| |JUNE 202219ffering an entire gamut of capabilities to solve complex business problems, Machine Learning (ML) and Artificial Intelligence (AI) are imperatives for business success today. A recent survey reveals 85 percent of businesses are either evaluating AI or already using some basic form of it in production. Most businesses face the same set of challenges while embracing AI: Lack of a strategic view and alignment of needs. Recognizing and establishing use cases. Shortage of skills in the market... How should organizations go about addressing these bottlenecks? How can business and tech leaders adopt AI to its true potential and drive value for the enterprise? Most of these bottlenecks can be mapped to three categories:StrategyBusiness and tech leaders should take a more scientific approach to addressing the two most important challenges: 1. Recognizing the need for AI and 2. Difficulties in identifying use cases. · Explore `Prediction' Opportunity: To recognize the need for AI and establishing use cases leaders should review organizational workflows and break them into tasks. They must analyze the tasks that have a significant prediction component and would benefit from a prediction machine. Next, they should determine the ROI for building a OA 3-PRONGED FRAMEWORK TO ENSURE SMOOTH ARTIFICIAL INTELLIGENCE (AI) ADOPTION IN ENTERPRISESBy Deepak Arora, VP - Technology, Publicis SapientCXO INSIGHTSDeepak Arora, VP - Technology
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