Elli Peterson's TechCrunch

Three years ago, our audit team faced a recurring challenge that many organizations still grapple with today: mountains of documentation, endless compliance checklists, and audit cycles that stretched far beyond reasonable timelines. We were drowning in data but starving for insights. That changed when we embarked on a journey to integrate advanced AI capabilities into our audit processes. What followed was a series of revelations, setbacks, and ultimately transformative successes that reshaped how we approach internal audit entirely. Our first encounter with Generative AI for Internal Audit came through a pilot program focused on contract review. We had approximately 2,400 vendor contracts requiring annual compliance verification, a process that historically consumed six weeks of our team's time. The AI system we deployed could analyze contract language, flag non-standard clauses, and identify compliance gaps in minutes rather than hours. However, our initial excitement quickly m...

Most marketing technology professionals understand that generative AI is transforming how we execute campaigns, but few truly grasp the intricate mechanics happening beneath the surface. The reality is that modern marketing operations now rely on a complex orchestration of machine learning models, data pipelines, and algorithmic decision-making systems that continuously adapt to customer behavior. Understanding these underlying processes is no longer optional for marketing automation specialists who need to optimize performance, troubleshoot issues, or architect new capabilities into their tech stacks. The integration of Generative AI Marketing Operations represents a fundamental shift in how marketing technology platforms process information and generate outputs. Unlike traditional rule-based automation that follows predetermined logic trees, generative systems create novel content, predictions, and recommendations by learning patterns from vast datasets. This behind-the-scenes trans...