| Summary: | Summary: This paper presents the “CDAC AI life cycle,” a comprehensive life cycle for the design, development, and deployment of artificial intelligence (AI) systems and solutions. It addresses the void of a practical and inclusive approach that spans beyond the technical constructs to also focus on the challenges of risk analysis of AI adoption, transferability of prebuilt models, increasing importance of ethics and governance, and the composition, skills, and knowledge of an AI team required for successful completion. The life cycle is presented as the progression of an AI solution through its distinct phases—design, develop, and deploy—and 19 constituent stages from conception to production as applicable to any AI initiative. This life cycle addresses several critical gaps in the literature where related work on approaches and methodologies are adapted and not designed specifically for AI. A technical and organizational taxonomy that synthesizes the functional value of AI is a further contribution of this article. The bigger picture: Artificial intelligence is enabling new opportunities for value creation in organizations, industries, communities, and overall society. However, exponential commercial investments in the private sector should not overlook the public interest and social value of this emerging technology powerhouse. The world’s superpowers are also competing for leadership in AI and the contentious pursuit of artificial general intelligence. Collectively for commercial, social, and national interests, as well as internal and external stakeholders, it is vital to know, observe, understand, apply, adapt, and even critique an inclusive, evidence-based approach to conceptualize, assess risks, design, develop, and deploy an AI solution. This article presents the CDAC AI life cycle, a comprehensive approach that addresses and accounts for all challenges from conception to production of AI.
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