AI Integration Challenges – Pitfalls to AI Adoption in the Enterprise (Part 2 of 3)

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 Integration Challenges - Pitfalls to AI Adoption

In this second installment of the "Pitfalls to AI Adoption in the Enterprise" series, we're going to talk about underestimating the integration needs of artificial intelligence and machine learning.
In our first article in this series covered Pitfall #1: Avoiding AI Novelty.
This second installment covers what many of our PhD podcast guests consider to be the biggest hurdle to AI adoption in the enterprise: Integration challenges. Bringing AI into an existing business is a challenging task, and it requires a very specific set of concerns.
Rather than learn these lessons the hard way, I've decided to break down the critical integration challenges of AI:
Pitfall 2: Integration Challenges
We'll begin our conversation here by talking about what we might refer to as how a run of the mill IT integration works. There's no better example of this than something that recently came up at an event where I was presenting. At the time of writing this article, I am just getting back from speaking at ...

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