In its recent white paper, The State of Global Sustainability Disclosures, Sprih Inc. analysed more than 200,000 reports from over 80,000 companies worldwide, creating one of the largest repositories of corporate sustainability data ever assembled. The findings show that sustainability reporting is no longer a fringe exercise.Yet comparability and consistency remain mainly out of reach for many businesses. 

According to Sprih, this is where artificial intelligence must move from being a reporting tool to becoming the backbone of ESG intelligence.

Increasing visibility

The white paper, powered by SustainSense, Sprih’s climate AI engine, reveals a paradox. Disclosure rates for Scope 1 and Scope 2 emissions are relatively mature across many regions and sectors and near-term targets are widely adopted. Energy consumption is commonly reported in aggregate.

Yet when we move beyond headline figures, fragmentation becomes obvious.

Scope 3 emissions, which are often the largest share of a company’s footprint, remain inconsistently disclosed. Water reuse and rainwater harvesting data are scarce and waste categorisation varies widely. Smaller firms, particularly those under US$100mn in revenue, lag significantly in both completeness and consistency.

The paper explains that without standardisation, sustainability disclosures risk becoming a patchwork of narratives rather than a coherent dataset. This makes investors struggle to benchmark risk, while regulators face uneven compliance landscapes. Moreover, procurement leaders lack visibility across supply chains and executives are left navigating strategy with incomplete maps.

But AI can help change this equation.

Teaching machines the language of sustainability

One of the most powerful insights from the white paper is methodological. SustainSense does not merely collect documents; it extracts, classifies, validates and normalises data across languages, formats and reporting frameworks. In other words, it teaches machines to understand sustainability.

This matters because ESG data is not structured by default. It sits inside PDFs, integrated annual reports, regulatory filings and standalone sustainability documents. Terminology can differ across jurisdictions and definitions evolve. Units can vary and even the placement of data within reports is inconsistent.

Agentic AI architectures, as described in the paper, create a structured layer on top of this chaos. They identify emissions figures, distinguish between location-based and market-based Scope 2 data, harmonise water metrics and align targets to recognised definitions such as near-term, long-term and net zero.

The result is not just a larger dataset, but a comparable one.

When thousands of disclosures are translated into a common analytical framework, patterns emerge. Europe’s leadership in comprehensive target-setting becomes quantifiable. Asia’s relative lag in Scope 3 transparency becomes measurable. The maturity gradient between large enterprises and SMEs becomes visible at scale.

According to Sprih, this is not anecdotal ESG, but rather "it is systemic ESG intelligence."

A strategic asset

For many companies, sustainability reporting continues to feel like a compliance obligation. But the white paper offers some hope. 

Executives can use AI-driven benchmarking to understand where their disclosure quality signals strength – or exposes weakness. Investors can assess governance resilience by examining not just target announcements, but the consistency of underlying metrics. Regulators can identify sectors where harmonisation efforts must intensify.

Crucially, AI can also surface blind spots. The analysis shows that while total energy consumption is widely reported, the breakdown between renewable and non-renewable energy is less consistent. Water withdrawal is commonly disclosed, but treatment and reuse metrics are rare. Waste generation is more visible than circularity performance.

These gaps, it seems, are not simply technical. They represent risk. In a climate-constrained world, incomplete value-chain data or poor resource visibility translates into financial exposure. AI could help transform ESG into static into dynamic risk management.

Better AI systems

Perhaps the most compelling idea in the white paper is the call for a global climate intelligence layer. If corporate disclosures are the raw material, AI is the infrastructure that makes them usable.

Imagine a landscape where investors can benchmark Scope 3 intensity across sectors in seconds; where procurement teams can map supplier emissions maturity; where policymakers can evaluate regional adoption of net-zero commitments with precision rather than estimates. Sprih says that this is not speculative, as it is already emerging. 

However, the technology community must recognise that scale alone is insufficient. AI systems must be transparent, auditable and continuously learning. They must adapt as reporting frameworks evolve and new regulatory requirements emerge. They must balance automation with validation to ensure trust.

Equally, companies must view AI not as a shortcut to green credentials, but as a tool for accountability. The question for the market is no longer whether AI will shape ESG. It is whether organisations are ready to operate in a world where sustainability performance is no longer hidden in footnotes, but illuminated by intelligence at scale.

The Middle East and North Africa (MENA) is set to become the world’s largest hydrogen exporter by 2060, while maintaining a dominant position in global oil and gas markets, according to DNV’s Oil & Gas Decarbonization in the Gulf Region report

The report highlights how Gulf Cooperation Council (GCC) countries are cutting the emissions intensity of their core oil and gas production while continuing to play a central role in global energy supply, presenting a picture of a region approaching the energy transition from a position of confidence and capital strength. Reductions in emissions intensity are occurring alongside continued hydrocarbon production and investment across renewables, electrification, hydrogen, methane abatement, digitalisation, and carbon capture.

Since 2005, the GCC has produced nearly 18% of global oil and gas, a share expected to increase as investment continues in low-cost, advantaged resources. As global energy demand increasingly shifts toward Asia, the region’s location and cost competitiveness strengthen its position as a preferred supplier. At the same time, decarbonization measures are becoming an integral part of long-term competitiveness.

“The global energy transition will not progress at the same pace across regions, nor will it follow a single pathway,” said Brice Le Gallo, vice-president & regional director for Southern Europe, MEA & LATAM, Energy Systems at DNV. “In the Middle East, oil and gas remain central to economic stability and global energy security. The key challenge is to reduce their emissions footprint while accelerating investment in the technologies needed for a lower-carbon energy system.”

Electrification is being used to cut Scope 2 emissions from pumps, compressors, and offshore facilities, through grid connections, renewable power, and hybrid solutions. These efforts are supported by energy-efficiency measures and the use of digital tools and artificial intelligence to optimise drilling, reservoir management, and asset operations, reducing energy intensity and emissions per barrel produced.

Methane reduction remains one of the most immediate and cost-effective options for lowering emissions. Across the GCC, routine flaring is planned to be phased out by 2030 and leak detection and repair (LDAR) programmes are increasingly standard. National oil companies are also aligning with international methane initiatives, enabling continued production growth while reducing methane intensity in line with national net-zero targets.

GCC countries are realigning domestic energy systems to reduce oil and gas use domestically and free up volumes for export and low-carbon fuel production. Growth in renewables, electrification of transport and buildings, and efficiency gains are driving this shift. Investment in downstream industries, petrochemicals, and low-carbon fuels is also changing export profiles, moving beyond crude oil toward higher-value and lower-carbon energy products.

With access to low-cost natural gas, strong solar resources, and established industrial and export infrastructure, the region is well placed to scale both low-carbon hydrogen (produced from natural gas with carbon capture) and renewable hydrogen produced through electrolysis. By 2060, the Middle-East and North Africa region is projected to produce around 19 million tonnes of hydrogen and 13 million tonnes of ammonia per year, exporting about 50%, mainly toward Europe and advanced Asian economies.

“Hydrogen, ammonia, and carbon capture are becoming core elements of the GCC’s energy export model,” said Jan Zschommler, market area manager for the Middle East, Energy Systems at DNV. “As emissions requirements tighten, access to international markets will increasingly depend on carbon intensity. Integrating hydrogen production with renewable power, carbon capture, and existing industrial clusters allows the region to remain competitive while meeting these requirements.”

Carbon capture, utilization and storage (CCUS) is also set to grow. In January 2026, the UAE's Supreme Council for Financial and Economic Affairs has introduced Carbon Capture Policy as a further commitment to meeting their carbon reduction targets. Captured CO₂ volumes (including CO₂ removal) are expected to reach around 250 million tonnes per year by 2060, equivalent to roughly 8% of regional energy-related and industrial emissions.

Bioenergy with carbon capture (BECCS) and direct air capture (DAC) combined are expected to remove around 81 million tonnes of CO₂ per year by 2060, helping to offset emissions from sectors that are more difficult to decarbonise.

The full report is available at https://www.dnv.com/energy-transition-outlook/oil-and-gas-decarbonization-in-the-gulf-region/

Vertiv unveils Next Predict, an AI-powered service that predicts and prevents data centre risks before they arise. (Image source: Vertiv)

Vertiv has launched Vertiv Next Predict, an AI-powered managed service designed to revolutionise data centre maintenance

Moving beyond traditional time-based and reactive approaches, the service industrialises operations by analysing asset behaviour before risks occur. Next Predict represents the latest enhancement in Vertiv’s integrated AI infrastructure portfolio, providing predictive intelligence across power, cooling, and IT systems to establish a unified, resilient foundation for AI-driven data centres.

As AI workloads transform the data centre environment, facilities require greater visibility and control over critical infrastructure to ensure continuous performance at scale. By adopting advanced analytics and predictive maintenance strategies, organisations can proactively address these challenges and maintain reliable operations across distributed environments.

“Data centre operators need innovative technologies to stay ahead of potential risks, as compute intensity rises and infrastructures evolve,” said Ryan Jarvis, vice president of the global services business unit at Vertiv.

“Vertiv Next Predict helps data centres unlock uptime, shifting maintenance from traditional calendar-based routines to a proactive, data-driven strategy. We move from assumptions to informed decisions, by continuously monitoring equipment condition and enabling risk mitigation before potential impacts to operations.”

Vertiv Next Predict uses AI-based anomaly detection to continuously monitor operating conditions and identify deviations from expected behaviour at an early stage. A predictive algorithm evaluates potential operational impacts to determine risk and prioritise response. Root cause analysis isolates contributing factors to support efficient, targeted resolution. Based on system data and the operational context, prescriptive actions are defined and executed, with corrective measures carried out by qualified Vertiv Services personnel.

Built for versatility and future growth, Vertiv Next Predict currently supports a broad and expanding range of Vertiv power and cooling platforms, including battery energy storage solutions and liquid cooling components. The service is designed for scalability, enabling seamless integration with future data centre technologies as part of a unified, grid-to-chip architecture. This approach allows customers to adopt Next Predict today while ensuring the service can evolve alongside their infrastructure requirements.

Vertiv Services brings decades of experience in critical digital infrastructure, a global network of trained technicians, and AI-powered analytics.

For more information about Vertiv Next Predict or Vertiv’s end-to-end power and thermal management solutions, including the OneCore scalable prefabricated data centre infrastructure solution, SmartRun modular overhead IT infrastructure system, and Vertiv’s expanding portfolio for AI and high-density workloads, visit Vertiv’s website.

Emirates Water and Electricity Company (EWEC) has signed an agreement with Khalifa University of Science and Technology to jointly develop advanced energy system tools aimed at strengthening the stability and resilience of the UAE’s rapidly decarbonising power sector.

The collaboration will focus on developing intelligent, software-based solutions to support grid stability as renewable energy penetration accelerates across Abu Dhabi and the wider UAE. The initiative comes as EWEC advances a major transformation of the water and power sector, targeting nearly emissions-free water production by 2030 and meeting 60 per cent of Abu Dhabi’s electricity demand from renewable and clean energy sources.

EWEC’s strategy includes the large-scale rollout of utility-scale solar photovoltaic (PV) capacity, forecast to exceed 30GW by 2035, alongside 8GW of battery energy storage systems. The transition is further supported by the decoupling of water and power production through low-carbon reverse osmosis desalination.

As variable renewable energy sources become increasingly integrated into the grid, managing system stability has become a critical priority. Under the agreement, EWEC and Khalifa University will develop intelligent software modules to support the integration of large-scale PV generation and energy storage into the power system. These tools will include predictive modules to forecast power ramping requirements, providing advisory support to operators to ensure secure operation within system limits.

The partnership will also deliver machine learning-based tools to estimate system inertia and forecast frequency deviations, alongside recommendations to mitigate potential grid stability risks.

Ahmed Ali Alshamsi, Chief Executive Officer of EWEC, said the collaboration supports EWEC’s broader role in shaping the UAE’s energy future through strategic planning and the deployment of large-scale solar and battery assets, while accelerating the transition to near-zero-emission water production via reverse osmosis. He added that integrating advanced analytics and AI-driven forecasting into operations will help build a future-ready water and power sector and support progress towards the UAE Net Zero by 2050 Strategic Initiative.

His Excellency Professor Ebrahim Al Hajri, President of Khalifa University, said the partnership demonstrates the role of academia in addressing real-world energy challenges and positions the university at the intersection of innovation and national strategy. He noted that the collaboration will harness advanced deep learning and intelligent modelling to support resilient, data-driven power systems, while transferring knowledge to the next generation of Emirati engineers and system operators.

Beyond technical development, the partnership includes a structured knowledge-transfer programme comprising technical documentation, training and a multi-day operational workshop. Emirati participation is embedded within the project team, with monthly reporting on skills transfer and national capacity-building outcomes.

The initiative aligns with EWEC’s long-term strategy to deliver a smarter, cleaner and more resilient energy system, combining advanced analytics with world-class infrastructure to ensure grid stability, accelerate decarbonisation and strengthen national capabilities.