficiency at scale.

According to IBM, this partnership reflects its vision for the future of enterprise AI. “At IBM, we believe the future of industry is AI-powered,” said Zaidoun Arbad, VP – Ecosystem, IBM Middle East and Africa. “By combining Nybl’s domain-specific innovation with IBM’s enterprise capabilities, we are enabling clients to transform operations and make smarter decisions in real time.”

Building AI with Purpose

For NYBL, the collaboration amplifies its mission to build AI grounded in science and ethics. Noor Alnahhas, Founder and CEO of NYBL, explained: “Our mission is to solve critical challenges across energy, agriculture, healthcare, and beyond. This partnership with IBM significantly scales our ability to deliver measurable impact while exporting innovation from the Middle East to the world.”

By focusing on purposeful AI, the partnership ensures that industrial innovation is not just efficient but also sustainable. Moreover, it highlights the importance of ethical AI development, with Alnahhas serving as a member of Dubai’s AI and Ethics Advisory Board.

Strengthening Global Technology Leadership

The agreement also allows IBM to integrate nybl’s innovations into its global portfolio, while supporting nybl’s ambition to position Middle Eastern technology on the world stage. Consequently, this collaboration strengthens the region’s influence in shaping the future of industrial AI.

Together, the two companies are creating an ecosystem where advanced, purpose-built AI drives real-world improvements. Whether preventing equipment failure, optimizing workflows, or enhancing safety, the combined capabilities of IBM Nybl AI solutions deliver measurable business value.

Looking Ahead

As industries worldwide face rising demand, increasing complexity, and tighter sustainability targets, AI-driven solutions are becoming indispensable. With this collaboration, IBM and NYBL demonstrate how trusted platforms like watsonx and Maximo can be combined with local innovation to create powerful, globally scalable solutions.

The launch in Dubai also reflects a growing trend: Middle Eastern companies are no longer just adopters of global technologies but exporters of innovation that impacts industries worldwide. With IBM Nybl AI solutions, the future of industrial operations looks not only smarter but also more resilient and ethical.

Check out our previous post on Thriwe Aina Launches in UAE to Redefine Customer Loyalty

The UAE has become the launchpad for Thriwe Aina, a next-generation AI concierge designed to transform customer loyalty. Announced in Dubai, this launch marks a major step in Thriwe’s journey as it pivots from a service-driven provider to a technology-first innovator. With Aina, the company aims to deliver loyalty programs that go beyond transactions and create meaningful, intelligent lifestyle experiences.

Why the UAE Was Chosen

The UAE continues to stand out as one of the world’s fastest-growing centers for artificial intelligence. Recent studies predict the country will rank third globally, behind only China and the United States, in AI’s economic contribution. Therefore, it is no surprise that Thriwe selected the UAE as the first market to debut its new concierge. By launching Aina here, Thriwe reinforces the nation’s role as a global hub for innovation and digital transformation.

Dhruv Verma, CEO and Founder of Thriwe, emphasized the importance of the move:
“Exceptional experiences build lasting loyalty. With Thriwe Aina, we’re not just enhancing engagement but redefining how loyalty is delivered in the digital age.”

What Sets Thriwe Aina Apart

Unlike traditional loyalty programs that focus on points or discounts, Thriwe Aina leverages AI to deliver seamless and inclusive concierge services. Moreover, businesses can integrate the platform quickly with their existing systems, minimizing disruption. In addition, it reduces operational costs while creating smarter, data-driven recommendations that anticipate customer needs.

For customers, Aina provides instant assistance, personalized suggestions, and natural multilingual conversations. Consequently, interactions feel effortless, relevant, and human, no matter the market.

The Future of Loyalty is Intelligent

The launch also signals a broader shift across the loyalty landscape. Businesses now need platforms that combine efficiency with personalization. Furthermore, AI enables companies to reduce their reliance on manual systems while increasing the quality of customer engagement.

“Launching first in the UAE reflects our confidence in this market as a global innovation hub,” Verma said. “Thriwe Aina sets a new benchmark for how loyalty can be seamless, intelligent, and inclusive.”

Delivering Measurable Impact

For businesses, Thriwe Aina creates tangible results:

• -Faster adoption with minimal operational disruption.
• -Automated query handling that reduces costs.
• -Data-driven insights that improve customer retention.

For customers, the platform becomes a trusted digital companion:

• Providing 24/7 personalized support.
• Anticipating preferences through intelligent recommendations.
• Enabling inclusive access through multilingual features.

As a result, loyalty becomes less about transactions and more about building long-term relationships.

Looking Toward Global Expansion

The debut of Thriwe Aina in the UAE is just the beginning. Entering the final quarter of 2025, Thriwe plans to expand its AI-driven ecosystem through strategic partnerships, customized offerings, and continued investment in machine learning. Meanwhile, the company is positioning itself as a leader in hyper-personalized loyalty solutions.

The UAE’s environment — one that blends bold digital infrastructure with forward-looking regulation — provides the perfect foundation for this journey. Therefore, Aina’s launch in Dubai represents more than a local milestone. It positions Thriwe as a global innovator, ready to redefine loyalty for the next decade.

Read our previous post, Check Point Wiz Partnership Delivers Unified Cloud Security

A quick reality check on market size so we’re not drinking our own Kool-Aid: the global AI market in 2025 is roughly $300–$400B, depending on scope (software vs. software + services + hardware). Reasonable consensus ranges put 2030 at ~$0.8–$1.6T. In other words, still early—but already too big to treat as a side project.

ASUS: PUT AI ON THE ENDPOINT—AND MAKE IT GOVERNABLE

ASUS’s enterprise stance is disarmingly practical. As Mohit Bector, Commercial Head (UAE & GCC) at ASUS Business, framed it, the fastest way to make AI useful is to put it where the work happens (the endpoint) and to make it governable. Concretely, that means:

• NPUs for on-device inference (privacy, latency, battery life).
• Manageability (fleet policy, remote control, security posture you can actually audit).
• Longevity (multi-year BIOS/driver support) so IT can set an AI-ready baseline and keep it stable.

ASUS thinks about the modern workplace as an Enter → Analyse → Decide loop, this is where the workday actually speeds up—quietly, relentlessly, at the endpoint:

• Enter: the device captures signals—voice, docs, screens, forms, sensors.
• Analyse: retrieval-augmented reasoning + analytics produce options, risks, and rationales.
• Decide: humans choose; agents act—raise tickets, update ERP/CRM—with audit trails.

It isn’t about one blockbuster use case. It’s about standardizing the canvas, so small wins compound every week.

INTEL: FROM SLOGAN TO STACK (AND WHY THE AI PC MATTERS)

Intel’s deck made the “every company will be an AI company” claim implementable. Four slide-level words—Open, Innovative, Efficient, Secure—double as a buyer checklist:

• Open: less cost, no lock-in. The same models should move across CPU/GPU/NPU and PC → Edge → Datacentre/Cloud without rewrites.
• Innovation: treat AI PCs with NPUs, edge systems, and cloud clusters as one continuum.
• Efficient: lead on performance per dollar and per watt; energy and cost are first-class design goals.
• Secure: your data and your models are IP; run locally when you should, govern tightly when you don’t.

A “Power of Intel Inside” platform slide stitched this together:

• AI software & services: OpenVINO as the portability layer to convert/optimize/run models across heterogeneous silicon.
• AI PC: always-on, private inference for day-to-day assistants.
• Edge AI: near-machine intelligence for vision and time-series use cases.
• Datacentre & cloud AI: scale-out training/heavy inference (fraud graphs, multimodal analytics, enterprise RAG).
• AI networking: the fabric that keeps it all moving—securely.

Why the fuss about the AI PC? Because it’s the next enterprise inflection after Windows and Wi-Fi. Slides mapped tangible outcomes:

• Productivity: faster info-find, auto-drafts, note-taking.
• Communication: translation, live captioning, dictation, transcription.
• Collaboration: smart framing, background removal, eye tracking, noise suppression—without pegging the CPU.
• IT operations: endpoint anomaly detection, VDI super-resolution, remote screen/data removal.
• Security: client-side deepfake detection, anti-phishing, ransomware flags.

Under the hood, Intel’s definition is a division of labour: CPU for responsiveness and orchestration, GPU for high-throughput math/creation, NPU for low-power sustained inference—the always-on stuff that makes assistants truly useful. Add vPro + Core Ultra and you get the fleet controls and long-term stability IT actually needs.

One more practical bit I liked: Intel AI Assistant Builder—a portal to stand up local assistants/agents (with RAG) that can run on the PC fleet first, shrinking time-to-value from months to days/weeks and letting you prove the full E-A-D loop before you scale heavier jobs to edge/cloud.

When the “100M AI PCs by 2026” slide hit the screen, heads tilted from curiosity to calculation. The figures—bullish vendor projections (~100M by 2026; ~80% AI-capable by 2028)—invite a haircut, but the signal is unmistakable: endpoint AI is becoming the default.

WHAT THE PANELLISTS REALLY TAUGHT US

RAKEZ (Free Trade Zone)

Posture: Execution-first. Make AI practical on the shop floor and trustworthy in the back office—governed from day one.

What they drive:

• Diagnostics (OEE baselines, defect maps) + data-readiness scans (MES/ERP) so pilots don’t stall.
• Reference lines/sandboxes where vendors prove accuracy, safety, throughput before purchase.
• Template playbooks: CV-QC, predictive maintenance, warehouse vision, invoice extraction/3-way match—each with SOPs, KPIs, integration steps.
• Curated vendors + shared services (labelling, model hosting/monitoring, SOC for AI) to reduce MSME cost/complexity.

MSMEs: “Bookkeeping-in-a-box” to clean ledgers and free cash; pre-negotiated PoC packs (fixed price/timeline, acceptance metrics); compliance starter kit (consent, retention, safety, escalation).

Enterprises: Multi-site rollout playbooks, edge + cloud reference architectures (identity-aware RAG, policy-constrained agents), and assurance artifacts (model cards, change control, audit trails).

Outcome lens: OEE ↑, FPY ↑/DPMO ↓, MTBF ↑/MTTR ↓, faster close cycles, fewer incidents—AI that moves the P&L and passes audit.

Note – FPY — First Pass Yield; OEE — Overall Equipment Effectiveness; DPMO — Defects Per Million Opportunities; MTBF — Mean Time Between Failures (repairable systems); MTTR — Mean Time To Repair

Oracle (Consulting / Applications cloud)

Posture: AI belongs inside the workflows where finance, HR, supply chain, and service teams live. Expect talk tracks like: ground answers in your own records (RAG with policy), instrument before/after outcomes, and treat AI features as part of ERP/HCM/CX—not a sidecar chatbot. The ask from buyers: prove the Enter → Analyse → Decide gains in real workflows (FP&A forecasting lift, supplier risk scoring, HR talent match quality).

Zurich Insurance (BFSI)
Posture: AI as a force for good, scaled with governance. Think hundreds of use cases: claims triage, fraud/anomaly detection, internal knowledge bots—human-in-the-loop where stakes are high, and IoT-style prevention to reward good behaviour. The key is measurement: fewer false positives, shorter cycle times, clearer audit trails—and elevated roles, not replaced ones.

Group-IB (Cyber / Threat Intel)

Posture: AI to defend—and defend against AI. SOC copilots that summarize and enrich alerts, deepfake/phishing detection, behaviour analytics across identities and endpoints, and the emerging discipline of security of AI (prompt-injection defences, LLM gatewaying, data loss controls for AI apps). If you’re rolling out agents, involve your security team early.

Dhruva Consultants (Tax Tech Transformation)

Posture: RegTech + AI to reduce compliance cost and risk. Document AI to normalize invoices/contracts, anomaly detection for mismatches and fraud flags, and a pragmatic “bookkeeping-in-a-box” on-ramp for MSMEs. Non-negotiables: auditability, versioning, segregation of duties for anything that touches filings.

Prime Group (Labs/Certification)

Posture: Risk-scored processes—every lab step tagged with expected outputs, data access, and fallbacks. Near-term wins: smarter scheduling and test selection; long-term horizon: a Mars-ready lab by 2050 aligned with the UAE’s space ambitions. It’s operational excellence today, exploration mindset tomorrow.

Education (Heriot-Watt University, Dubai)

Posture: candid and useful: human-led pedagogy; AI-assisted admin and decision support. HWU brings talent pipelines (AI/Data Science programs), translational research, and applied robotics capacity (think Robotarium-style ecosystems). This is the repeatable talent + research engine enterprises can plug into—capstones, CPD, joint R&D—that shortens the path from idea to pilot.

WHY UAE HAS A STRUCTURAL ADVANTAGE: RAKEZ × HWU

Local context matters. RAKEZ (Ras Al Khaimah Economic Zone) is more than a location; it’s an adoption on-ramp aligned with MoIAT’s Industry 4.0 programs (ITTI/Transform 4.0). Translation: factories—especially MSMEs—get real help to deploy vision-led quality, OEE analytics, and worker-safety use cases, with policy scaffolding and incentives attached.

Pair that with Heriot-Watt University as a talent/research flywheel and you have a short, well-lit path from concept to production: execution zone + skills engine. That’s a genuine regional edge.

SUMMARY

Techsphere’s most important contribution wasn’t a prediction; it was a design pattern. ASUS gives you the enterprise substrate (AI-ready endpoints you can actually govern). Intel gives you the principles and plumbing (OpenVINO portability; CPU/GPU/NPU continuum; PC → Edge → Cloud). The panellists supplied proof patterns across industries. And the UAE context—RAKEZ for execution, HWU for talent/research—shortens the distance from idea to impact.

If “every company will be an AI company,” the winners won’t be the first to demo—they’ll be the first to standardize. Start at the endpoint, insist on portability, manage a portfolio, and make the Enter → Analyse → Decide loop measurable. That’s how the slide turns into the balance sheet.

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• Glossary of Technical Acronyms
• OEE — Overall Equipment Effectiveness (measures manufacturing productivity: availability × performance × quality).
• FPY — First Pass Yield (percentage of units passing production without rework).
• DPMO — Defects Per Million Opportunities (defect rate in Six Sigma terms).
• MTBF — Mean Time Between Failures (average time between breakdowns of a repairable system).
• MTTR — Mean Time To Repair (average time to repair a failed component/system).
• AI / IT Terms
• NPU — Neural Processing Unit (specialized chip for AI inference, optimized for low-power sustained workloads).
• CPU — Central Processing Unit (general-purpose processor for orchestration, responsiveness).
• GPU — Graphics Processing Unit (parallel processor for high-throughput math and AI training/inference).
• RAG — Retrieval-Augmented Generation (technique where AI models query external knowledge bases before generating answers).
• ERP — Enterprise Resource Planning (integrated system for core business processes like finance, supply chain, manufacturing).
• MES — Manufacturing Execution System (software for monitoring and controlling production).
• VDI — Virtual Desktop Infrastructure (running desktop environments on centralized servers).
• SOC — Security Operations Center (hub for cybersecurity monitoring and response).
• IP — Intellectual Property (protected data, models, or designs).
• Industry & Enterprise Acronyms
• BFSI — Banking, Financial Services, and Insurance (industry vertical).
• FP&A — Financial Planning & Analysis (finance function for budgeting, forecasting, performance analysis).
• HCM — Human Capital Management (HR technology and processes).
• CX — Customer Experience (customer-facing processes and software).
• ITTI — Industrial Technology Transformation Index (UAE Ministry of Industry and Advanced Technology initiative under Industry 4.0).
  
  

The ASUS Techsphere Forum, organized by Integrator Media, brought together C-suite leaders from diverse industry verticals to explore how evolving hardware standards are shaping the future of work. The event highlighted the growing role of AI-enabled PCs, showing how advancements in endpoint hardware can directly support business needs. By balancing industry-specific requirements with insights on hardware innovation, the forum offered executives a clear view of how these technologies can enhance productivity and deliver measurable value across the wider business community.