Azerbaijan emerges as a regional AI hub for energy decarbonisation and chemical innovation

Boston Consulting Group (BCG) executives say Azerbaijan is positioning itself as a practical testbed for applying artificial intelligence to energy, with a particular focus on chemistry and emissions reduction that could accelerate industrial decarbonisation across the region and beyond. According to an exclusive interview with Trend, Anton Aristov, Managing Director and Partner at BCG, framed the Caspian AI Institute as a hybrid research-and-delivery vehicle: “70% of its resources should be dedicated to practical use cases in energy, while the remaining 30% should be devoted to research that pushes the boundaries of cutting-edge technologies relevant to the global community.”

That dual mandate, Aristov said, is intended to keep the institute relevant to global partners while delivering tangible, industry-ready solutions for oil, gas and refining firms. The institute’s portfolio includes AutonomousLab.AI, an AI-driven platform to discover and synthesise novel chemicals starting with carbon‑capture materials. According to the Caspian AI Institute’s own materials, AutonomousLab.AI combines pre-trained models with laboratory workflows and international academic collaborations to compress discovery cycles that traditionally take years into months.

Aristov described one early success unveiled in Dubai with SOCAR: an AI-designed carbon‑capture solvent. “Once trained on this dataset, the AI was tasked with designing new candidates , and it produced around 400,000 molecules, nearly 100 times more than what is currently known to science,” he told Trend. He added that a portfolio of roughly 40 candidates had been identified that are “supposed to capture 50% more CO2 than what’s used in the industry,” and that laboratory synthesis in Spain had confirmed some candidates outperform existing molecules.

BCG and its partners emphasise the distinction between discovery and scale-up. Konstantin Polunin, Partner and Director at BCG, warned that moving from promising molecules to commercially viable products requires industrial partners and technical capacity: “We have a molecule, it proves that this is viable, and there is a longer path to scale-up to technological applications, but that’s a question of partners, and that’s a question of opening up own capacities to test this technology, and then making a commercially viable export product worldwide,” he said to Trend.

Automation is central to the institute’s ambition to accelerate throughput. Aristov said the next bottleneck is laboratory experimentation and outlined plans to automate synthesis and testing: “We are working to automate these processes, aiming to establish a fully robotic laboratory operating 24/7, synthesizing molecules and feeding back results , whether success or failure , in real time.” The Caspian AI Institute’s public materials describe AutonomousLab.AI as marrying AI generation with automated chemistry to enable rapid iteration across chemical domains relevant to energy, from corrosion inhibitors to lubricant additives.

Beyond chemistry, BCG and SOCAR are deploying AI to operationalise emissions reduction. The Methane.AI platform, described on the Caspian AI website and confirmed by BCG statements reported by APA, collects and analyses measurements to identify methane sources, quantify volumes and forecast abatement pathways. Aristov framed the platform as tailored to companies with limited digitalisation: “It enables these organizations to conduct sampled, on-the-ground measurements and then extrapolate the findings across the rest of their infrastructure.” The Caspian Methane Accelerator, a collaborative forum that already includes SOCAR, KazMunayGaz and Uzbekneftegaz, is intended to create common baselines and reduce the unit cost of emissions abatement through shared measurement and investment plans.

BCG is also testing AI at the software interface level to reduce repetitive tasks in subsurface workflows. Aristov described prototype AI agents that “run directly over the interface of this software , entering data, pressing buttons, identifying mistakes, making decisions,” preserving the original professional packages while removing routine work. He said the model allows human experts to transfer accumulated knowledge into AI systems so that retiring specialists’ expertise can be retained and replicated across workstations. The company plans a marketplace of AI agents that professionals can download to accelerate discrete steps of seismic processing, a proposal discussed at the 2025 Caspian Technical Conference.

Strategically, BCG’s executives see Azerbaijan’s agility and state support as competitive advantages. “Europe could potentially learn from these fast movers,” Konstantin Polunin told Trend, citing the speed of innovation in Azerbaijan and neighbouring Central Asian states. Aristov pointed to policy tools that could accelerate talent attraction and commercialisation , notably a special economic zone in liberated territories that is being developed with green and innovative priorities , and to efforts to build a “bridge to the global AI ecosystem” including Silicon Valley investors and academic partners such as URV in Spain and leading international universities.

Industry analysts and regional strategists view the push as part of a broader digital transition. A 2025 report on AI in Central Eurasia notes government strategies to diversify away from hydrocarbon dependence through AI-driven transformation in public services and industry, while BCG’s presentations at regional forums emphasise practical, exportable technology packages as the route to scale. According to BCG’s public remarks at the Baku Energy Forum, the institute’s work is already being prepared for carbon capture and storage projects and for exportable technical services.

BCG presents the Caspian initiatives as pragmatic responses to industry needs: rapid discovery, targeted automation and collaborative platforms to lower the cost of decarbonisation for asset owners with legacy infrastructure. The model remains contingent on successful scale‑up, industrial testing and the creation of financing and partnership arrangements that can convert laboratory gains into deployed emissions reductions. As Aristov observed, compressing discovery from a decade to months is a significant step; converting those discoveries into widespread, low‑carbon production will require the next wave of engineering, capital and cross‑border collaboration.