Introduction
At GITEX Global 2025 in Dubai, one of the most significant moments came when Sam Altman, CEO of OpenAI, joined a virtual conversation with Peng Xiao, Group CEO of G42. Their discussion, titled “From Early Adoption to AI-Native Societies: Envisioning the Next Era of Intelligence”, spotlighted how nations must build new structural foundations—both physical and policy-oriented—to support societies where AI is as embedded in daily life as electricity or roads.
Below are key takeaways from Altman’s remarks and the broader implications for AI-native societies.
Key Insights from Altman & G42
Intelligence as Infrastructure & Access
Altman emphasized that the emerging divide in AI won’t be about algorithms or raw capability, but about access. He stated: “The best way to avoid an AI divide is to make intelligence ‘abundant and cheap’ … to make it available everywhere, to teach people how to use it, and to make it accessible to all.”
The idea is that intelligence (AI services, models, tools) should be considered a super-utility—something foundational, like power or roads. Peng Xiao called this infrastructure “the intelligence grid.”
AI + Energy & Compute Convergence
Altman and Peng argued the cost of intelligence will increasingly align with the cost of energy and compute infrastructure. As AI scales, nations will be judged not just by their models but by their ability to host and power them.
Altman predicted a future where AI systems build infrastructure themselves (robots constructing robots, data centres replicating / scaling), pointing to a “new industrial phase” of automation.
National AI Strategies as Essential
Altman said every country “is going to need to have an AI strategy.” He praised the UAE’s approach as a model for the rest of the world. This includes not only investment in AI but building regulatory, governance, and infrastructural systems to support sovereign and inclusive AI ecosystems.
AI in Everyday Life & Culture Shift
AI is shifting from novelty to necessity. Altman said that over the past couple of years, people have started to depend on AI for productivity and workflows, and that what seemed futuristic is now part of daily life.
Tangible examples: Peng Xiao shared how ChatGPT was used 500 times in prompts to design part of Sheikh Tahnoon’s home in Abu Dhabi. Also that in Sheikh Tahnoon’s office there is a high ratio of AI agents vs human staff. These reflect that AI isn’t just for labs—it’s being operationalized in personal, administrative, architectural contexts.
Implications & Structural Requirements
Based on Altman’s comments and observations from GITEX, several structural foundations are emerging as essential for AI-native societies:
| Requirement | What It Means in Practice |
|---|---|
| Compute & Infrastructure Scale | Developing large data centres, hybrid energy solutions (solar, nuclear, gas), building “AI campuses” like UAE’s Stargate in partnership with OpenAI, G42, Nvidia etc. |
| Governance & Policy Frameworks | Regulatory oversight for data privacy, sovereignty, standardization. Ensuring model transparency, trust, safety. Each nation needs frameworks to support this. |
| Access & Education | Democratizing access: tools, platforms, investment in skills. Ensuring AI isn’t just in big cities or governments. Inclusion so that smaller economies, remote regions can partake. |
| Energy & Sustainability | Because AI compute requires power, cooling, and energy resources, sustainability and cost control are vital. Intelligence cannot scale if infrastructure is power-starved or prohibitively expensive. |
| Cultural and Institutional Integration | Embedding AI in public services, architecture, governance, business operations, education. AI also influencing how people work, what tasks are automated, etc. |
Challenges & Caveats
- Risk of Entrenchment or Lock-in: As countries build out national AI stacks, there is risk they become dependent on specific vendors or foreign technologies, which could undermine sovereignty if not managed carefully.
- Inequality & the “AI Divide”: Even with intentions to make AI abundant, the logistics of infrastructure, internet access, and policy may cause gaps between countries or within populations.
- Ethical, Privacy, Safety Issues: As AI systems begin handling more governance, public services or personal data, there must be strong safeguards, auditing, and trust.
- Energy and Environmental Impact: Scaling infrastructure has environmental and energy costs. Sustainable design, efficient hardware, renewable energy are essential to avoid negative externalities.
What These Mean for the UAE & the MENA Region
- The UAE is positioning itself as a leader in this space: with projects like Stargate (AI campus), strong investment in data centres, and national policy orientation toward digital sovereignty.
- The co-operation between OpenAI, G42, and other major firms (Cisco, Oracle, etc.) shows that global partnerships will be necessary to enable infrastructure, access, and technology transfer.
- Local examples (architecture design via AI, daily AI agent usage) show early integration becoming visible. This helps shift public perception from AI as futuristic or optional, to AI as essential.
Conclusion
Sam Altman’s address at GITEX Global 2025 represents a landmark moment in the evolution of AI governance and societal design. The structural foundations of AI-native societies go beyond models and tools—they require investment in infrastructure, energy, regulation, policy, inclusion, and a mindset that treats intelligence as a foundational utility.
For governments, enterprises, and innovators, the message is clear: strategy is not optional anymore. Building smart, resilient, inclusive, and sovereign AI ecosystems is what will define global competitiveness and societal wellbeing over the next decade.
