A great number of AI use cases can be achieved with off-the-shelf AI tools, some of which may already be built into the software your organization uses on the day-to-day. Building more custom AI solutions is a big undertaking — and not a one and done undertaking at that; like any digital system, they require maintenance. Whenever possible, organizations should explore how to leverage what already exists, only embarking on a custom solution when tackling something truly unique to your organization and its mission. This module will shed light on how to make that decision between building vs. buying an off-the-shelf solution.
PJMF has not developed content for this module yet, but let us know you’re interested, and we’ll keep you in the loop if/when it’s released.
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How can we ensure that we're pursuing solutions that are deeply rooted in the problem at hand, taking a people-first rather than a tech-first approach?
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How do we think about the data we have or still need, the quality of that data, and the infrastructure required to support a safe and successful implementation?
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From budgeting to building the right team to assessing potential risks, how do we go about planning an AI project?
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The Patrick J. McGovern Foundation (PJMF) is a global, 21st century philanthropy committed to bridging the frontiers of artificial intelligence, data science, and social impact.
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