In recent years, all my AI discussions with C-level execs have had a (disappointingly) common theme: they want an immediate solution, with no understanding that there are multiple foundational steps, requiring focus and (often) investment.

Issue/Opportunity ->
Hypothesis statement ->
Data gathering ->
Data cleanse/classification ->
Experiment ->
Model ->
[iterate]
[iterate]
[iterate]
Solution

The 1st lesson from Google etc. is that systems should ban “null data” as a minimum - yet few do.

That, IMHO, is where (human) intentionality comes in.

Having a clear view of the issue, the opportunity, and the end-goal is key to ensuring the people, process and enabling tech are lined up to arrive at the intended destination.

<AI platform> is necessary but never (in and of itself) sufficient to get you there.

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Too many business leaders still believe that AI is just another ‘plug and play’ incremental technological investment. In reality, gaining a competitive advantage through AI requires organizational transformation of the kind exemplified by companies leading in this era: Google, Haier, Apple, Zappos, and Siemens.
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#transformation #futureofai #australia #data #leadersoftomorrow #humancentereddesign #visionary

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