Three A's That Lead To AI Transformation

The last few years have been dominated by the concept of shepherding companies through their digital transformation — but now those same companies are just venturing into a brand-new stage of their evolution: the AI transformation stage.

Digital transformation was forced by the rapid expansion of the Internet and the digital economy.  Companies were quickly forced to find ways to engage with their customers through digital channels, which added a layer of complexity unseen in the past.  New systems were required. New technology had to be implemented.  The landscape of brands, publishers and media changed dramatically as a result.  

Many companies have invested deeply in their digital transformation, thus  creating lots of data and increasing opportunities to touch the consumer in a myriad of ways.  

All those touchpoints and resultant data have set up this next phase, where AI is integrated to create new efficiencies for business.  AI Transformation can be summed up by what I refer to as the three A’s: augmentation, automation and application.  



Technology can be layered to surround the people in your organization and improve their productivity.  Think of how Tony Stark is faster, stronger and smarter due to his access to information when he’s in the Iron Man suit.  A regular employee can use AI technology in the same way.  

This manifests in lots of different ways, but they’re not intended to replace people as much as they’re intended to replace the responsibilities of those people, freeing them up to do more productive things with their time.  With AI, any person can be more efficient, more productive and more effective in their roles.

Automation is the second element of AI transformation, where an organization identifies basic processes that can be automated to save time and increase efficiency at an organizational level, beyond the individual.  Think of this as optimization in marketing, logistics, hiring review, etc. 

Any basic type of analysis can be automated, and the output delivered into a business intelligence platform or other system.  If the data sources are standardized, the analysis can be automated, and the enterprise can be optimized to act on the results of that data.

Once you‘ve identified the ways AI can augment or automate your organization, it’s about application.  It’s about putting those ideas into action and activating them across your entire organization (apparently, I love using words that start with “A” today).   

Applying these tools across departments can create efficiency across your organization that hopefully leads you to maximize your workforce and increase the effectiveness of your interactions with consumers.

True automation of website optimization or ad delivery based on customer journey mapping is one example of this.  In this example, you can automate the engagement based on data about your consumers, and your team can leverage tools like Grammarly to increase the accuracy of any responses they write.

These days, regardless of what most vendors say, too much of this is manual or guided by simple rules-based algorithms.  With AI applied through the organization, these are much more advanced and can learn on their own without those rules-based models being constantly updated by humans.

You may or may not be finished with your digital transformation work, but you should certainly start thinking about your AI transformation as a way to create ongoing efficiencies as you continue to move forward.

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