Today's post is 301 words, a 2-minute read. Sources: Generative AI Enterprise — "McKinsey Unveils AI Profit Lessons" 1 big thing: We just entered a new phase of enterprise AI — here's what that means for B2B marketers The question is no longer whether AI works. It is whether your organization can actually deliver on it. Why it matters: McKinsey's 2026 State of AI confirms what most enterprise leaders already sense — AI investment is surging, individual productivity gains are real, but P&L impact remains elusive for most organizations. Driving the news: McKinsey surveyed 1,719 participants across 97 nations. → 80% say AI has improved their individual productivity → Only 37% attribute any EBIT impact to AI — roughly flat year over year despite surging investment Zoom in: Companies breaking through share two practices: they redesign workflows alongside the model rather than layering AI on top of existing ones, and they measure in business outcomes rather than accuracy metrics. → McKinsey anchors this with two case studies — a global manufacturer scaling with AWS and a conglomerate deploying agentic AI at speed Yes, but: 20% of respondents say AI operating costs — tokens, infrastructure, compute — are already constraining usage. Cost management is becoming a real strategic variable, not a footnote. Be smart: If your AI initiatives are measured in time saved or content volume produced, you are measuring the wrong things. Tie AI output to pipeline influence, conversion rate, or content-attributed revenue. That is the only measurement that survives a budget conversation. The bottom line: Technology is rarely the binding constraint. Delivery, adoption, and measurement are. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai #AIStrategy #B2BMarketing