In Episode 93 of the Digital Velocity Podcast, Erik Martinez sits down with Ginger Grant, a seasoned data strategist, to explore how artificial intelligence and machine learning are reshaping the fundamentals of business analysis and decision-making.

Ginger shares her unique perspective on the crucial distinctions between generative AI and machine learning, highlighting why accuracy, data quality, and the right questions matter more than ever. She explains why companies must address messy, fragmented data before they can effectively harness AI, and how grounding models in proprietary data unlocks more reliable business insights.

Listeners will gain insights into:
• Why machine learning has a more immediate impact than generative AI for business-critical tasks
• The persistent challenge of data organization and the dangers of Excel-driven reporting
• How companies like Goldman Sachs are grounding AI models in proprietary data to achieve accuracy
• Why dashboards and rote reporting are ripe for automation—and where humans remain indispensable
• How leaders can encourage AI adoption without stoking fear of job loss, through training and intentional change

For direct-to-consumer marketers and cross-industry leaders alike, Ginger offers actionable guidance on how to move beyond data collection toward true business impact. From defining success metrics to ensuring critical thinking remains at the core of analysis, this episode is a must-listen for executives and marketers preparing to navigate the future of AI-driven decision-making.