How automation and AI are strengthening resilience in the UAE’s energy sector

Emerson executives explain how advanced automation, artificial intelligence and local engineering capabilities are helping the UAE’s energy sector withstand disruption, accelerate recovery and prepare for its next phase of expansion.

The energy industry has traditionally relied on physical redundancy to protect operations against disruption. This includes investing in spare processing trains, additional pipelines and standby equipment that can take over when failures occur. However, building such capacity requires years of investment and billions of dollars, often competing with funding allocated to growth projects.

In the UAE, operators have faced the dual challenge of repairing damaged assets while continuing to deliver new projects, placing additional demands on the same engineering teams and equipment.

Speaking to Gulf News in an exclusive interview, Samer Najm, Strategic Account Director at Emerson Automation Solutions, and Walid Samara, Vice President – Global Projects Pursuit and Strategic Sales, Middle East and Africa, at Emerson, discuss how automation and AI are transforming industrial resilience, why many AI projects have yet to move beyond the pilot stage, and how the UAE’s energy expansion is reshaping expectations of technology providers.

The challenge facing the UAE’s energy industry

Q: The UAE’s energy industry has faced the challenge of repairing damaged assets while continuing to deliver new projects. What lessons has this experience offered about industrial resilience and business continuity?

Samer Najm: The most important lesson is that resilience begins long before a disruption occurs. When it comes to business continuity and recovery, companies develop contingency plans well in advance. This year, many organisations were able to activate those plans when needed.

Readiness is built through years of rehearsed procedures, reliable instrumentation, connected systems, and ensuring that people and spare equipment are readily available.

Facilities with a clear understanding of the extent and nature of damage can plan repairs with greater confidence. Having local engineering teams and service capabilities also significantly reduces the time between identifying a problem and restarting operations.

Once this groundwork is in place, response and recovery become matters of execution.

Q: Traditionally, companies have relied on physical redundancy, including spare equipment and additional production capacity, to protect operations. To what extent can automation and digital technologies provide an alternative?

Walid Samara: Automation and improved operational visibility can deliver some of the resilience traditionally provided by physical redundancy, but only to a certain extent.

They can shorten outages, reduce the time needed to identify and diagnose damage, and enable facilities to continue operating at reduced production levels when necessary. However, they cannot create capacity that does not exist.

There are three key areas where automation makes the greatest difference.

First, detection. Continuous monitoring, alarm rationalisation and advanced process control enable operators to identify faults in minutes rather than over several shifts. They also help teams focus on critical incidents instead of becoming overwhelmed by excessive alarms.

Second, safer access during repairs. Inspection robots can enter hazardous areas before human teams, allowing engineers to assess conditions and understand potential risks before sending personnel into those environments.

Third, maintaining operations when individual units are unavailable. Optimisation software can safely rebalance production, while restart procedures rehearsed by operators on simulators make recovery faster and more predictable.

Ultimately, physical redundancy protects capacity, while automation protects time. During many disruptions, time is what costs the most.

Moving AI from pilot projects to everyday industrial operations

Q: Despite significant investment in digital transformation, many energy companies have struggled to move artificial intelligence from pilot projects into everyday industrial operations. What is holding them back?

Walid Samara: Only a minority of energy and industrial companies are currently using AI to fundamentally change the way they operate. Many have conducted pilot projects, but significantly fewer have managed to scale them across their operations.

The main obstacle is data, not algorithms. Data quality, availability and integration with legacy systems consistently rank among the leading barriers to wider AI adoption.

I would not describe operators as opposed to the technology. In our experience, they are more uncertain about AI than hostile to it. They want to see it deliver tangible results in their own facilities before relying on it in critical operations.

Q: Are ageing industrial facilities and legacy control systems in the region also slowing the adoption of AI?

Samer Najm: Absolutely. Many industrial facilities across the region operate with legacy systems that were never designed for today's levels of digital connectivity or advanced control capabilities. A considerable proportion of this equipment has yet to be upgraded.

This becomes particularly important when operators want to introduce closed-loop control, whereby AI does not simply provide recommendations but directly influences industrial processes.

AI can only act through the instrumentation and control systems already in place. Therefore, the quality and capabilities of the underlying infrastructure are fundamental to successful implementation.

Q: What practical steps should energy companies take to move from AI experimentation to large-scale deployment across their facilities?

Walid Samara: We believe there is a realistic four-stage approach.

First, operators should establish clean, contextualised and reliable data for a limited number of operating units.

Second, they should introduce AI in an advisory capacity, allowing the technology to provide recommendations while human operators retain decision-making authority.

Third, they can move towards bounded closed-loop control within a single operating unit. This should first be thoroughly tested through simulation before being introduced into live operations.

Fourth, successful applications can be replicated across additional units and facilities. However, every AI model must have clear ownership, maintenance arrangements and regular updates to reflect changing operating conditions.

It is also important to recognise that industrial facilities are not identical. Each unit has its own feedstocks, operating conditions and historical performance data. AI models must therefore be adapted to the specific requirements of each site rather than simply transferred from one facility to another.

The operators achieving the greatest returns are those treating AI as an integral part of everyday operations rather than as a standalone technology experiment.

Autonomous robots and the future of industrial operations

Q: Autonomous robots are increasingly being deployed to inspect hazardous industrial areas, while AI-powered control rooms are being tested to manage abnormal operating conditions. How far should the energy industry go in handing operational decisions to autonomous systems?

Walid Samara: Autonomy in live industrial facilities should be introduced gradually and within clearly defined boundaries.

The safety instrumented system and the basic process control layer must remain independent of AI optimisation. This ensures that AI can be overridden or removed without compromising the facility’s fundamental safety protections.

The authority granted to autonomous systems must also remain within the facility’s established operating limits, with clearly defined boundaries that cannot be exceeded and specific conditions under which control must be returned to human operators.

Before deployment, autonomous applications should be validated in simulators against a wide range of abnormal operating scenarios.

AI is particularly well suited to optimisation and decisions involving extensive possibilities and repetitive calculations. However, decisions involving safety-critical operations or unusual process conditions should remain under direct human control.

Q: Does the increasing use of autonomous technologies mean the role of human operators will eventually change fundamentally?

Walid Samara: Yes. The operator’s role is gradually shifting from direct manual control towards supervision. This involves overseeing the entire facility, managing exceptions and determining when human intervention is necessary.

However, this transition also creates an important challenge: the potential erosion of operational skills.

The main risk is skill fade. If operators rarely need to intervene, they may gradually lose the practical experience and hands-on competence required when an automated system fails or encounters an unexpected situation.

For this reason, regular simulator-based training becomes even more important as industrial facilities become increasingly autonomous. Operators must remain fully capable of taking control whenever circumstances demand it.

Q: How is the experience of repairing existing facilities while simultaneously developing new projects changing the expectations of energy companies towards technology providers and industrial suppliers?

Walid Samara: Operators increasingly expect suppliers to have a genuine presence in the country rather than simply selling products and services into the market.

They want local engineering support, readily available inventory, faster delivery times and technical expertise on the ground.

The In-Country Value (ICV) programme, which is now mandatory for national companies, reinforces this requirement. However, customers were already moving in this direction because having suppliers and technical teams close to their operations significantly reduces lead times and improves responsiveness.

The expectation is no longer simply to purchase equipment or technology. It is to establish long-term partnerships with suppliers capable of supporting projects throughout their entire lifecycle.

Where the UAE's next energy investments will go

Q: Looking ahead, which areas of the UAE’s energy industry do you expect to attract the greatest investment, and what role will automation and digital technologies play in these developments?

Walid Samara: We expect the next wave of investment in the UAE to focus on several strategic areas.

These include export infrastructure, particularly expanding pipeline capacity towards Fujairah, as well as upstream development as the country works towards its target of achieving five million barrels per day in oil production capacity.

Gas will also remain a major investment area, encompassing new upstream developments and liquefied natural gas (LNG) projects.

Beyond the traditional energy sector, power generation, water infrastructure and data centres are expanding rapidly. All these industries share a fundamental requirement: continuous, reliable and efficient operations.

Automation, measurement technologies and digital capabilities will therefore need to be integrated into projects from the earliest stages of development.

This is essential not only to protect project delivery schedules but also to ensure that new facilities have the data infrastructure required to operate efficiently from day one.

The opportunity is to build the next generation of industrial facilities with resilience, connectivity and digital intelligence embedded in their foundations.