Establishing Measurable ROI Benchmarks for AI Projects – A 5-Step Process

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.

Establishing Measurable ROI Benchmarks for AI Projects

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

 

Setting the right expectations for a measurable return on investment (ROI) is crucail for AI project leaders.

Don't promise enough of the kind of ROI your decision-maker wants (almost always measurable or financial ROI), and the project won't be approved.

Overpromise, and you set yourself up to almost certainly disappoint your client, and ensure that your AI project doesn't get the resources or support it needs to turn into a deployment.

In this article, we'll walk through a process for setting expectations about the measurable ROI of AI projects the ri...

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