Imagine a smartphone. It’s touted to be the latest and greatest. It has AI features. A virtual assistant you can converse with in real-time. A camera that can recognise objects and optimise settings accordingly. It can even communicate with other similar products to streamline and coordinate your daily tasks. You’d think this phone came out in 2024, right?
Nope. The phone I’m describing is the LG G7 ThinQ, which made its debut in 2018.
The LG G7 and G8 did not meet manufacturer expectations. Despite having true innovations on board, LG’s market share shrank to 2% and the South Korean electronics powerhouse withdrew from the mobile market altogether in 2021.
Can we call what LG did true innovation, even though it flopped? Is an innovation an innovation because it’s new? Useful? A combination of both?
What is an “innovation”?
According to the father of innovation diffusion research, Everett Rogers, innovations don’t really take hold unless there’s an inflection point somewhere along the line. That is, at some point, there’s a slow trickle of early adopters to an innovation, who hopefully have enough social pull and influence others into making the jump. Then, a tipping point occurs, and mass adoption follows. Sales slow as they reach saturation point and laggards finally get “the picture.”
Unfortunately for LG’s mobile division, the Artificial Intelligence “future” of Generative AI, such as OpenAI’s ChatGPT or Google’s Gemini, was another half-decade away. Though we all knew that social media algorithms and certain web automations were using a form of artificial intelligence, it wasn’t “useful” until we could “speak” to it using natural language and have it answer us in kind.
AI of the kind we see today also had its failures to launch. AI researcher Dr. Emmanuel Maggiori in his incredible book Smart Until its Dumb, wrote that “we” already lived through an AI boom during the late 1950s and through to the 60s before interest waned and investment dried up in the 1980s as AI research failed to deliver anything tangible. He calls this “the AI winter”. AI has been around a long time, but it seems we’re only “now” realising its usefulness. Consider the fax machine, which was invented as an Electric Printing Telegraph in 1846. Though improving along the way, the tech finally reached mass adoption during the 1980s, Rogers’ writing “it took over 100 years for fax machines to become an overnight success.” AI – not exactly new. Possibly useful. So, what does that make it?
Innovative doesn’t mean new
An innovation, according to Rogers, must have a relative advantage to what came before, be compatible with existing values, easy to use and understand, well trialled, and delivers observable results.
So, we have to ask ourselves: how much “innovation” today is just bolting on Generative AI to something that we already have? Or, as Maggiori writes in his book, is it completely made up for the sake of appearing innovative? It seems as if some “innovators” took the advice Homer Simpson gave his half-brother Herb: “take an existing product and put a clock in it or something” instead of developing his truly innovative baby-to-English translator machine. Some companies are riding AI hype to inspire massive growth whether they produce anything practical or not. Some see it as a “remix” of the dot com bubble of the early 2000s.
When it comes to observable results demonstrating a relative advantage, Generative AI does seem to be improving performance in certain tasks, such as speeding up predictive analytics and coding. Though AI seemed to catch on like wildfire in 2023, businesses in 2024 are taking a step back and asking how AI can enhance business outcomes and where the value in AI truly comes from.
In sum, business needs to step back, think strategically, and figure out if the “innovation” being touted will improve anything. We can make the future a bit clearer by looking at “innovations” dead on and asking whether they’re able to – or will – return more than what we invest in them.
