This white paper provides executives with a framework for adopting generative AI while balancing innovation with technology, people, culture, governance, ethics, and regulation. It warns that AI projects can fail because of weak data quality, inadequate controls, escalating costs, unclear value, skills shortages, and fragmented infrastructure. Organizations need modern interconnected data environments, suitable computing and development platforms, workforce adaptation, and clearly defined business use cases. Risk management must address privacy, intellectual property, cybersecurity, explainability, fairness, bias, regulatory compliance, and sensitive data throughout model training, internal datasets, and outputs. The paper recommends flexible technology partnerships, avoiding vendor lock-i

Join for free to read