Tuesday, October 17, 2023

How Much AI Return from "Efficiency," Compared to "More Revenue?"

Investors and company executives rightly must think about how increased investments in artificial intelligence will produce a return on those investments. In most cases, the current thinking is that applied AI will allow firms to reduce operating costs or boost customer experience. 


That is likely to be the most-immediate form of payback in most cases. 


But there is some thinking that applied AI can boost revenues in some way related to higher rates of customer acquisition, possibly lower churn or higher revenue per account. 


For example, AI is expected to support:

  • Personalized marketing and recommendations that boost sales

  • Product development based on customer insights

  • Pricing optimization based on customer buying behavior

  • Fraud detection and prevention

  • Operational efficiency


Amazon uses AI to personalize its product recommendations and to develop new products, while Netflix uses AI to recommend movies and TV shows to its users.


Spotify and Airbnb do the same for making music recommendations or matching lodging vendors with guests. 


Walmart uses AI to optimize its inventory levels and to improve its supply chain. All those are essentially process improvements. 


Any firm can use AI to analyze product reviews, allowing it to identify product weaknesses or strengths. 


Thinking is less developed on ways AI can be used to create entirely new products. It is one matter to investigate ways AI can make existing products better, boost profit margins or cut costs when creating, distributing, marketing or selling those products. 


The analogy might be the creation of “search” or “social media,” which really were entirely new products. Those were big new categories of products. In most cases, “direct to consumer” e-commerce was not entirely new, but simply a process improvement, even if it radically reshaped distribution mechanisms. 


That is not to deny that such DTC changes upend industry business models. Look at the changes in the video, audio and print media industries over the past few decades, where streaming is displacing linear video; where streaming has displaced physical media; where online delivery has replaced physical content media. 


Historically, most new technologies allowed us to reshape business processes to make them “more efficient” or “automated” or “self provisioned” or “virtual.” And while that is likely to be the case for applied AI, the big new industries and firms will move beyond that, as did search and social media and possibly cloud computing. 


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