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AI tools providing individual convenience (like finding a cheap flight) don't meaningfully show up in GDP. Real, measurable productivity gains only materialize when businesses fundamentally re-engineer their core processes to leverage the technology, much like Walmart and UPS did with computing and the internet in previous decades.
The common use of AI for trivial tasks is a distraction. The real opportunity for businesses is to apply AI to core operational workflows, dramatically increasing output per employee. This creates a window for massive margin expansion before market prices adjust.
While flashy AI tools for design and content creation garner attention, their ROI can be negative. The most significant efficiency gains will come from automating mundane, repetitive tasks in areas like supply chain logistics, where AI can solve complex coordination problems that truly move the needle.
Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").
Drawing a parallel to the slow adoption of PCs in the 90s, Boris Churney argues companies won't see AI productivity boosts by simply layering it onto old workflows. The biggest benefits come from placing AI at the core of the business and redesigning processes around its capabilities, eliminating old bottlenecks entirely.
Simply making your team more productive with AI (e.g., doubling PRs) won't increase revenue unless you redesign your business model to leverage that new capacity. The goal isn't to do old things faster, but to find entirely new things that are now possible, like letting customers order cars via email in 1995.
The historical adoption of electricity in factories shows that true productivity gains came from redesigning the factory floor, not simply replacing steam engines. Similarly, companies must fundamentally re-engineer processes around AI to unlock its transformative potential.
True productivity gains from AI will mirror the adoption of electricity. Early factories that just replaced steam engines with electric motors saw little benefit. The revolution happened when they completely redesigned the factory floor around the new technology. Similarly, companies must reimagine entire workflows around human-AI collaboration.
Businesses are unlikely to use powerful AI simply to shave a few percentage points off their software spend. The real, high-impact ROI comes from applying AI to improve core business operations, making the actual business more effective and efficient.
Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.
The productivity boom from AI won't materialize from workers simply using new tools. Citing historical parallels with electricity and computers, the real gains are unlocked only when companies fundamentally restructure their operations and business models around the technology.