AI Governance & Ethics

Data Quality Management (DQM) refers to the process of maintaining, improving, and ensuring that data across an organisation is accurate, consistent, complete, and reliable. It is a critical component of any data governance strategy and a key enabler of trustworthy…

Data silos occur when information is isolated within specific departments, teams, or systems, making it inaccessible or inconsistent across an organisation. These silos often arise from legacy systems, lack of integration, or cultural and structural barriers between teams. While data…

Ethical AI refers to the development and deployment of artificial intelligence systems that operate transparently, fairly, and responsibly. It ensures that AI technologies align with human values, respect privacy, and avoid causing harm or reinforcing bias. As AI becomes more…

Bias in Artificial Intelligence (AI) occurs when algorithms produce results that are systematically prejudiced or unfair due to errors in the data, design, or implementation process. AI bias reflects the patterns and imbalances found in the training data, leading to…

In Artificial Intelligence (AI), a black box refers to a model or system whose internal workings are not easily understood or visible to humans. It produces outputs based on inputs, but the reasoning behind its decisions remains opaque. This lack…

AI Ethics refers to the set of principles and practices that guide the responsible development and use of Artificial Intelligence (AI) technologies. It ensures that AI systems are designed, deployed, and monitored in ways that respect human rights, minimise harm,…

AI Risk Management is the process of identifying, assessing, and mitigating the potential risks associated with the design, development, and deployment of artificial intelligence systems. It ensures that AI technologies operate safely, ethically, and in alignment with regulatory standards while…

AI governance is the set of policies, processes, and controls that guide how your organisation develops, deploys, and monitors AI systems. It ensures your AI operates safely, ethically, and within legal boundaries while protecting against risks like bias, data breaches,…