Verizon CEO Predicts AGI Within 18 Months as Industry Leaders Debate Workforce Reality

Verizon CEO Dan Schulman forecasts that Artificial General Intelligence will arrive within six to 18 months, triggering a decade of technological acceleration so intense it will compress a century’s worth of progress into five to ten years. Speaking at the Ford Pro Accelerate event in Detroit, Schulman warned that current AI models represent the baseline for an impending shift that will outpace traditional labor market adjustments and corporate restructuring cycles.

This projection places Schulman at the aggressive end of industry timelines. While many researchers estimate AGI—systems capable of reasoning across diverse domains rather than executing narrow tasks—is decades away, Schulman argues that model capabilities are currently doubling every two months. He predicts this trajectory will lead to quantum computing dominance within two years and functional humanoid robotics by 2035. The immediate implication for large employers is structural: Verizon’s 250,000-person workforce must transition from rigid functional silos to fluid organizational models before institutional safeguards can fully mature.

Despite these warnings of rapid displacement, executives managing physical infrastructure describe a different bottleneck. For the telecommunications and energy sectors, the primary constraint is not an excess of displaced workers but a severe shortage of skilled tradespeople needed to build the networks supporting AI expansion. Dycom Industries CEO Dan Peyovich noted that his company employs 21,000 people specifically to lay fiber and construct telecom infrastructure, emphasizing that the technology boom requires massive physical buildouts that automation cannot currently perform.

This divergence highlights a critical gap between software-centric AI predictions and industrial reality. PG&E CEO Patti Poppe illustrated this tension by describing linemen who still require helicopter drops to reach remote transmission towers while simultaneously needing fluency in predictive sensors and edge computing. The grid of the future demands hybrid workers who possess both traditional trade skills and digital literacy, suggesting that AI adoption in heavy industry may augment rather than replace human labor in the near term.

Manufacturing and construction leaders are already deploying AI to address labor scarcity rather than headcount reduction. Stanley Black & Decker has introduced autonomous drilling robots for data center construction that handle repetitive coring tasks, allowing electricians to focus on complex wiring and termination. Trane Technologies uses AI to optimize building HVAC systems based on real-time occupancy rather than design specifications, targeting a 15% efficiency gain in a sector where 30% of energy is typically wasted. Both applications frame AI as a tool to increase output per worker amid persistent hiring difficulties.

Schulman acknowledged these operational realities but maintained that leaders should plan for worst-case disruption scenarios rather than assuming a smooth transition. To mitigate risks, Verizon recently launched a $70 million initiative providing free AI training to American workers beyond its own employee base. This move reflects a growing recognition among telecom executives that network resilience depends on broader workforce adaptability, not just internal upskilling.

The debate ultimately centers on timing rather than direction. While industrial CEOs see AI as a companion technology solving immediate productivity gaps, Schulman’s timeline suggests these incremental adaptations may be overtaken by exponential capability growth. His prescription for corporate leadership involves active scenario planning for disruptions that arrive faster than educational institutions or policy frameworks can respond.

Verizon’s $70 million workforce development program is currently active and accepting participants through local community organizations nationwide.