AI's most successful enterprise use cases, customer service and coding, target opposite ends of the labor cost spectrum. It either replaces easily quantifiable, lower-cost roles or provides significant leverage to the most expensive employees like software engineers.

The most exciting application of AI isn't making people faster at their current jobs. It's enabling them to broaden their span of influence—like a backend engineer doing frontend work or a non-engineer automating technical customer onboarding—which creates significantly more business value.

The most potent productivity gains from AI aren't just for junior staff. Seasoned professionals who combine deep domain expertise with adaptability are using AI to rapidly learn adjacent skills like design or marketing. This allows them to "collapse the skill stack" and single-handedly perform tasks that previously required multiple people.

AI's capabilities are inconsistent; it excels at some tasks and fails surprisingly at others. This is the 'jagged frontier.' You can only discover where AI is useful and where it's useless by applying it directly to your own work, as you are the only one who can accurately judge its performance in your domain.

A small cohort of power users are achieving massive productivity gains with AI, while most companies are stuck at the most basic stages. This creates a widening competitive gap where firms that master simple access and training will dramatically outperform those mired in bureaucratic inertia.

The prevailing vision of every employee using a co-pilot for marginal gains is misguided. True enterprise value will be unlocked by a "Vanguard model," where companies invest heavily in a few powerful, mission-critical agentic systems that drive transformative productivity in specific, high-impact areas.

Early AI adoption focused on saving time. The new wave, driven by agentic systems, derives its primary value from enabling completely new functions and significantly increasing throughput, representing a move from efficiency to opportunity-focused ROI.

The recent explosion in enterprise AI spending was triggered by the release of effective, specialized tools like coding assistants that provided clear ROI to specific professionals like developers. This suggests future growth hinges on targeted, vertical-specific applications, not just general-purpose models.

Initial AI productivity gains (e.g., turning a 2-day task into 10 minutes) are just the start. The true, transformative value emerges when business experts, newly empowered by AI thinking, use that saved time to pursue entirely new, previously impossible work, fundamentally changing business outcomes.