DBS quantifies AI impact not by cost savings, but by the incremental revenue generated from AI-driven customer "nudges." Using rigorous A/B testing, they track the lift from these interactions, reframing AI's value proposition from an efficiency tool to a revenue growth engine, targeting over a billion dollars.

To avoid "AI slop"—the proliferation of low-quality AI outputs—Dell's CTO advocates for a disciplined, top-down strategy. Instead of letting tools run wild, they focus on a small number of high-impact use cases with clear business outcomes, ensuring quality and preventing chaos.

The true ROI of AI lies in reallocating the time and resources saved from automation towards accelerating growth and innovation. Instead of simply cutting staff, companies should use the efficiency gains to pursue new initiatives that increase demand for their products or services.

AI allows companies to suppress their 'hunger' for new hires, even as revenues grow. This breaks the historical correlation where top-line growth required headcount growth, enabling companies to increase profits by shrinking their workforce—a profound shift in corporate strategy.

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").

The "AI ROI flywheel" is a strategy where an organization starts with AI projects that deliver massive, measurable returns (e.g., 10:1 to 30:1). These initial wins create credibility and buy-in, making it progressively easier to secure resources for future AI initiatives.

Instead of abstract productivity metrics, define your AI goal in terms of concrete headcount avoidance. Sensei's objective is to achieve the output of a 700-person company with half the staff by using AI to bridge the gap. This makes the ROI tangible and aligns AI investment with scalable, capital-efficient growth.

Historically, labor costs dwarfed software spending. As AI automates tasks, software budgets will balloon, turning into a primary corporate expense. This forces CFOs to scrutinize software ROI with the same rigor they once applied only to their workforce.

Companies using new technologies merely to cut costs and boost margins often fail. The winning strategy, proven during the containerization era by firms like Walmart, is to pass efficiencies to consumers. This drives volume and captures the market, a superior playbook for AI adoption.