Video: AI Planning - Principle 2 - Feasibility

In this video, Graeme Cox explains his second principle of planning an AI Strategy - Feasibility.

Setup a call with Graeme

Please submit this form, if you would like to setup a call with Graeme.


So after ideating, and working through all of the top down ideas about what what might be possible and desirable in the organization, we take a look at what is actually feasible for the organization to deliver. That's that's rooted in your data first and foremost.

Not all AI use cases are actually rooted in the availability of large, large amounts of quality data.

But a lot of them are. And the scale of your data, the quality and consistency of your data, and the availability of your data in in the right time scale to be able to undertake a function can be absolutely crucial to whether something is actually possible or not.

And looking at that in a reasonable amount of depth to understand at least as far as being able to understand what is feasible and the kind of scale of cost that will be involved in engineering and developing that data to the point that it could be used are an important part of developing a business case.