How Eric Schmidt Sees AI Automating Corporate Backbones Next
Corporate spending on routine tasks runs into the billions annually—yet Eric Schmidt, former Google CEO, says most businesses have barely scratched the surface of AI automation. In a December 2025 interview at Harvard University, Schmidt called AI 'under-hyped,' arguing its true impact will come from automating the mundane operations hidden deep inside organizations. This isn’t about flashy AI demos—it’s about transforming the costly, repetitive work that burdens companies. "The boring backbone of business is where automation wins big," Schmidt said.
Automation Isn’t Just Cost-Cutting—It’s Constraint Repositioning
Popular narratives frame AI as a productivity or hype phenomenon fueling code generation or creative tasks. They miss the real game: slashing trillions in corporate overhead by redesigning the operational core. Most firms focus externally on customer-facing AI, but Schmidt spotlights internal workflows like billing, accounting, and inventory management as AI’s dominant next frontier. This shifts the fundamental constraint from labor-cost to process inefficiency—a leap similar to how automation mechanized manufacturing rather than just improving marketing.
This perspective aligns with the insight in Why Dynamic Work Charts Actually Unlock Faster Org Growth, which shows how rethinking system dependencies inside organizations accelerates scaling.
Concrete Examples Show What Firms Are Getting Wrong
Unlike competitors who chase AI for external engagement or coding automation, firms that automate core processes reduce variable costs at scale. Schmidt cited billing and logistics as prime candidates—segments where human error and delay inflate expenses. For contrast, OpenAI scaled ChatGPT primarily through API usage and content generation, creating a new product vertical with high marginal costs, whereas internal AI systems shrink the existing overhead base.
This mechanism echoes what we documented in How OpenAI Actually Scaled ChatGPT To 1 Billion Users, but Schmidt’s focus cuts deeper into operational leverage.
Why Wall Street and Most Executives Are Underestimating AI’s Impact
The economic impact Schmidt anticipates dwarfs what current market enthusiasm forecasts. Whereas some economists warn of bubble dynamics tied to generative AI hype, Schmidt identifies the real disruptive advantage as embedding AI into time-consuming workflows that handle medicine, climate modeling, and engineering. The key constraint shifting here is not technology availability but organizational redesign, a point overlooked in Why Wall Street’s Tech Selloff Actually Exposes Profit Lock-In Constraints.
By shifting these systemic bottlenecks, firms unlock compounding returns without continually inflating headcount or marketing spend. This is leverage unlike the dot-com ad-driven user bubble that Bill Gates and Sam Altman warn against.
Strategic Moves Ahead: Who Takes Advantage and How
Executives who focus investments on automating internal backbones will outpace rivals chasing surface-level AI buzz. Operations leaders should map out repeatable processes ripe for AI replacement, especially where error rates and manual overhead inflate costs. Companies that rethink AI as an infrastructure layer—not just a product—will build durable systems that work without constant human intervention.
This transformation will ripple globally. Markets with flexible regulatory environments and strong data infrastructures—such as the United States and Singapore—stand to edge out competitors slow to adapt. The era of AI as a sales tactic is passing; the era of AI as operational leverage is beginning. "The biggest AI gains come from automating the boring parts of business," Schmidt stated. This repositions where investors and operators should place their bets.
Related Tools & Resources
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Frequently Asked Questions
How does Eric Schmidt view AI automation in businesses?
Eric Schmidt believes AI automation will primarily transform the "boring backbone" of businesses by automating costly, repetitive internal operations like billing and accounting, potentially slashing trillions in corporate overhead.
What corporate areas are most impacted by AI automation according to Schmidt?
Schmidt highlights internal workflows such as billing, accounting, inventory management, and logistics as prime candidates for AI automation that reduce human error and variable costs at scale.
Why does Schmidt say AI's true impact is 'under-hyped'?
He argues that the true impact of AI is not flashy demos or external-facing tasks but embedding automation into mundane, repetitive internal processes that constitute the costly backbone of business operations.
How is AI automation different from previous productivity technologies?
Unlike AI used mainly for customer engagement or creative tasks, Schmidt sees AI as repositioning constraints by redesigning inefficient operational processes, similar to manufacturing automation rather than just improving marketing.
What are the economic implications of AI automation in corporate backbones?
AI automation in internal workflows could drastically reduce inefficiencies, unlocking compounding returns without increasing headcount or marketing spend, potentially dwarfing current market enthusiasm and economic forecasts.
Which regions are expected to benefit most from AI automating corporate backbones?
Markets like the United States and Singapore with flexible regulatory environments and strong data infrastructures are expected to gain a competitive edge by adopting AI-driven operational leverage early.
What strategic advice does Eric Schmidt give to executives regarding AI?
Schmidt advises executives to focus on automating internal repeatable processes with high error rates, treating AI as an infrastructure layer rather than a product to build durable, low-overhead systems.
How does the AI approach of companies like OpenAI differ from Schmidt's automation vision?
OpenAI's ChatGPT scaled via content generation APIs creating new product verticals with high marginal costs, whereas Schmidt emphasizes AI shrinking existing overhead by automating core internal processes.