AI Is Rewriting Who Gets to Build

Data quality problems don't just create bad reports; they create mistrust. And once trust is gone, people stop using your systems and start building their own workarounds. In this episode of AI Radicals, host Satyen Sangani sits down with Erin McIntosh, Vice President of Global Data Operations at CNA Insurance, to talk about what it actually takes to modernize data governance at a global commercial insurer in the age of agentic AI. Erin shares how CNA is rethinking decades-old governance playbooks, why "build vs. buy" decisions have been upended by new AI tooling, and how her team is shifting from automating decisions to actually improving them. Erin also opens up about the hardest part of leading transformation at speed: getting an organization to trust new systems, rebuild processes from the outcome backward instead of the process forward, and move from slow, bureaucratic governance to agentically-led governance that can actually scale. "Good data governance is actually effective. Bad data governance is actually slow and burdensome." Listen to this episode to learn: Why the shift from automating decisions to improving decisions is where real AI ROI comes from Why agentic governance—not more process—is the path to finally scaling stewardship, compliance, and data quality Why seeking perfection instead of progress is the biggest waste of time and money in AI deployments today