Whether we ask Amazon’s Alexa to play our favorite song or shout “Hey, Google” before asking the device a question to help our child with their homework, artificial intelligence (A.I.) has been in the spotlight more frequently in the past few years in consumer applications.
In past articles, I have identified the implementation of A.I. as being “helpfully cool”; however, its application in industries of all sorts is exponentially revolutionizing how we both think and work.
Coupled with the disruptive nature of the coronavirus pandemic of 2020, A.I. is now far beyond the novelty it was originally considered to be.
Because of the versatility of A.I. applications and how quickly they are becoming applicable in everyday life without us even realizing it, the business disruption that comes with them is speeding up as well.
Organizations that implement my Anticipatory Organization Model will have tremendous advantage in leveraging the power of A.I. and, in turn, will stay ahead of the curve.
A truly disruptive Hard Trend
This Hard Trend is now not just a future fact, but one that’s accelerating in power and application at a predictable, exponential speed.
While many of us are familiar with A.I. thanks to those aforementioned consumer-oriented devices such as Alexa and Google Home, the fast-developing potential of A.I. is becoming evident, especially after the disruptive year of 2020 and the coronavirus pandemic.
Another component of my Anticipatory Organization Model is the role of the Three Digital Accelerators, specifically, the exponential growth of computing power, bandwidth, and digital storage.
These accelerators I identified as early as the 1980s are what drive digital disruption, and A.I. is heavily reliant on those three, allowing it to take off in disruptive ways never thought possible. This disruption can, in many ways, make or break an organization and its processes.
Given those digital accelerators, many different kinds of products and services, especially A.I.-related, haven’t merely changed their markets or industries, they’ve thoroughly disrupted them and completely shattered the status quo.
Let’s have a look at a couple of different disruptive A.I. advancements that were not only already in motion before 2020, but were drastically accelerated by the pandemic, understand a bit about how they work, and think exponentially about how A.I. can be applied to your organization.
The pandemic certainly made physical contact with humans a difficult and nearly impossible task, as social distancing, mask wearing, and complete virtualization of processes for many organizations were necessary shifts.
Ride-share programs like Uber and Lyft saw a massive drop in their customer base thanks to the pandemic, and for many start-ups working exclusively with A.I. in the automotive industry, this pandemic obstacle became the occurrence they needed to take the leap in transforming public transportation.
Robotaxis are just as they sound, self-driving taxis fully powered by A.I. The functionality behind A.I. in the automotive industry is largely similar to a bat’s sonar ability. The built-in features use a type of sonar to detect danger and obstacles, diverting the vehicle from potential collision.
At the tail end of 2020, Tesla founder Elon Musk promised that in the coming year, there would be at least one million Tesla robotaxis that function in an Internet of Things (IoT) framework, where you use a smartphone app to hail them.
Around the globe, China also released a large network of robotaxis, benefitting the need to slow the spread of the coronavirus from person to person while also keeping public transportation moving.
More efficient operation
Manufacturing companies are not usually the first to implement A.I. and machine learning (M.L.); however, with the acceleration of those Hard Trends thanks to COVID-19, just as many are starting to see tremendous ways in which they can streamline processes and even go remote with others.
COVID-19 disrupted the status quo of many manufacturers in several industries in that not only did human contact have to be limited in a world dominated by physical workers, but logistics changed drastically as well.
But as we bounce back, and as A.I. makes its appearance in the logistic world as commonly as robotaxis and public transportation, A.I. applications make business processes in the manufacturing world far more streamlined.
Human beings cannot work around the clock, but machines can when necessary! Combining A.I. and M.L. with what is being referred to as the Industrial Internet of Things (IIoT), not only can manufacturing happen around the clock with less human interaction, but those individuals who do work during traditional hours can potentially operate remotely as white-collar workers had to during the pandemic and global lockdown.
Capitalize on soft skills
While my Anticipatory Organization Model helps businesses leverage accelerated digital disruption to their advantage, the collateral damage many employees worry about, especially as it relates to A.I. and M.L., is their employability in the industry. What happens if and when humans aren’t needed for tasks that were vital to their job description?
Well, that is where my Anticipatory Leader System for the individual comes into play! Recently, I’ve used it to discuss the importance of understanding your soft skills, or the art side of science. When a computer can program, what will the software engineer do? When a machine can assemble an automobile faster than human beings on the assembly line, where do workers fit in?
My Anticipatory Leader System uses the same principles the Anticipatory Organization Model does to train the individual on seeing the Hard Trends of their industry, think exponentially about them and their skills, and learn how to become disruptors themselves before being disrupted.
There will always be a place for humans in a digital world; as A.I. and machines learn how to do the math, science, and laborious tasks of past careers, humans will fill the sentient, creative side of those tasks.
A robotaxi can drive people where they need to go, but perhaps the once-driver of a taxi cab is now communicating with the person via remote telecommunication, keeping them company during transit or even aiding in a change in plans that an A.I.-enabled vehicle cannot.
How we as organizations or individual employees stay ahead of disruption, especially ones accelerated by the pandemic, is to pre-solve problems before they disrupt with anticipation.