Model context protocol (MCP) is a vital standard enabling AI agents to automate tasks in core enterprise systems, but requires immediate, strong governance for safe adoption.
Are you about to see an increase in your VMware licensing, or have you seen the increase and are looking at your options?
End-user testing is crucial; it guarantees new systems truly meet user needs, enabling a smoother operational handover via service desk and project team collaboration.
Acquisitions like Workday-Paradox risk fragmenting HCM with new data silos, demanding unified AI governance and local compliance scrutiny.
ServiceNow has announced the release of AI Experience, a unified interface that will span the entire ServiceNow platform and seek to position it as the unified orchestration layer for enterprise AI.
Agentic AI demands immediate, top-level governance to manage universal risks, preserve accountability, and protect leaders from personal liability exposure.
Autonomous agentic AI presents a universal risk/value challenge; leaders must urgently establish robust, new-era governance frameworks to meet their personal duty of care.
AI governance isn’t a brake on progress; it’s a strategic enabler of ethical, scaled innovation, requiring a shift to use-case focus and universal literacy.
Boards and executives must ask targeted questions to bridge their AI knowledge gap, ensuring responsible adoption and effective governance.
Neo4j’s investment highlights graph technology’s critical role in practical AI, providing essential context to unlock efficiency gains from GenAI and ML.
