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RDI paradigm shifts: how governments can adapt

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Round table diversity meeting

GCC governments are placing Research, Development, and Innovation (RDI) at the heart of national strategy. According to a new report from Boston Consulting Group and Dubai Future Foundation with the World Governments Summit, six RDI paradigm shifts now define the field. The message is clear: adapt policy and engagement, or risk falling behind.

The six RDI paradigm shifts, in plain language

1) Disciplines are blending. Borders between fields are dissolving. Biology meets materials science; data science powers food tech; wearables turn into nutrient-delivering “smart” textiles. Consequently, governments should fund cross-disciplinary teams, not single-track silos. Interdisciplinary grants, co-supervised PhDs, and national priorities that cross ministries all help.

2) AI + big data need safe “playgrounds.” AI accelerates discovery, from virtual experiments to predictive models. Big data multiplies that effect. However, questions around ownership, consent, and privacy demand guardrails. Therefore, create regulatory sandboxes. In these supervised spaces, researchers and startups can test new methods while regulators stress-test policy.

3) Synthetic intelligence is here. Human expertise now pairs with machine computation. This “synthetic talent” changes methods and speed. Accordingly, education policy must add AI literacy across STEM and beyond. Moreover, public funding should back tools that keep sensitive computation local when possible, balancing capability with control.

4) Lab-to-market must move faster—without skipping basics. Pandemic-era vaccine timelines showed what is possible when mature science meets focused translation. Even so, breakthrough speed relied on decades of fundamental research. Hence, governments should provide patient capital for early-stage work and then unlock private funding as projects mature. This cadence protects depth while rewarding delivery.

5) Impact means more than the “impact factor.” Citations matter, yet they miss real-world value. Updated scorecards should include reproducibility, adoption, jobs created, and societal benefit. Additionally, expert panels can complement metrics. When reviewers celebrate learning, not just outcomes, labs take bold shots and share negative results that move fields forward.

6) Access is widening—and narrowing. Cheap tools and open methods democratize discovery. Meanwhile, compute-heavy AI stacks concentrate power. To keep the door open, governments can fund national computing, bridge academy-industry gaps, and build open data repositories. In parallel, incentives for private knowledge-sharing will broaden participation.

Voices from the ecosystem

Khalifa AL Qama of Dubai Future Labs
Khalifa AL Qama of Dubai Future Labs
Maya El Hachem of BCG
Maya El Hachem of BCG

Leaders across Dubai echo the urgency. Maya ElHachem of BCG underscores how AI and big data double research productivity and compress timelines in areas like drug development. Khalifa AlQama of Dubai Future Labs stresses talent, patient capital, and pro-innovation environments. Similarly, BCG’s Anna Flynn points to a future shaped by “synthetic talent,” where students treat AI as a research partner, not just a subject.

Anna Flynn BCG
Anna Flynn BCG

What can governments do next?

Set cross-cutting priorities. Pick missions that require collaboration—food security, resilient health, and sustainable industry. Then align budgets, grants, and procurement around those missions.

Fund the full pipeline. Back curiosity-driven research; support validation; scale pilots through sandboxes; use demand-side tools like challenge prizes and advance market commitments.

Equip the workforce. Update curricula with AI, data governance, and reproducibility. Additionally, reward faculty who co-create with industry while keeping open-science principles.

Invest in shared infrastructure. Provide secure compute, trusted data spaces, and testbeds for cities, factories, and logistics. Consequently, startups and labs build faster with lower cost.

Measure what matters. Report on translation speed, startup formation, public-private projects, and social impact. Publish the lessons. Improve the scorecard each year.

Dubai’s momentum

Dubai has already moved. The Dubai Research, Development, and Innovation Program advances a knowledge-based economy through grants, sandboxes, and targeted fields such as health, cognitive cities, AI, and robotics. As these programs scale, more founders and labs will find a predictable path from idea to impact.

Bottom line

The world’s innovation map is shifting. Governments that embrace these RDI paradigm shifts—and act with focus—will build ecosystems that prove resilient, ethical, and fast. With clear missions, practical sandboxes, AI-ready talent, and fair access to tools, the region can turn research into lasting value for society and the economy.

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Snowflake powers KSA’s Zahid Group’s data and AI transformation to unlock enterprise value

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Zahid Group, one of Saudi Arabia’s leading diversified business groups spanning heavy equipment, energy, transport and manufacturing, and others, has selected Snowflake, the AI Data Cloud company, as the strategic foundation for its enterprise data and AI transformation, giving the Group a scalable way to strengthen governance, advance AI adoption, and elevate customer experiences enterprise-wide. The relationship was formalized during a signing ceremony at Zahid Business Park in Jeddah, launching a multi-year investment that will strengthen productivity and support technology-led growth in line with Saudi Vision 2030.

With Snowflake, Zahid Group’s Digital Solutions Division is unifying data from across its business streams and departments on a governed, secure, centralized and scalable lakehouse platform. A modern business intelligence ecosystem will give leaders faster access to information, enabling them to spend less time reconciling reports and more time acting on insights. The next phase will use Snowflake Cortex AI to enable employees to engage with data through natural language, reducing reliance on traditional reporting and shortening the path from question to decision.

Snowflake’s adoption at Zahid Group comes as Saudi Arabia accelerates its goal of becoming the Middle East’s leading AI infrastructure and technology hub. The Council of Ministers has designated 2026 as the Year of AI, and PwC estimates that AI could contribute around 12.4% of the country’s GDP by 2030.

Before adopting Snowflake, Zahid Group’s data was dispersed across multiple systems, requiring extensive manual consolidation and resulting in reporting inconsistencies that slowed decision-making. As an early proof of value, the Caterpillar Helios initiative demonstrated the power of secure, real-time data sharing through Snowflake. Building on this foundation, Zahid Group is now extending Snowflake’s capabilities across its digital ecosystem, enabling real-time data streaming and integration with core platforms such as Infor and Salesforce.

This connected architecture has standardized critical reporting processes, reducing month-end reporting cycles from days to hours, and in many cases minutes. By eliminating manual effort and improving data consistency, it provides leaders with timely, trusted insights that support faster decision-making and strengthen a culture of data-driven innovation.

Suzan Sadek, Group IT Manager, Zahid Group, said: “Data is one of the most valuable assets of the digital economy. By choosing Snowflake, we are building a trusted and scalable data foundation that enables AI-driven innovation, faster decision-making, and improved customer experience. This transformation strengthens Zahid Group’s competitiveness, while supporting Saudi Arabia’s Vision 2030 ambition to create a data-driven economy.”

Michel Nader, General Manager for the Middle East, Turkey & Africa, Snowflake, said: “Zahid Group is demonstrating how trusted data can become the foundation for enterprise AI at scale. Snowflake brings information closer to customers while providing leading AI capabilities to enable digital transformation across Zahid’s operating environment. We are proud to support the company’s next phase too, where employees can access trusted insights faster and strengthen the Group’s ability to create lasting and scalable value across its businesses.”

Looking ahead, Zahid Group will expand Snowflake’s platform’s role across the Group, extending governed data products, advanced analytics and AI capabilities into more business functions to deliver measurable value for customers, partners and employees.

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PNY Technologies Joins LEAP 2026 with the Latest AI Technologies – Riyadh, Saudi Arabia | 31 August to 3 September | Booth H3-D10

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PNY Technologies announces its participation in LEAP 2026, taking place in Riyadh from 31 August to 3 September, where it will present its latest AI infrastructure and accelerated computing solutions.

The showcase will feature the technologies behind PNY’s AI infrastructure portfolio, from the AI Enterprise Factory to the latest NVIDIA RTX PRO and GeForce graphics solutions, together with networking and infrastructure technologies.

Visitors will also be able to explore the PNY AI Factory Digital Twin Configurator, which allows users to design and configure their own AI factory using digital twins and NVIDIA Omniverse.

PNY will also host live demonstrations developed in collaboration with its technology partners, including SOMOD, DDN, INFINIARC, VERTIV, and F5.

The company’s participation in LEAP 2026 reflects its continued commitment to supporting AI innovation across the Middle East and helping shape the technologies powering the region’s digital transformation.

The PNY team, including regional representatives, will be on-site throughout LEAP 2026 to meet with visitors, partners, and members of the media at Hall H3, Booth D10. Attendees wishing to arrange a briefing or interview are welcome to submit a request below.

Contact request: https://forms.pny.eu/pny-at-leap-2026/

Press contact: sverdier@pny.com / mhamdouche@pny.com

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Globant Introduces Glob.AI, Reinventing Technology Services for the AI Era

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Globant (NYSE: GLOB), a global company focused on driving enterprise reinvention through AI, today introduces Glob.AI, a new AI-native tech services model that fundamentally changes how enterprises access, purchase and deploy AI services. Available online through a self-service model, Glob.AI gives organizations access to enterprise-grade, high quality AI Pods (service units run by a set of AI agents and supervised by humans). Companies are charged for what they produce -per output or per consumption- never per seat or per hour.

“For over 20 years, Globant has stayed ahead of every major technology shift, and AI is no different. Glob.AI is our next step: the one-stop shop where our AI Pods live, each specialized by task and industry. Traditional AI adoption drives token consumption far beyond what efficient output requires, and the real cost is the wasted tokens plus the unstructured, manual supervision of AI. AI Pods introduce a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes, representing the true state of the art of what AI can deliver today,” said Martín Migoya, CEO and co-founder of Globant.

Glob.AI brings together AI-native velocity with Globant’s 23 years of enterprise delivery baked into the governance layer. AI agents do the heavy lifting, with Globant’s experts supervising their outputs and guiding every step. Glob.AI works to standards–documented, tested, secure, built for enterprise scale. It’s the speed AI promises, with the rigor and quality that businesses need, by including:

  • Well-defined, deterministic, and repeatable processes, supervised end to end by experts
  • Optimized AI usage and transparent pricing: customers pay strictly for expert-validated outputs and/or real consumption — not hours, seats, AI hallucinations, retries, or wasted cycles.
  • At least 30% more productive than the typical engineer-plus-AI approach
  • Full AI sovereignty and governance: total flexibility over which models customers use and where they run them, with zero client data ever used to train external models.
  • Token consumption secured in a client’s proprietary Token Vault, providing full traceability and compounding a client’s institutional knowledge over time.

“AI is not just making the same projects faster, it is making thousands of projects viable that never were before,” said Guibert Englebienne, co-founder of Globant. “Until today, enterprises could not buy technology services this way: instantly, transparently, paying only for results. That is the shift Glob.AI delivers, and the strong demand for AI Pods shows enterprises are ready for it.”

Organizations joining the waiting list at Glob.AI will gain early access to a comprehensive catalog of agentic workflows capable of building and deploying solutions for enterprise platforms and specialized industry use cases. The AI Pods in the offering also include partnerships with major organizations including Anthropic, AWS, Vercel, OpenAI, Adobe, Azure, Google Cloud Platform, SAP and Salesforce.

Traditional enterprise tech services require months of discovery, RFPs, and procurement cycles before the work begins. Glob.AI changes that model entirely. Users can log in and immediately start building enterprise grade software. Tech delivery becomes a live, continuous service rather than a fixed-term project — every improvement and release happening on the platform, fully visible to the client, in real time.

Globant released AI Pods in mid-2025, and they are already in use by several Fortune 500 organizations across media, entertainment, professional services, and finance, delivering early results that include:

  • FIFA experiencing a 20% efficiency increase in throughput generation while maintaining or improving quality rates
  • LALIGA deploying AI across key functions in three months
  • YPF reducing contract timelines by up to 40%
  • PharmaMar achieving 15x faster insights in oncology research
  • A leading commercial bank completing a COBOL migration in 2 months versus 14 as projected with a traditional approach
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