Enterprise AI has a memory problem, but businesses have the answer (www.techradar.com)

A new perspective on enterprise AI is emerging, highlighting a critical "memory problem" that limits AI's understanding of business contexts. While much of the focus has been on advancing AI models themselves, experts argue that organizations already possess the rich, contextual data necessary for meaningful AI implementation. This "business memory" encompasses decades of past decisions, workflows, and industry knowledge that, if properly harnessed and structured, could dramatically enhance AI's decision-making capabilities and automation potential. To effectively leverage this resource, businesses must invest in infrastructure that transforms unstructured content into an AI-ready format, ensuring that AI operates based on relevant, trustworthy information. Moreover, implementing an ontology—a formal framework that links entities and processes—can significantly enhance AI’s contextual understanding, particularly in regulated industries such as healthcare and finance. By capitalizing on their existing knowledge and data, companies can avoid the pitfalls of starting from scratch and instead build resilient, adaptable AI systems that offer enhanced outputs without sacrificing integrity or compliance.