Sam Altman says AI could transform global energy industry as OpenAI deepens UAE ties

OpenAI CEO says artificial intelligence could help energy companies improve efficiency, accelerate innovation and solve complex engineering challenges.

OpenAI CEO Sam Altman has said artificial intelligence could transform the global energy industry by helping companies develop new technologies, improve operational efficiency and address complex engineering challenges, even as growing AI adoption drives demand for electricity.

Speaking at the opening ceremony of ADIPEC 2026 in Abu Dhabi on Monday, Altman described the relationship between AI and energy as a major opportunity for both industries, arguing that increasingly capable AI models could help address some of the sector’s most difficult challenges.

“For a long time, the AI industry has talked about what it needs from the energy industry. And now I think we can repay the favour,” Altman said.

He explained that AI’s potential extends beyond improving workplace productivity to accelerating scientific discoveries and solving problems that have historically proved difficult for researchers.

The remarks came as Altman discussed OpenAI’s expanding relationships in the UAE, including its collaboration with ADNOC and G42 to explore advanced AI applications in the energy sector.

How AI could reshape energy production

Altman said advances in AI were creating opportunities for energy companies to improve production and operational efficiency through new approaches to engineering, research and industrial processes.

He pointed to the potential for AI systems to assist with developing new materials, improving turbine designs and optimising operations.

According to Altman, energy companies could increasingly use sophisticated AI systems to address technical challenges, potentially improving the availability and efficiency of energy worldwide.

The OpenAI chief said the technology was moving beyond its initial role as a productivity tool, with advances in AI-assisted scientific discovery opening up opportunities across multiple industries.

He described the emerging capabilities as the beginning of a potential new period of innovation, comparing their significance to a Renaissance rather than simply another industrial revolution.

Altman argued that the capabilities of newer AI models could encourage companies to pursue more ambitious projects than those previously considered feasible.

“We’re all not dreaming big enough, because we’re all kind of used to last year’s models,” he said.

UAE’s AI ambitions

Altman also praised the UAE’s approach to artificial intelligence, describing the country as one of the world’s most forward-looking markets for AI adoption.

He attributed the country’s progress to government leadership and its willingness to integrate AI across public services and the wider economy.

Altman said countries that embrace AI early and deploy it extensively would be better positioned to benefit from its economic and technological potential.

His comments followed announcements of new OpenAI-related partnerships in Abu Dhabi spanning sectors including energy, education, investment and government.

Discussing the relationship with ADNOC and G42, Altman said the companies had been exploring opportunities to apply increasingly advanced AI systems to major industrial challenges.

He also highlighted the UAE’s willingness to pursue ambitious technological projects, describing it as an important factor in OpenAI’s relationship with the country.

Energy could become AI’s biggest constraint

Despite improvements in AI efficiency, Altman warned that energy availability could become one of the most important factors determining how quickly the technology develops.

He explained that although the amount of energy required for individual AI queries has declined, improvements in efficiency are encouraging greater overall usage.

“On one hand, the energy per query is falling incredibly dramatically,” he said.

Altman argued that the AI and energy industries have a shared responsibility to meet growing demand, particularly as AI becomes more widely used in healthcare, education and scientific research.

He suggested that future applications could include accelerating drug discovery and making high-quality educational support more widely accessible.

Looking ahead, Altman identified energy as a particularly difficult constraint because, unlike software and computing hardware, physical energy infrastructure cannot be improved through advances in AI models alone.

While developments in robotics, chip manufacturing and model efficiency could reduce the cost of delivering AI services, the physical infrastructure needed to power those systems would remain critical.

For the energy industry, Altman suggested that increasingly sophisticated AI systems could help address this challenge by making energy production and delivery more efficient.

He argued that the relationship between the two industries could become increasingly important as AI adoption accelerates and demand for computing power continues to grow.