AI startup Rocket offers vibe McKinsey-style reports at a fraction of the cost

The emergence of AI-driven strategy platforms like Rocket signals a structural shift in how organizations consume analytical insights. Rather than treating this as a threat to data engineering roles, I see it as a pressure test on our data infrastructure. These platforms will demand cleaner data contracts, more robust governance layers, and tighter integration between warehouse and LLM pipelines. Teams currently managing fragmented data sources will struggle; those with mature dbt projects and centralized semantic layers will win. The real implication isn't that McKinsey jobs disappear—it's that internal data teams become gatekeepers for AI consumption. We need to stop thinking of analytics as dashboards and start architecting for AI prompt engineering at scale. My recommendation: audit your current data lineage and governance maturity now. If you can't answer "what data is this LLM actually seeing?" in sixty seconds, you have a structural problem that will compound as these tools proliferate.