Why is AI so useless for business?
I&#x27;m going to go against the flow of most comment here and say that it&#x27;s not always business misunderstanding AI. Bad labeled data and unclear goals&#x2F;expectations sure, but the latter one should be identifiable by a good ML&#x2F;Data scientist, if you have any insight to what you can actually deliver.<p>But most ML&#x2F;Data Science people have no proper understanding of AI&#x2F;ML, and when just traditional &quot;coding&quot; can solve the problem rather than throwing fancy statistical models and buzzword.<p>I&#x27;m not in business nor AI&#x2F;ML, but in Robotics. And as a person in Robotics it&#x27;s always the same experience working with AI&#x2F;ML engineers: They first say they require large amount of data, then give great promises. (but never specific metrics, except maybe a percentage of success) Then they deliver a module that fails outside the <i>perfect</i> scope of deployment(works only in the lab at 1pm). This is ofc never specified in the delivery. Also crucially, it does not give a good indication of failure. The amount of ad-hoc you need to add <i>after</i> the thing is delivered is just staggering.<p>On top of this reality, most ML&#x2F;Data science peoples response to this entire process is to point and blame the data, or the &quot;well you guys is expecting too much from this!&quot; when they had ample time to outline the scope, limitation and requirement <i>before</i> they even started collecting the data.