Technology

Aramco will combine its expertise and intellectual property with Emerson’s advanced corrosion solutions to digitalise and transform corrosion management. (Image source: Emerson)

Emerson has announced it will co-develop next-generation corrosion management solutions for Aramco

Corrosion management is a strategic priority for Aramco, tied directly to operational performance, safety and environmental responsibility. Continuous corrosion monitoring eliminates difficult, inefficient and dangerous manual corrosion measurements and provides a reliable digital data stream for improved decision making.

At the Middle East Metallurgy, Corrosion & Coatings (MECOC) Expo earlier this year, Aramco’s executive vice president of technical services, Wail A Al Jaafari said that Aramco has invested more than US$70mn in corrosion management technologies, achieving over US$770mn in cost savings and avoidance.

“AI-powered solutions are now anticipating corrosion before it happens, leveraging a cast network of IIOT sensors across our facilities and pipelines. These sensors provide more than 10mn corrosion-motoring readings annually across over 40 facilities,” he said.

Aramco’s Hybrid Statistical Corrosion Prediction Model, HySCorr, leverages 20 years’ worth of data, using machine learning and advanced flow and corrosion modelling to produce dynamic, predictive and more accurate monitoring of pipeline health, therefore protecting thousands of kilometres of pipelines.

As part of the corrosion research and development collaboration with Emerson, Aramco will combine its expertise and intellectual property with Emerson’s advanced corrosion solutions to digitalise and transform corrosion management. Emerson will provide its technology leadership in ultrasonic online corrosion monitoring technology; seamless wireless connectivity for corrosion wall thickness monitors, and real-time and continuous data collection to develop a fit-for-purpose corrosion management solution for Aramco processes.

“Emerson, with our complete technology stack, is uniquely positioned to co-innovate the next-generation corrosion monitoring solutions that are cost-effective, scalable and customised for Aramco,” said Ram Krishnan, chief operating officer for Emerson. “We look forward to working with Aramco to develop not only a corrosion solution for its vast operations, but one that will also be a valuable tool for many other industries.”

Professor Michael Wade and Caspar Herzberg, CEO of AVEVA discuss the report findings at AVEVA World 2026. (Image source: Alain Charles Publishing)

A new report from AVEVA, a global leader in industrial software, and the International Institute for Management Development (IMD) discusses what makes digital ecosystems succeed

Based on a global survey of 275 senior business leaders across 12 industry sectors and 19 expert interviews, the inaugural Industrial intelligence Report on Digital Ecosystems and the Future of Connected Industries explores how organisations can harness their industrial intelligence to build, orchestrate and scale business ecosystems that create value, and highlights the main barriers to success.

Increasingly, organisations are seeking to construct digital ecosystems to address business challenges, whether that is innovating faster, navigating supply volatility, or decarbonising complex global operations. Such ecosystems – networks of independent but interdependent organisations that interact through shared digital infrastructure, shared data and co-ordinated decision making – create value that no single organisation could produce alone. Digital ecosystems are delivering measurable operational value in areas such as customer experience, commercialisation speed and ecosystem-wide automation.

Yet, as the research shows, the gap between digital ecosystem ambition and execution remains wide. Where ecosystems are working, companies are realising tangible value through harnessing their industrial intelligence. But the barriers to success remain challenging, spanning the areas of corporate strategy, governance, and technology.

In a fireside chat at AVEVA World in Milan, where the report was launched, AVEVA CEO, Caspar Herzberg spoke about the findings with Michael Wade, director of IMD Global Center for Digital and AI Transformation and Professor of Strategy and Digital, IMD.

Importance of data sharing and good governance

Professor Wade highlighted that the two key factors posing challenges were data sharing and governance, both of which are critical for value to be created, delivered and captured.

While 74% of leaders surveyed consider digital ecosystems a top strategic priority, only 27% report sharing data substantially or extensively with ecosystem partners, and only 9% have achieved joint, integrated cross-organisation data governance.

“The more data was shared, the more value was created, but at the but at the same time, paradoxically, we saw a quite a large reluctance to share data,” Professor Wade said.

Discussing the importance of setting up good governance, he commented, “Poor governance or lack of governance reduces value. Those organisations that had set up strong joint governance celebrated value in their digital ecosystems.” Governance maturity is strongly associated with ecosystem value, the report shows.

Ai is widespread but shallow, according to the findings, with only 3% treating it as a core platform capability. Infrastructure constraints, rather than trust or regulation, represent the main barrier to AI deployment in ecosystems.

Several illustrative case studies also emphasise the gap between ambition and execution: integration complexity, legacy systems and weak governance. Most organisations are investing in digital ecosystem strategy while underinvesting in the operational foundations that make ecosystems work.

The report concludes that organisations most likely to lead the next phase of digital ecosystem development will be those that solve the fundamental problems that currently prevent ecosystems from delivering on their promise: governance structures aligned across partners, deeper data sharing and the capability to collaborate broadly across diverse partner types.

Herzberg explained, “With this collaboration with IMD, our ambition is not merely to understand the motivations behind the move to digital ecosystems, but to define the frameworks, competencies and leadership practices that will concretely enable companies to transcend silos and build more adaptive, ecosystem driven operating models.”

“Governance, integration and learning matter more right now than algorithms. Ecosystems are already delivering operational value. The next phase is about converting that foundation into strategic advantage through better data sharing, coordination, clearer roles and more deliberate leadership... Industrial sectors have decades of experience collaborating out of operational necessity. What is changing is that data, AI and connected platforms are turning those collaborations into real time, intelligence driven systems,” commented Professor Wade.

EZTasks.ai is directly embedded into the EZOps Mobile Oilfield Platform. (Image source: EZOps) (Image source:

Mobile oilfield management platform, EZOps, has launched EZTasks.ai as the first in a series of artificial intelligence-driven offerings that are anticipated throughout the year

EZTasks.ai is directly embedded into the EZOps Mobile Oilfield Platform as an intelligent task-generation feature, which field personnel can use from anywhere, be it in the cab of a truck, at a wellsite, or on a lease road, eliminating the earlier need to be physically present for data entry into EZOps. This means task managers or field technicians can leverage the platform right from the middle of high-activity environments, saving time and eliminating distance factor, and in turn, boosting operational efficiency and production generation.

The feature can be used via any of the three input methods, including voice-to-text, copy & paste or file and image uploads. Users can speak observations, issues or instructions directly into EZOps, which are then interpreted by the AI before it generates suggested tasks. Copy & paste, on the other hand, refers to text from emails, messages, reports or any source that maybe put directly into EZOps. EZTasks.ai is set to extract and structure the input information. Via file & image uploads, users can upload documents, photos, inspection reports, meeting notes or field images. The AI analyses the content and translates it into actionable suggested tasks within the platform.

The AI-driven real-time input methods of EZTasks.ai centralise unstructured data sources such as images, documents, or meeting notes. This makes a marked difference in seamless data entry and boosted data quality, ensuring visibility of critical information.

"Field teams are busier than ever, and the last thing they need is a cumbersome data entry process standing between them and the work at hand. EZTasks.ai meets workers where they are — literally. Whether someone is their truck, at a field location or standing in front of a piece of equipment, they can now capture what they need and let the AI do the administrative work – ultimately creating further operational efficiencies," said Tracy Gray, vice president of EZOps.

Digitalisation and AI will create close to US$500bn in cumulative value for E&P companies between 2026 and 2030. (Image source: Adobe Stock)

Digitalisation and artificial intelligence (AI) will create around US$500bn in cumulative value for E&P companies between 2026 and 2030, according to new analysis from Rystad Energy, creating a huge market for digital solutions

Cost reductions from more efficient operations, production increases from higher uptime and increased recovery, and compressed development timelines contribute to this value creation. Exploration and production (E&P) companies currently investing in digital and AI are expected to capture an additional value of US$80bn per annum in 2030 compared to 2025.

The returns are already visible in the industry, Rystad notes. ADNOC reported US$500mn in AI-driven value already in 2023, and has committed US$1.5bn in digital capital expenditure targeting US$1bn in annual value creation. Norway’s Equinor generated around US$200mn in AI-related savings between 2021 and 2024, and reported US$130mn in 2025 alone.

The US$500bn value creation opportunity in upstream oil and gas encompasses four main workflow categories: asset development, operations and maintenance, exploration and reservoir development, and  drilling, wells and production. Each is at a different stage of digital maturity. Digitalisation within exploration and reservoir development is relatively well established. Operations and maintenance is now seeing more rapid adoption, with predictive maintenance and remote operations delivering cost reductions. Subsurface workflows hold the largest untapped value potential, especially from getting more volumes out of the ground and reducing drilling costs. Some operators have, for instance, compressed seismic interpretation timelines from months to around 10 days.The early adopters of these technologies typically have digitalisation and AI as an integral part of their strategy.

Capturing the value at stake requires investment in digital tools, infrastructure and integration, and E&Ps are estimated to have spent around US$25bn on digital and AI purchases in 2025. The market for providing these tools and services is expected to grow by more than US$10bn by 2030, surpassing US$35bn in total annual market size and approaching US$50bn by 2035.

However, the main barrier to capturing this value is deployment at scale, says Rystad. Partnerships with suppliers and technology experts are increasing to reduce complexity, and simplify integration, typically through platform solutions. Traditional oilfield service (OFS) providers with domain expertise, and technology experts such as integrators or hyperscalers are among the most important partners for E&Ps, with the commercial model shifting from transactional service delivery towards integrated technology partnerships that can leverage an ecosystem of players, platforms and scalable tools.

AI is accelerating the value potential of digital solutions in oil and gas. Despite many breakthroughs, most current AI applications in upstream rely on traditional machine learning models trained on equipment and workflow-specific data, which takes years to accumulate, and models may require significant rework. Newer AI approaches may change this, for instance through agentic AI automating tasks and augmenting humans in a way that breaks down organisational silos and acting as a contextualising layer that functions across varied data types without full retraining.

Rystad puts forward a scenario where AI accelerates the value creation even further, with breakthroughs simplifying integration and compressing adoption timelines. This accelerated AI scenario would also require additional spending on digital solutions, and the value creation gap between early adopters and followers could widen even more.