The realization of AI initiatives takes place within the AI portfolio. The value section of the AI strategy sets overall priorities, ambition and investment levels for the portfolio. To make this more practical, the AI strategy may also incorporate some exemplary AI use cases. However, it is not the AI strategy itself but the AI portfolio which incorporates and maintains a full and current overview of AI initiatives and use cases. … To develop the value and adoption sections of the AI strategy, AI leaders can use the following activities and questions as guidance (for further details, see the attached AI strategy template):
- Identify strategic value priorities for the AI portfolio**.** What are the levels of ambition with respect to applying AI? Will AI be used mostly to improve existing business, or to extend or even disrupt business? See Gartner AI Opportunity Radar: Set Your Enterprise’s AI Ambition for more information. How much funding should go to each of these ambition levels and in which business areas? How do these priorities relate to business objectives? For example, if the business objective is to cut costs, then AI use cases that impact costs take priority. If it is to improve customer engagement, then AI use cases that support customer engagement take priority. In other words, in which business areas are there the most important opportunities for AI to create real value? In each of these areas, what business goals is the use of AI related to? In which areas can AI be a catalyst for new or currently unaddressed business opportunities or challenges? Which KPIs will be impacted for which stakeholders? What are the key metrics for measuring the value that AI creates? What are some practical examples of AI use cases? Which business objectives and metrics are these examples related to? What is the art of the possible from within and outside the organization’s sector or industry?
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REF: The Pillars of a Successful Artificial Intelligence Strategy