Bridging The AI Trust Gap: Innovations In Explainable Machine Learning
Analytics Insight, Friday, April 11th, 2025
In this modern era, Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing businesses, yet their adoption remains a challenge due to their often opaque decision-making processes.
Lokeshkumar Madabathula, a researcher and AI expert, explores how explainable AI (XAI) can address these challenges by making AI-driven insights more transparent and actionable for business stakeholders.
The Growing Need for Explainability in AI AI adoption in business processes witnessed a steady incline, but indeed, there still lies a prime issue: trust. Many companies find it difficult to comprehend the insights generated by AI, thus giving rise to skepticism and unwillingness during decision-making. It has been reported that 89% of organizations acknowledge the potential of AI, but only about 23% in reality have incorporated such solutions into their core business strategies.