The Story in Your AIs.

By Paul Wiefels, managing director & co-founder of Chasm Group, LLC


So, it begins. The next secular wave of technological innovation. Actually, it’s already well underway. Its sponsors (and beneficiaries) span megacap companies like MSFT, GOOG, NVDA—to promising upstarts in already burgeoning categories, e.g., healthcare, software development, and cybersecurity where you can’t possibly have enough people, time, or bandwidth to identify and repel all the bad guys.

Great stories in whatever form always introduce significant, even existential challenges that the protagonist must confront and overcome in order to win the day. It’s no different when creating successful narratives advancing disruptive or discontinuous innovations. (And I am not talking here about messaging per se.) The challenge is one of overcoming complexity. This manifests in myriad ways, some obvious, some less overt. History shows us that eliminating complexity and the friction that comes with it, paces how people adopt and proliferate such innovations; and how they must be brought to market. In our view, there are three primary dimensions that we believe are linked. Solving for one affects how to solve for the others.

The first is adoption complexity. Put simply, how significant is the impact of this “new thing” such that we are willing to put up with, even embrace, the challenges of initial adoption across the spectrum from purchase to usage? This includes consideration of what it replaces if anything; the significance and impact of the ROI it provides; and many other factors. The antidote for adoption complexity comes through the formation of “killer” applications. These might be singular or numerous. But they are a necessity if a given innovation is to be adopted by a wide swath of customers—from very early adopters to those who border laggard status.

Solving the killer application challenge gives rise to considering how easy or difficult it will be for users to proliferate the use of the innovation throughout a given target market population. This is the dimension of solution complexity. It also extends to the innovation sponsors’ ability to scale production and deployment. Whatever sources of complexity exist for both buyers and purveyors must also be significantly reduced or eliminated. For example, think back to the advent of Apple’s iPod. MP3 players at the time had a significant source of solution complexity in that the music one stored on them was typically sourced illegally or faced other limitations. Music labels were not happy with this nor were the artists. Apple solved the issue by introducing Apple Music, a legal way to obtain a large catalog of music endorsed (reluctantly at first) by the labels. On-premise enterprise software came loaded with solution complexity, most transferred directly to the user. Enter SaaS. Far less friction as enterprises subscribed to the benefits promised, solution complexity now transferred back to the purveyor.

Solving solution complexity informs the third dimension of the triad: marketing complexity. How easy or difficult should the innovation be to buy? You’re thinking “Huh!?”  Yep. If something has a lot of adoption and/or solution complexity, yet is very easy to obtain, online for example, you better have your customer-facing service and/or success teams in place, at scale, and ready to answer the questions that will inevitably follow, e.g., “How in the world do I set this thing up and use it?!” Conversely, making customers jump through hoops to buy something that they understand, can operate, and have multiple options for—like many legacy car dealerships—is sure to engender animus and likely poor customer satisfaction scores. Enter the online car dealerships. There are myriad examples.

When the story of AI reaches its yet unknown ending, the ability of vendors to manage out its inherent complexity will determine whether the ending is a happy one, or something less than that.