Decision Logic: The Difference Between an Answer and a Decision

Ask an AI system a question, and you'll get an answer. Decision logic determines whether you should trust it.  In this episode of The AI Forecast, Paul Muller sits down with Darlene Newman, Innovation Lead at Duczer East, to explore the hidden layer that helps AI move from pattern matching to practical decision-making.  From semantic layers and ontologies to knowledge graphs and governance frameworks, Darlene unpacks the often-overlooked structures that sit between AI outputs and real-world decisions. She also shares practical guidance on integrating decision-making logic into AI initiatives without adding complexity. Paul and Darlene take a closer look at: Why decision logic is the “why” behind AI decisions How guardrails help prevent hallucinations and unreliable outputs Why knowledge design is becoming a critical AI capability How organizations can build scalable and auditable AI systems Practical approaches for integrating decision logic into AI initiatives Beyond models and prompts, this conversation is about giving AI the context it needs to make better decisions. For enterprise leaders, it offers a practical look at the structures and knowledge foundations that can help AI deliver consistent business outcomes. To hear more about turning organizational knowledge into AI capabilities, check out Ep 69 | Industrial Enterprise AI: Growing Value and Organizational Risk Management  Stay in touch with Darlene: Darlene Newman on LinkedIn: https://www.linkedin.com/in/darlenenewman/ Where Innovation Takes Root newsletter: https://www.linkedin.com/newsletters/innovation-through-the-hype-7272737391067459584/ +++ Like and subscribe to The AI Forecast, sponsored by Cloudera, to stay up to date on the latest episodes. You can watch the video version of this episode on The AI Forecast.