Energy dilemma and scientific discovery Sam Altman links model expansion to efficiency calculations in Abu Dhabi
Sam Altman’s remarks in Abu Dhabi reveal the difficult equation governing the future of advanced computing, where the discussion of artificial intelligence is no longer confined to chat interfaces but has moved directly to energy physics and industrial consumption challenges. During his participation in the Abu Dhabi International Petroleum Exhibition and Conference, ADBIC 2026, the CEO of OpenAI described the United Arab Emirates as the most forward-looking country globally in this arena, affirming that the tripartite partnership with ADNOC and the G42 Group aims to shape and empower the energy sector with advanced smart systems. This is the path that strategic agreements, signed by the Crown Prince of Abu Dhabi alongside major investments such as the Al Jabbah Basin in Al Ruwais, have pursued.
The cost of a query falls while the total demand explodes.In our reading of the scene, this paradox was the core of the economic proposal presented by Altman, who explained that the amount of energy required per query decreases as model efficiency improves, yet the lower cost of use encourages consumption of the technology at a far higher rate. Instead of increased efficiency reducing loads, it creates a compound demand that makes energy consumption the most prominent challenge, prompting OpenAI to bet that artificial-intelligence applications in the energy sector itself will offset this pull and even support a global increase in energy supply.
This technological shift extends to reasoning capabilities, where Altman’s focus is on scientific discovery after models have successfully tackled complex mathematical problems that humans could not solve in recent months. This computational power does not stop at theoretical research; it also covers the engineering and physical complexities involved in energy production and sustainability, paving the way for artificial intelligence to move from transaction execution to leading unprecedented scientific and industrial solutions.
Smart systems acquire the status of colleagues, but human judgment remains the decision maker.Thus Altman defines the workforce landscape, noting that technology now performs large portions of office work while emphasizing that societies can adapt as long as creativity and final decision remain in human hands, keeping algorithms as tools of empowerment rather than entities that decide the future on behalf of their owners.
What actually changes for institutions and professional teams in the Gulf, Egypt, and the region? The direct shift begins in computing budgets and infrastructure, as technology managers should not assume that lower query costs will reduce their expenses, because turning models into permanent team members will increase overall usage and drive the total bill higher. At the professional level, you must recognize that added value quickly moves from verbal skills and text coordination to integrating models into solving complex mathematical problems and managing physical assets; the next race will be decided not by the speed of drafting correspondence but by the precision of systems in raising the efficiency of power networks and managing them.