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For decades, oil has been ��������’s most valuable asset. But as the Kingdom fast-tracks its Vision 2030 goals, a new resource is emerging at the heart of transformation — data.

Raw data, much like crude oil, needs to be refined, processed and leveraged strategically to yield insights. That is where artificial intelligence steps in; not simply as a tool, but as the refiner, architect and the engine of ��������’s post-oil future.

Oil market volatility has long dictated ��������’s economic fortunes. But the uncertainty surrounding global oil demand, price fluctuations and intensifying climate pressures have rendered this model precarious.

Oil prices recently plummeted to $60 per barrel, well below the $90 per barrel needed to balance the Saudi budget, and the Kingdom is feeling the pinch. This has prompted Saudi Aramco to explore asset sales and slash dividend payouts to manage declining revenues.

This situation highlights the financial strain caused by oil price volatility and demonstrates the urgency for economic diversification.

That is why Vision 2030 is more than a road map; it is a race against time. The aim is to build a multi-engine economy driven by tourism, advanced manufacturing, green energy, and above all, data.

If data is the new oil, then AI is the refinery — extracting valuable insights, spotting patterns and driving smarter decisions in real-time. However, this goes beyond analytics; it is about engineering an entirely new operating system for the Kingdom.

Across ��������, invisible AI systems are shaping the visible fabric of development. From intelligent power grids and AI-driven public services to cognitive urban planning in NEOM, AI is embedded in the Kingdom’s critical infrastructure and is constantly refining raw data into actionable insights.

�������� is not just following global AI trends; it is forging its own unique AI landscape. Institutions like the Saudi Data and AI Authority, and initiatives like the National Strategy for Data and AI, are leading the charge in building an ethical, localized foundation of AI innovations, designed to meet the Kingdom’s specific operational and governance needs.

And this shift is not confined to paper strategies; it is being coded into action.

In high-risk industries, AI is not just supporting safety — it is driving it in real-time. On construction sites, PPE detection and work-at-height monitoring ensure on-the-ground compliance, while ergonomics and behavioral monitoring flag fatigue or risky posture before injuries occur.

If data is the new oil, then AI is the refinery — extracting valuable insights, spotting patterns and driving smarter decisions in real-time.

Gary Ng

In oil and gas, AI-enabled smoke and fire detection, access control systems and fleet monitoring help secure hazardous zones, track vehicle efficiency and reduce accidents in volatile environments.

Meanwhile, in manufacturing, intelligent systems streamline floor operations, pinpointing bottlenecks, enforcing safety norms and safeguarding workforce well-being through continuous monitoring. Across these sectors, data informs and makes decisions — instantly and autonomously.

But the momentum does not stop there. Across logistics hubs, warehouses, public infrastructure and even giga-projects like NEOM, these applications are scaling. Whether it is enhancing worker safety in extreme conditions or optimizing equipment performance, AI is shaping how decisions are made.

This shift is subtle, but deeply human. Because it is not just about reducing paperwork or ticking off compliance boxes, but also about preventing loss of life.

In this context, companies like viAct are building solutions tailored to such industrial needs. The scenario-based AI solutions, often integrated with edge devices, AI CCTV and generative AI, help detect safety violations in dynamic jobsite environments, offering nudges toward safer behavior without halting operations.

This shift is not just about platforms or policies; it is about lives on the ground. What happens when a machine-learning model helps a site engineer spot a safety lapse before it becomes a disaster? What changes when AI enables frontline workers to operate more safely in extreme conditions? These are the questions defining the human side of ��������’s AI revolution.

As �������� is trading gigs for algorithms, it is clear that progress will not be measured in barrels, but in bytes. This is more than a digital upgrade — it is a systemic reinvention of how industries operate, grow and protect their people.

And while the scale of this transformation is national, its real power lies in the granular — the engineer who avoids an accident, the factory that adapts in real-time, the city that learns and the workforce that thrives.

The question now is not whether data will drive Vision 2030; it is how that data is refined into meaningful outcomes. The answer lies in technologies that are not just smart, but situational, helping industries make decisions that save time, resources and lives.

• Gary Ng is co-founder and CEO of viAct, a Hong Kong-based startup that uses AI to monitor workplace safety