Disruptions Aren't Bleak. They're Breakthroughs.

I'm going to go down nostalgia lane and pull a Mr. Rodgers. Hi [LinkedIn] neighbor. I'm so glad we're together again. Today, I want to talk about new ideas. Things that are original. Things that we use our imagination to be creative. That's why today's word of the day is innovative. Let's go down history lesson lane, shall we. Innovation's origins is derived from the Latin word innovationem. Innovationem was first used in the 16th century in the context towards things were a new idea, a new device, or new method. Innovationem is derived from the verb innovare, which was first documented in 1540, as Etymology Dictionary further explains innovare as dating back to?1540.

Why is all this history important when we're talking about innovations changing the world today? Well, when we think of something being innovative, we think of something new. The reality is, being innovative isn't about introducing something new - it's about trying to introduce something better, more efficient, or more effective. Think Iterative. Not innovative.

Breakthroughs come in waves, as visually illustrated below through the History of Innovation Cycles from our friends over at the Visual Capitalist:

It's important to think disruptions as breakthroughs from a psychological lens so as to look at changes as positively benefiting society and yourself vs the alternative narrative continuing to spread like COVID, in that innovation is coming everyone's jobs. It is true that the term innovative is in everything these days. Today, the most innovative thing that everyone is using AI. Is it just me or is everything, everywhere, in every direction entrenched with AI? Every company touts itself as being innovative. With the advent of AI, every company has deemed itself innovative. The word innovative has become wildly overused?to the point that national discussion has become circular, “to be innovative, we have to encourage innovation.” However, despite the overuse, we need to be innovative about our use of the word innovation. We should start talking about innovation as a series of separate skills and behaviors.

The History of Innovation Cycles helps this narrative further by showing which skills were introduced during cycles, for which our behaviors adapted accordingly.

When you looked at each one these waves, they all took years to take shape and adopt with each wave taking long to cycle through. But notice a pattern? Each wave keeps reducing its cycle time with two things in common: (1) advancements in technology and (2) more people to speed up the process. I believe the two are directly correlated. Take the latest two iterations as we are in the sixth wave, which is Digitization and Clean Tech era (Artificial Intelligence, Internet of Things, Machine Learning, Electric Vehicles, Super Computing, Robots, Drones, etc.). Drones and robotics have been industrialized, militarized, and commercialized over the last 25 years so let's focus on the two predominant one's affecting us today: EV and AI.

Let's start with EV's. Tesla released it fully electric Roadster in 2008, some 15 years ago right at the start of this wave. It was novel at first, but realize it's taken 15 years to normalize EV's as an industry standard where every car manufacturer is finally moving to EV's. Why? There were long term investments in manufacturing that the likes of 福特 , 通用汽车 , 大众 , Honda , Toyota Motor Corporation , 日产 and more needed time and money to prove there was a sustainable market and outfit their plants and people to shift. We're 15 years in, so over the next decade, you will likely see a full shift for most automotive companies to go fully electric to complete the projected 25 year cycle from the visual above (I am of the mindset that I don't care how expensive gas gets, I will still want at least one V8 or V12 car in my garage always). It will only be a matter of time where other industries using combustion engines, such as the airline industry, figures out how to fully move in the same direction.

Which brings us to AI. The earliest substantial work in the field of artificial intelligence was done in 1951 by British logician?Alan Turing. Surely a computing and computational enthusiast not unlike the Big Bang Theory's Sheldon Cooper. Turing published his work “Computer Machinery and Intelligence” which eventually became The Turing Test, which experts used to measure computer intelligence. The term “artificial intelligence” was coined and came into popular use. Tableau references 1980 as the first real use of AI with the XCON expert configurator, designed to assist in the ordering of computer systems by automatically picking components based on the customer's needs. For most who think of AI, we jump to IBM Watson as being the first cognitive computer that combined AI and ML becoming commercially available in 2010.

Follow a trend here? In 2023, the number of EV's steadily climbed year over year become slowly normalized so that instead of the population being surprised and saying "where did that come from", the majority of the population was wondering when the auto manufacturers were going to catch up. No surprises.

We've been in the midst of an AI evolution, not revolution, since 2010 but its' been a bit more quiet. According to McKinsey's 2023 State of AI Report on Generative AI having it's breakout year, AI adoption has remained steady at around 55 percent. Steady and getting ready are two different things. Recall back to the my example the automotive industry's approach to adopting EV's. The key different in EV vs AI is that AI is software based, and applying software to a workflow processes that exist today are far less intrusive than having to outfit entire plants and facilities. AI has been around it should be no surprise that a study by SMG found that?77% of businesses are using or exploring AI, with 35% having already integrated AI in some aspect and 42% further exploring AI for additional purposes. The explorations have been novel and niche for almost a decade, but now the technology has caught up allowing businesses the foundation and capabilities to allow AI to generate meaningful outcomes and value. EV's took 15 years to normalize starting in 2008. AI's at 13 years, so expect this year into the next for it normalize and for us, as people to normalize to it as well. Just like Tesla had to build out facilities to outfit EV's, there's one thing I didn't mention yet that will bring this full circle. They needed to hire people. In 2013, Tesla has 5,859 employees. Fast forward to 2020, they had 70,757. In 2021 they grew to 99,290 jumping to 127,855 by the end of 2022. Estimates have Tesla at over 130,000 employees at the end of 2023.

The same thing is now happening with AI, its just happening faster because of the lack of physical hardware needed to affect the workflows and more people (there's over 8 billion of us inhabiting the planet). Companies are out there seeking resources with AI backgrounds. Universities and companies alike are making AI classes and certifications available. Tech.co consolidated sites for free classes from the likes of Google, Microsoft, Harvard, and others can be found here.

Drawing parallels to EV and AI, crypto currencies and blockchain technologies are being heavily invested in a somewhat quiet manner to the mainstream, where some large financial institutions such as JPMorgan Chase, Goldman Sachs and Bank of America have launched crypto trading desks since 2015. The mainstream crypto, Bitcoin, was introduced in 2010, hit $1 in 2011, and became mainstream in 2017 when its price reached over $200 per share. See the trend? We're in 2024 so if we buy into the 25 year cycle, we're 9 years in and likely 5 to 6 years out before our financial systems really start to adopt crypto and blockchain more actively.

If you've thought this article has been about disruptive waves of innovation and technological advancements, then you've missed the point. It's about people. The only reason any of these breakthrough broke through is because people adopted and bought in. Listen, you can't build a better mouse trap without the mice right? AI is designed to help, not hurt, and we the people have a say in it, so I urge you to break through whatever fear based glass ceiling you have self-imposed based on your perception of AI and see what you too can do with it.