Going from Pilot to Deployment with AI – 4 Factors to Consider

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.

Going from Pilot to Deployment with AI

While overt AI "flops" are less common than they were three years ago, the pattern of failure for AI projects is still much the same.

Leadership selects an AI project without a strong understanding of (a) it's long-term value, (b) it's technical viability, or (c) the phases the project will take to go from pilot to deployment.
Project teams operate with sub-optimal data, often without the data science talent they need, and under unrealistic expectations of short-term ROI (as if AI were IT).
The project never comes close to deployment.

Assessing project opportunities and having the right expectations about AI's adoption challenges is paramount to converting pilots into actual deployments.

Especially for firms new to artificial intelligence, it's crucial to demonstrate progress and success with AI early on - in order to win approval, confidence, and additional budget to expand AI efforts productively.

Nothing builds confidence like actually putting an AI application i...

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