Looking at AI from a different perspective that proposes many enterprises "lie" about AI deployments almost to present an innovative falour to their brands.

Too many enterprises just do not have the data management skills or resources to deploy AI effectively so these 7 checks are really useful.

Another key point- AI will filter out the important from the trivial and automate decision-making on trivial matters. That lets humans focus their formidable combination of knowledge, intuition based on experience and empathy to make and execute better decisions on behalf of customers.

BUT- are they trained to so so? Typically not and thus AI is poorly utilised. 

Before AI is ever exploited, and assuming you can positively answer all seven points in  the linked article, you must answer WHY you are doing it and WHAT decisions will therefore be made better.

Take insurance. AI is often touted as a game changer in digitally transforming the customer UX and journey for damaged autos. 

  1. Identify a write-off earlier to pay cash settlement faste
  2. Automate damage assessment, quote & repair process for cost-effectively getting the customer back on  the road

Great in marketing material but in reality? The data are: -

  • Incomplete
  • Too little i.e. insufficient

AI is a sledgehammer to crack a nut. The practical answer is to combine the data available, appropriate algorithms and human intuition. The result will be faster, better, and cost-effective. Just look at solutions from Audatex, Xtract360 and 360Globalnet for practical solutions.

That's not to say that AI is not important when it comes to Digital Transformation. It's a strategic priority but for many enterprises they have to get the full technology stack, human and other resources and  skills plus C-Suite vision in place. It's probably a three to five year task to achieve that.

In the meantime focus on what makes the biggest impact this year and next and get your ducks in line to adopt and deploy AI when you can. 

More Reading: -

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