For people who ask AI too much, and expect it to care

Tag: Explainable AI

  • Caveats and Pitfalls When Using AI for Price Optimization

    Caveats and Pitfalls When Using AI for Price Optimization

    1. Data Quality Is a Bigger Risk Than Algorithm Choice AI pricing engines rely heavily on historical data to train demand forecasting and elasticity models. If that data contains gaps, errors, or inconsistencies—such as outdated costs, missing promo labels, or inconsistent SKUs—the resulting price recommendations may be worse than manual judgment. Example: A model trained on…

  • Building Trust in AI: Transparency, Explainability, and Accountability for Business Leaders

    Building Trust in AI: Transparency, Explainability, and Accountability for Business Leaders

    Artificial intelligence (AI) is no longer a futuristic promise—it’s a business reality, driving efficiency, innovation, and growth across industries. Yet, as AI becomes ubiquitous, so do concerns about its trustworthiness. For business leaders, deploying AI isn’t just about technical prowess; it’s about ensuring stakeholders—customers, employees, regulators, and investors—have confidence in the systems they rely on.…