Closing The Gap Between AI Ambition And Data Reality

Many companies struggle to scale AI from pilot to production due to underlying data infrastructure issues rather than model flaws. Investment often focuses on AI models and tools, neglecting the critical data pipelines and quality controls needed for effective AI deployment. Experts advise prioritizing data readiness and operational data quality to bridge the gap between AI ambition and real-world impact.