On this episode of the Scouting For Growth podcast, Sabine VdL talks to Marinela Profi, a leading authority on AI and the Global AI & Generative AI Marketing Strategy Lead at SAS. Marinela sits at the intersection of data science, AI, and business strategy, helping global organizations move beyond AI hype toward real, governed impact. In this episode, she shares key insights from the SAS Generative AI Global Research Report and unpacks what’s actually happening inside organizations adopting GenAI—what’s working, what’s stalling, and where leaders are getting it wrong. What the data really says The SAS report surveyed 1,600 organizations across 16 countries, ensuring a truly global perspective. One headline finding: China leads in adoption (83% actively using or experimenting with GenAI) The U.S. leads in maturity and implementation, focusing more on operational integration and value creation High adoption, however, does not automatically translate into strong returns. Productivity gains—unevenly distributed Generative AI is improving efficiency and employee experience by making information more personalized, accessible, and responsive. But value creation looks very different depending on role. Business users, analysts, data scientists, IT teams, and marketers all benefit in distinct ways—and face different risks and responsibilities as a result. This uneven impact is forcing organizations to rethink how they deploy AI across functions, not just centrally. Governance is the dividing line One of the clearest insights from the research: governance separates winners from laggards. Most organizations are still underprepared. Without proper frameworks, companies expose themselves to: ethical and bias risks regulatory and compliance failures IP leakage security vulnerabilities reputational damage GenAI can produce highly convincing outputs—but accuracy, accountability, and trust don’t come for free. Regulated industries aren’t waiting Contrary to popular belief, banking is one of the most advanced sectors in GenAI implementation, despite heavy regulation. The reason? Clear governance, defined use cases, and disciplined prompting practices. As Marinela notes, effective prompting isn’t just a skill—it’s a control mechanism. From GenAI to agentic AI Marinela also points to the next frontier: agentic AI—systems that don’t just generate content, but perceive, reason, and act autonomously. This raises the stakes even higher for explainability, transparency, and human oversight. Why this episode matters This conversation is a reality check for leaders racing to adopt AI. Speed without structure creates risk. Adoption without governance destroys trust. And AI maturity isn’t about how fast you move—it’s about how responsibly you scale. If you’re navigating AI strategy in financial services, healthcare, government, or any regulated environment, this episode offers a grounded, global view of what it really takes to turn generative AI into sustainable advantage.