The World Economic Forum (WEF) in 2026 marked a critical inflection point where Artificial Intelligence transitioned from a subject of speculative debate to the central organizing principle of global economic strategy. Discussions previously dominated by US-China trade tensions or energy security have now pivoted toward the tangible, structural requirements necessary to sustain an AI-integrated economy, particularly the pathway toward Artificial General Intelligence (AGI).
This urgency is fueled by the realization that while Large Language Models (LLMs) have matured rapidly, the physical and regulatory scaffolding required for their sustained operation remains critically underdeveloped. Industry leaders are now focused on systemic risk mitigation, energy provisioning, and the sheer scale of capital expenditure (CapEx) needed to bridge the gap between computational capability and physical reality. The WEF now treats AI infrastructure with the gravity once reserved for the electrical grid.
Key figures underscored the energy bottleneck. Elon Musk, CEO of Tesla, projected AGI capabilities surpassing human intelligence by the end of 2026 but warned that energy production capacity is the definitive constraint. While China accelerates solar deployment at over 100GW annually, the global grid infrastructure lags, threatening a scenario where advanced semiconductor production outpaces the available power to activate the resulting compute.
Conversely, Jensen Huang, CEO of NVIDIA, highlighted a strategic opportunity for the European Union. He argued that the EU could leverage its industrial manufacturing base to bypass traditional software development cycles by rapidly integrating AI infrastructure. This transition, Huang noted, demands significant land allocation for data centers and a surge in demand for trade-skilled labor—electricians and plumbers—whose wages have reportedly doubled in active AI deployment zones, signaling a structural shift in labor value.
The organizational impact of mature AI is now structural, not incremental. A WEF study, 'AI at Work,' revealed that firms are moving beyond simple automation hacks toward fundamental redesigns. Case studies showed AI reducing multi-week tax analysis to 72 hours and streamlining complex logistics procedures, leading executives like ServiceNow’s Hala Zeine to confirm that AI agents are being formally integrated into organizational charts with defined KPIs, effectively becoming 'digital colleagues.'
Geopolitical concerns remain, albeit reframed around data sovereignty and control. Anthropic CEO Dario Amodei warned that distributing advanced chips to adversaries effectively constitutes 'intelligence as a service' for competitors, concentrating immense power. Meanwhile, AI pioneers like Yoshua Bengio and historian Yuval Harari cautioned against internal risks, emphasizing the danger of superintelligent systems lacking human grounding, potentially leading to sophisticated social manipulation.
For Latin America, the WEF report indicated significant untapped potential, projecting $1.7 trillion in annual value, yet only 6% of organizations report significant benefits. Mexico is noted as a regional leader in Industry 4.0 integration, particularly in automotive and aerospace manufacturing optimization. However, national competitiveness is threatened by a 53% productivity gap between large corporations and the SMEs that constitute 90% of economic units, compounded by talent shortages and regulatory ambiguity.
Looking forward, Google DeepMind CEO Demis Hassabis predicted that the labor market will enter 'uncharted territory' within a decade, advising undergraduates to prioritize AI proficiency over traditional entry-level roles. In response to rising inequality concerns, 25 major firms endorsed a commitment to create economic opportunities by focusing on affordable access, skills training, and skills-based recruitment pathways to ensure broader societal participation in the intelligent age. (Source: Adapted from Mexicobusiness.News)