What the Future of IoT Might Look Like
And where AI and AR fit
The greatest smartphone innovation in 2017 will be taller displays and skinnier bezels. LG’s G6 started it, Samsung’s Galaxy S8 continues it, and if the rumours are true, Apple’s iPhone will cap another year in iterative smartphone innovation. It’s now 2017, almost 10 years since the original iPhone’s launch. After nearly $1 trillion in cumulative iOS revenue, and some 1 billion customers served, the pipeline may have finally run dry. Clearly, the end of smartphone innovation is near.
Naturally a new question emerges: what’s next? The inevitable slowdown in smartphone innovation is the result of a known truth: products improve at a faster rate than people’s needs. The point of good enough has been satisfied.
The maturity of the market doesn’t suggest that there’s no more money to be made here, there’s at least a billion people in developing markets yet to be served. But it does suggest that the battle for supremacy is effectively over. The industry shakeout has occurred — culling Symbian, Windows, webOS, and Blackberry — and the winners have been established. Apple and Google won. Firms that want a slice in this industry either have to leech off the ecosystems that these megaliths have created, or attempt to invent new categories.
The pursuit for new growth avenues will eventually topple this industry equilibrium. Leeching and category invention are often deeply linked. Many of the applications built on top of these existing smartphone operating systems are planting the seeds for the brand new categories that will define our next technology revolution: AR, AI, and IoT are on the tips of everybody’s tongue. As the leechers and trailblazers fill in existing gaps, they’ll find more gaps that need to be filled.
In this emerging age of AR and AI, the gaping hole is finding ways for our technology to understand data and context, and to be proactive. A passive screen in our back pocket won’t cut it, and smart watches are just the start.
Cloud infrastructure, machine learning, and big data analytics are also elements of this wider story. It’s not one or the other, all these pieces are going to be there. But maybe some will be more profitable slices of the pie than others, or maybe some things have to come before others because there are dependencies in play. Does VR need to come first so we gain the technical competencies and discover the use cases for AR? Do elements of an IoT ecosystem need to be built out before the industry can begin leveraging the possibilities in big data machine learning and artificial intelligence?
With this in mind, the question isn’t really ‘what’s the next big thing?’ The real question becomes, what is the starting point? And consequently, who owns the data and control centres? In today’s world where we have no shortage of personal gadgets, the smartphone is the core from which all our other gadgets revolve. Apple and Google own the control centres, and cloud-based platforms own most of the data. At the peak of WinTel, Microsoft’s mistake was assuming the desktop PC would remain the centre of the universe, perennially handicapping the company’s nascent mobile efforts by tying it to Windows.
10 years from now what will be the heart of the technology ecosystem? Will it be wearables, non-tangible cloud services, IoT devices, or will it still be the smartphone?
It’s early days and there are a ton of moving parts. This discussion is just about laying down some thoughts on how all those things might fit together. I’m going to focus on IoT as the anchor here, a topic which has paled in comparison to AI and AR in recent times. The broken promises of the ‘smart home’, and the struggles of IoT companies such as Nest have certainly dealt blows to the credibility of this trend. After all, why hasn’t IoT taken off? The time should be now.
First of all, what is IoT? IoT is the internet connectivity of typically analogue appliances, allowing them to interact, and push and pull data. Naturally, IoT is heavily reliant on cloud services that link these appliances with existing services or other devices, and have them speak the same language. Apple’s HomeKit and Amazon Alexa are attempts to define this language for IoT in the home.
To some degree, the concept of the connected home is clicking. Amazon’s Alexa in particular has found success by becoming a novel home assistant for everyday conveniences, and Apple’s HomeKit leverages the iPhone’s simple and pervasive UI to control a range of IoT elements. But until the concept of the connected home connects to a broader ecosystem or need, it will fall short of its potential.
The potential is great, and of course, easy to understand. Here’s the value proposition: IoT enables us to automate mundane activities of our daily lives with our phones and natural language. It’s easy to envision what this looks like, just watch an ad for Google Home. Artificial intelligence has progressed to a point where natural language recognition is both accurate and reliable, and we have no shortage of internet sensors to tack onto things and mobile devices to interact with them.
But these details are far from the finish line. Even failed products have value propositions that are easy to articulate. Windows Mobile was all of your contacts, emails and productivity from your Windows PC, right in your pocket. On the basis of feature set, it’s actually hard to reason why Windows Mobile didn’t succeed. We know Steve Ballmer didn’t get it.
Although the iPhone’s reign is credited to myriad different factors, I would posit that core to the iPhone’s success was its ability to latch onto existing, and growing ecosystems: namely, iTunes and the web. Through the iPod, Apple had an existing install base of millions of users who owned iTunes media, and were familiar with the desktop client to manage devices. The iPhone tapped into this vast ecosystem by allowing users to get their iTunes media onto their phones in an easy way. The second ecosystem was more profound, that was (is) of course, the web. By building the first mobile web browser that didn’t suck, the iPhone predicated the rise of the mobile web, and eventually the smartphone’s ascension to the centre of our digital lives.
So, what’s the ecosystem for IoT and the smart home? Or to put it even more bluntly, what is the specific need it fills? That stuff is still being figured out, but at this stage, it’s fascinating to see what the three big players in this space — Apple, Google, and Amazon — can each bring to the table. Google and Amazon both have dominance in search and eCommerce respectively, which they’ve built up vast ecosystems for. Imagine IoT solutions in the home that could recognise when a particular item in your home is running low, and immediately place an order through your Amazon account. Or perhaps sensors in your home which recognise when your baby wakes up in the middle of the night and streams lullabies from a YouTube playlist.
This is all just a shot in the dark at what’s possible. Before this happens though, all the hardware and smarts needs to be built out, it’s just a matter of timing.
But that leaves Apple, a company which has built substantial competencies in its own OS and hardware vertical, but no real presence in platform horizontals. That’s what Apple is going to have work through over the next five to ten years: how the company stays relevant in a world where the most importance device might not be the one in our pocket, but the little ones latched onto everything around us, and the horizontal services that they’re built on.
In the enterprise space, particularly in manufacturing and retail supply chain management, the small improvements that can be made through IoT insights can be enormous when working on scales of thousands and millions. What are the possibilities when IoT devices deliver information directly to Salesforce, or SAP, or Dynamics? And who owns this information, and how does it change the deployment of IT infrastructure? But conversations on enterprise are worth their own discussions.
Meanwhile, the interplay between AI and IoT is extremely important. Where IoT gathers all kinds of data in new places, cloud services and technology such as Google’s open source machine learning engine TensorFlow come into play to actually analyse this information and uncover the right insights. Naturally, the more IoT infrastructure grows, the more data can be fed to machine learning engines. The two developments are compatible and will likely grow together.
Whether cloud firms will adopt vertical strategies by insulating their platforms and building out their own IoT hardware remains to be seen. But over time, we would expect that there will be simply too much white space for a small set of firms to fill. Google and Amazon simply can’t build the thousands, even millions of sensors that will eventually digitise the ‘things’ all around us.
What I sense will happen is a replication of the platform and OEM dynamic which has been the bread and butter of the tech world for decades. A few players will control the platforms, and countless third parties will build the IoT hardware that feed them. In this world, the smartphone becomes just another node. And in this world, is there room for an insulated vertical player to capture all the value in the chain as Apple has with smartphones? The pure scale of this next revolution renders this unlikely, but it will be interesting to see.