Developing an AI Strategy (Part 1): The Rules of Business Still Apply With AI

Andy Jordan is President of Roffensian Consulting S.A., a Roatan, Honduras-based management consulting firm with a comprehensive project management practice. Andy always appreciates feedback and discussion on the issues raised in his articles and can be reached at [email protected]. Andy's new book Risk Management for Project Driven Organizations is now available.

  Artificial Intelligence   Strategy  

A lot of my clients are looking to develop and implement artificial intelligence strategies. That’s not surprising given the attention that AI is getting these days.

The problem? Because AI is still evolving very rapidly, there is a lot of uncertainty around what those strategies should look like.

I don’t pretend to have the definitive answers, but I do have some thoughts. Over the course of three articles, I’m going to look at three distinct aspects of AI strategy:

1. the planning
2. the exploration
3. the execution

Let’s start with planning.

Business drivers remain key
It is essential for organizations to develop AI strategies. The capabilities of the technology are going to be so disruptive that organizations must get in front of the threats and opportunities if they are going to be able to control how AI impacts their business.

And it’s likely not enough to simply consider AI in the context of existing strategies; there must be something distinct that addresses the capabilities in an integrated way. That is, that there is a consistent approach to how AI will be leveraged, utilized and managed across all functions and business areas.

That said, AI strategy must still align with the organization’s overall business strategy. This is where organizations need to start. Let’s take a step back for a second to explain.…

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