If only we had a crystal ball that we could dust off and wave our hands over every time we had to make a strategic decision. A technology séance, if you will, to give us a sneak peek into the future. Should we invest in AI? Will smart homes ever become a reality? Is Industry 4.0 still going to be a “thing” in 2025? Just ask the crystal ball.
I recently met a client from an energy company who asked me to more or less do just that, and offer my predictions about what would happen from a tech perspective in their domain over the next 20 years. Based on those insights, the client said, his company could plan its investments in technology.
Naturally, this question led me to reflect back over the past twenty years of technological change. A little over a decade ago, the iPhone didn’t even exist. People had to navigate their way around town without Google Maps or Waze, and Uber and Lyft wouldn’t come onto the scene for several more years. Snapchat, Instagram, and WhatsApp were all invented over the last decade, and the list goes on. One significant technology, product, and business model innovation after another. If you traveled back in time before June, 2007 when the iPhone was released, and tried to tell people what was to come, they probably would’ve thought you were referring to the plot of a science fiction movie rather than predicting the future. The world is a very different place now than it was then, and nobody saw it coming.
So, how, exactly, can we predict what will happen 20, 40, 60 years from today?
The truth is, I’m not sure if there is actually much value in trying to predict what will happen in the far-off future. I could easily tell you that, by 2079, cars will fly, planes will be fully autonomous, meat will cease to exist, and blockchain technology will be your only wallet. Who knows, why not? I probably won’t even be around then, so I’m not worried about being accountable for my predictions. Most of us are only held responsible for results in the near term, and in the world of technology that is extremely hard to predict.
“I’ll have one in red.” “Sorry, it’s just a demo, come back again next year.”
Anadolu Agency via Getty Images
Why Is It So Hard To Predict The Near-Term Future?
In its purest form, technology is a solution to human problems. The thing about problems is that they are not all created equal. Some may be more important than others, but because solving them will not generate revenue, they may not get the same attention as other problems that hold the promise of greater financial return. These types of undercurrents, or inconsistencies, can cause sub-segments of technology to accelerate and spike, progressing at an uneven pace. Since these are not easy to identify in real-time, it’s also difficult to predict which sub-segments will evolve faster, and by which date they will become market ready.
There are a few key elements driving these inconsistencies:
Industry-Led Investments: When specific industries identify the benefit of a particular technology, they tend to invest in it. For example, a bank or insurance company may have an interest in fraud detection, and may invest in technologies like machine learning (ML) to solve this problem. These types of industry-led investments cause specific capabilities of a broader technology to advance faster. Other segments of the same technology that do not attract industry interest tend to lag behind.
Accessibility-Led Investments: When the foundational development tools for a particular technology, such as neural networks or computer vision, are made available by companies like Google, entrepreneurs have a chance to jump into the game and create new innovations. Once again, we see spikes in certain aspects of technology accelerating forward.
VC-Led Investments: When venture capital firms (VCs) believe, rightly or wrongly, that certain technologies hold the key for exponential value creation, they pour money into this domain, thus accelerating the development.
Use-Case-Led Investments: When technological breakthroughs happen, or new use cases emerge, acceleration can be achieved. For example, take Magic Leap and Microsoft, which are both investing in a broad range of mixed reality (MR) capabilities— “MR anywhere.”. Under this approach, MR will appear in every direction the wearer of an MR headset will look. Now, consider Tilt Five, a soon-to-be-launched tabletop gaming product that provides an MR experience looking at a very defined field of view— “MR somewhere.” So, what will the future of MR be? Is Tilt Five a breakthrough that will define the market, or will the slow grind of Magic Leap and Microsoft’s HoloLens break the path? Will we use MR headsets in the future that can augment any environment, or will we interact with MR next to defined spaces? Or, perhaps a new disruptor will jump out of the shadows “iPhone style” and redefine the market. Hard to tell.
Can anyone please predict the future of Mixed Reality (and make sure that it is more comfortable than this)
The Crystal Ball Of The Tech Stack
So, with these elements at play, how do we predict the near-term future of technology?
We must start by identifying the constraints that help accelerate technology. A few of the usual suspects are listed above. We need to consider which industries stand to benefit from which technologies, which technologies are available for entrepreneurs, and where VC money is being invested. We also need to keep a watchful eye on those “wild card” innovations that will suddenly reshuffle the deck. Most importantly, we need to consider the tech stack.
For any product to work, a robust tech stack is required. Take, for example, an IoT product, for which we will need:
- Sensors to capture the data
- A communication layer to transmit the data
- Cloud capabilities to make sense of the data
- An app layer to turn our data-driven insights into actions
These layers form what is broadly referred to as the IoT tech stack. Without it, an IoT product cannot function.
Let’s take a look at the tech stack of autonomous vehicles (AVs). From a sensor perspective, the battle between radar or LIDAR (or both) has yet to be won. From a communication perspective, the amount of data that needs to be processed in real time is incredible. Edge computing, which can help reduce the amount of data sent to the cloud, and 5G, which is still not widely present, both stand a chance to disrupt this layer of the stack. From a data analytics perspective, some use cases (like highway driving) are possible at the cloud and the edge, while others (like parking at Walmart during rush hour) are still unresolved. Until all of the layers are solved, we can’t even get to the application layer. Through the lens of the tech stack, we are able to uncover many gaps, and bridging these gaps will take time.
The reason I like to use the tech stack for evaluating when technologies will become mature is that it is a simple and logical tool that can reveal quite a lot about the near-term future. It doesn’t require a massive time investment in research. Rather, an understanding of the making of technology solutions, and the state of development of the different stacks. If we focus on the tech stack, we no longer need a crystal ball to tell us the future of technology. We can gain a solid understanding of the near term future of tech, and make the right business decisions.
More about the Tilt Five and HoloLens products mentioned above:
- Tilt Five product review, with Jerri Ellsworth, Tilt Five CEO and co-founder, exhibiting an innovative approach to “MR somewhere.”
- In comparison, HoloLens demo of “MR anywhere.” Not to take anything from MS progress, but it is still about operating dashboards. Instead of screen, now dashboards and controls float in mid air.