Three Phases of AI Vendor Selection for the Enterprise 

Daniel Faggella

Daniel Faggella is Head of Research at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and leading enterprises, Daniel is a globally sought-after expert on the competitive strategy implications of AI for business and government leaders.

AI Vendor Selection

When we're called into an enterprise for our AI Opportunity Landscape research, it's common for me to discover that the reason we've been called in is that the company has (a) already spent millions with vendors they didn't see results with, or (b) they have 3-4 AI pilots underway with very little traction.

Enterprise AI projects fail for many reasons - and most of them stem from a lack of executive AI fluency. Directors and execs start off their AI initiatives with the wrong expectations about the requirements for AI deployment, the wrong expectations about how ROI will be measured, the wrong expectations about AI's realistic range of capabilities.

Our Emerj Plus content - and most of our work here at Emerj is general - is geared towards making leaders "AI fluent." In this article, I'll be exploring a basic 3-phase approach for vetting vendors properly - giving you the ability to save time, and find the vendor partner most likely to deliver on your project requirements.

This ...

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