According to Andrew Ng (@AndrewYNg), reporting from the World Economic Forum (WEF) in Davos, significant business impact from AI arises not from numerous isolated, bottom-up AI experiments but from top-down workflow redesign. Speaking with global CEOs, Ng observed that while experimental AI projects offer incremental efficiency—such as automating a single loan approval step in banking—the real transformative opportunity lies in rethinking the entire process. For example, automating preliminary approval enables banks to offer a '10-minute loan' product, enhancing customer experience and driving growth. This shift requires integrating AI into end-to-end workflows and aligning product, marketing, and operational strategies. Ng emphasizes that while grassroots innovation is valuable, scaling for maximum business impact demands strategic, holistic redesign, positioning AI as a growth engine rather than a mere efficiency tool (source: @AndrewYNg, deeplearning.ai/the-batch/issue-337/).

According to @godofprompt, citing McKinsey's 2025 State of AI report, 88% of companies now deploy AI in at least one business function, but just one-third are scaling AI across the enterprise. The report highlights that while 62% are experimenting with AI agents, under 10% have achieved functional scale. Only 39% have seen EBIT impact, though 64% report improved innovation. McKinsey identifies a small cohort—6% of 'AI high performers'—who distinguish themselves by redesigning workflows and transforming their businesses, treating AI as a core infrastructure rather than a cost-saving tool. The main business opportunity lies in moving beyond pilot projects to enterprise-wide transformation, positioning AI as essential to process redesign and long-term value creation (Source: McKinsey 2025 State of AI Report via @godofprompt).