As more and more enterprises ride the wave of Artificial Intelligence (AI) systems and applications, a need for a structured approach for managing AI projects arises. In the past, enterprises used to deploy few Machine Learning (ML) and AI models to address specific needs such as mining historic datasets for extracting business knowledge. During the last couple of years, enterprises have entered a new era, as they are planning to deploy data-driven systems in almost every aspect of their business operations. In this direction they employ multiple models and algorithms for different applications, yet over a common data infrastructure. Hence, enterprises must monitor the development and deployment of many AI systems, in terms of a variety of properties such as their effectiveness, trustworthiness, security, and economic benefit. This requires a structured monitoring framework, which is commonly known as AI governance.
AI governance relies on a common set of processes for understanding and auditing the AI models used by enterprise. It is aimed at providing a unified, yet integrated approach to scrutinizing the training, the operation and the business benefits of various algorithms. Modern enterprises must create a proper governance framework to ensure the trusted and effective operation of their AI systems.
AI Governance frameworks audit AI models and algorithms across their entire lifecycle. In this direction, they must consider the following aspects of AI models’ development and deployment:
To establish a proper governance framework with the above-listed dimensions, enterprises had better adopt the following best practices:
In the era of hyper-automation organizations will have to deploy, operate and manage many AI systems. This management won’t be effective without proper governance. This is the main reason why companies must develop a proper governance framework as part of their investments on expanding and scaling up the use of AI and its impact on business performance. We therefore expect Chief Information Officers (CIOs) and Digital Transformation Manager (DTM) to include AI governance in their agendas and to consider the above-listed guidelines.
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