AI Is Not A Product And What Alexa Taught Us At CES 2017

Note

The following is a post that I drafted on 9-Jan 2017, more than a year ago. Given the reported excitement over Alexa at CES 2018, I thought it would be a good idea to publish it and to see how things have changed in a year. I am actually a bit surprised at how relevant my observations remain today. I have left it as I did a year ago, and hence there are parts that are obviously unfinished.

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One of the more interesting things in tech this month was the presence of Alexa enabled products at CES. Although this seems to have taken quite a few people by surprise, it’s actually quite easy to see how this happened, and why other aspects of an AI enabled interface (answering via Google Graph or voice control of your smartphone etc.) have not seen excitement anywhere near. One critical caveat though is that at this point, we have only seen excitement from home appliance vendors and not from the consumers; at this point, we have not yet seen real demand.

The following is a summary of my thoughts on this.

Who has the capability for a voice UI?

  1. More than a year ago, I wrote a comment on Techpinions that “Amazon, by offering Echo voice to other companies, is essentially making it the new AWS. This could result in even small startups using sophisticated voice technology”. This is essentially what we are seeing at CES. We are seeing many startups and non-tech companies integrate with Alexa to provide a voice UI to their products.
  2. Essentially, nobody needs in-house voice recognition technology anymore to provide a voice UI to control their product. Anybody can do it. Importantly, since it will probably be difficult to significantly differentiate on voice, voice UI itself will become a commodity.

Who needs a voice UI?

  1. One huge problem with AI, and new category products in general, is that very few people need them. Impressive as Google Now may be, people have not yet shown much excitement over an assistant that peeks into your email and notifies you of the few events and appointments that it has managed to decipher correctly. There has been little need for assistants that try to learn everything about you and predict what you may want.
  2. It turns out that the people who wanted a voice UI the most weren’t end-customers. The ones that had the most use for a voice UI were vendors; they have always wanted something new and shiny to lure consumers to buy a new TV, a new refrigerator, a new microwave, etc. The perfect example would be TVs with 3D and 4K, devices that were previous darlings of CES a few years ago, but ended up being duds.
  3. What Amazon has provided is a promising (but yet unproved) solution. It provides hope for the eternal question; how do you get customers to spend a few more dollars on your commodity product? Home appliance vendors have forever been adding small incremental features to lure consumers into replacing their 5-year old device, and to get them to buy higher priced ones rather then their low-end offerings. Wider TVs, 3D, 4K, Internet connectivity, lower energy consumption, SD slots to view photos, etc. Despite being a dud in the consumer market, features like 3D and 4K were actually big topics at previous CESs.

How it adds up

  1. Amazon has basically provided a way to add a voice controlled interface to otherwise mundane devices, with very little effort and investment. Alexa-enabled devices can now tout headline grabbing titles like “AI-powered washing machine” and pretend to be something that’s genuinely useful and innovative.
  2. Importantly, we have to remember that the consumer is completely absent from the argument. The need for thes AI-powered devices comes from the vendors, not the end users. Like 3D/4K TVs, the excitement could be very short lived.
  3. Therefore, we have to keep in mind that this excitement is completely independent of how well Alexa’s AI performs.
  4. More than anything, this tells me how quick adoption of a product can be if you have hit a clear need. Conversely, it shows how hard it is to get the mainstream to share enthusiasm for a product without one. Here, we must keep in mind that AI is not the key because the existence of a need for it has not been demonstrated. The key is the ability to be buzzword compliant with minimum effort.

The implications

  1. One point of discussion is whether Amazon has managed to get a head start that is significant, of whether Google or Apple would easily catch up if and when they open up their ecosystems. As mentioned above, the motive for the home appliance vendors to be HomeKit/Siri or Google Home compatible is very strong. As long as Apple or Google provide an easy way to be compatible, then vendors will most likely rush in just like they have done for Amazon. Keep in mind that making your appliance compatible is probably much easier than developing an independent app, something that the vendors still do.
  2. Regarding the above, it’s also important to note that the replacement cycle for home appliances is very long, hence early leads are unlikely to translate to large share of installed base.
  3. The smart home has hardly taken off, and some pundits have attributed this to the lack of a central control. If this is truly the case, then we might see a surge in smart home appliance adoption, due to Alexa. However, we must also be aware that Alexa compatible device adoption alone is unlikely to be a reliable measure of smart home adoption, unless there is a clear price difference (with 3D TV adoption, even people who did not 3D bought them). We must be careful in how we interpret the numbers.
  4. The broad question here is what AI is really good for, and does the popularity of Alexa at CES give us a hint? Why would people want AI at all, and what level of AI would be necessary to solve the job. Although far from decisive, if the main job of Alexa ends up controlling home appliances through voice, without necessarily inferring or predicting your needs by peeking into your daily habits, email and calendar events, then that would suggest that a glorified, voice controlled macro library is what people want and need. That is, unless the task is complex, humans can tell computers what they need, and their isn’t a clear need for computers to be clever. If this is indeed the case, then Google’s Knowledge Graph and huge repositories of users’ private information may not be as useful as one may think.
  5. AI is already used to determine the best washing conditions for your specific laundry, and current AI may not significantly contribute to that.

AI does not have a job nor does it solve a need. Therefore it cannot be a product. It is only a technology.

Alexa at CES shows how it might be a product, or rather what AI might be useful for. Of course, ultimately the user will decide.

Alexa is something that will help drive sales of high-end commodity products.

A $50 Kitchen Timer

Although cheap kitchen timers can be as cheap as just a few dollars, a premium one that you can use hands free might justify a $50 price tag. That was the only remotely useful use-case that I could find in this article, but maybe that’s enough.

The larger question would be, out of the tens of millions of people who purchased a smart speaker, how many people hooked it up to a smart home device e.g. smart light bulbs, smart locks? Assuming that this is what is going to be hot at CES, I wonder how large the addressable market actually is, which I expect is probably much much smaller than the total number of devices sold.

Smart Speaker Business Models

In a recent tweet, Benedict Evans brings up the point that business models are important for understanding the nascent smart speaker market. This is particularly important given a Reuter’s report that both Amazon and Google likely lost money on these devices during the holiday shopping season.

This brings up the question, what business models are these smart speakers really suited for, and have Google and Amazon exhausted the possibilities? Are there other companies with different business models that might enter the smart speaker market, and be even more aggressive or successful?

Nowadays, if you want to search for perspective, it is a good idea to look to China to see what the Chinese are doing (other East Asian countries are also illuminating). According to a report by Activate, there are quite a few interesting developments. In the chart below, Activate shows that in addition to Baidu and Alibaba which can be considered as counterparts to Google and Amazon respectively, we see the Asian messaging giants – Tencent (WeChat), LINE and Kakao getting into the game. What’s interesting is that these messaging apps are not just for messaging, but are actually portals to a whole variety of services spanning ride-hailing, deliveries, music streaming, digital payments and more. This means that without plugging in third party apps like how Amazon is doing with their “Skills”, WeChat, LINE and Kakao may be able to provide a battery of useful services that could be better integrated into the voice UI. They would also be in a better position to monetise directly from a variety of services compared to Amazon which only monetises through shopping or Google which doesn’t yet have a clear monetisation strategy yet.

Therefore, it seems that the East Asian tech companies have a better business model for Smart Speakers than any of their US-based counterparts. US customers are reported to use Smart Speakers only for very basic tasks, but is it possible that East Asian users will soon adopt more complex use-cases, simply because the better matching business models will encourage the services to be much better, more varied and more integrated. Who knows? If Smart Speakers turn out to be really successful, they might turn out to be the vehicle on which Chinese companies will finally penetrate the US market (although there might be significant national security issues with having Chinese ambient microphones in US households).

Amazon’s Echo Strategy

I have read over the Internet that some pundits are estimating that Amazon sold tens of millions of Echo devices – much more than their closest rival, Google’s Home.

Impressive as this may sound, it is not the first time that Amazon has used a strategy of dumping a cheap/subsidised device onto the market with the goal of winning market share early on in the game. The original Kindle Fire tablet that was introduced in 2011 shared the same strategy and was also a hit during the holiday shopping season, topping Amazon’s best seller charts as well. The Kindle Fire never became dominant though.

The lesson that I would learn from this is that flooding the market early on with cheap devices will not win you a strong position for the future. The tech market constantly evolves and products reliably get better and better each year, almost like clockwork. Even though smart speakers may look completely cloud-dependent with very few requirements for local hardware, I can reliably predict that in the next few years, this will no longer be the case. If the market for smart speakers persists (which is by no means a given), they will for example at least evolve to incorporate some local AI features to allow them to become smarter while maintaining a certain level of privacy. Cheap devices that are a few year’s old and do not have these improvements will not provide any kind of significant moat, and customers will be eager to switch to the new ones.

Thoughts on Maps

A few thoughts on Maps, in particular Google Maps and Apple Maps.

Google Maps was not the first digital maps solution nor even the first cloud maps solution. However, they have continuously refined the product adding information that they have gathered using high resolution satellite images, cars that roam the streets, and also local business information that they acquired through either partnering, web scraping, user-generated content and other means. Furthermore, based on the assumption that self-driving cars of the future will rely on maps that vastly more information intensive than the ones that we typically use today, having such high-quality maps is predicted by many to be a huge advantage when such technology becomes mainstream.

There are some problems with this approach though. One is sponsorship. Given that Google generates the vast majority of its revenues though advertising, it is highly probable that they will try to more aggressively monetise Maps in the not-so-distance future. This will most likely be through their integration of local business information, and by preferentially suggesting their sponsors’ businesses to their users, instead of simply listing in order of relevance and proximity. This may negatively impact the user experience in a way that has parallels to how Google has modified their Search results to preferentially show either their own services or sponsored products, relegating the more relevant organic search results to less convenient positions near the bottom of the page. It may also spark anti-trust concerns (and indeed already has) as this activity can be seen as an abuse of their dominant position on Maps to promote their own local business services.

Another is that the assumption that high-resolution maps are essential for autonomous driving will not last forever. If and when autonomous systems become as intelligent as human drivers, then they will no longer need such detail. They should be able to drive themselves based on the abstract and rudimentary maps that human drivers have relied on for decades. Therefore when AI becomes sufficiently sophisticated, these high-resolution maps will become mostly unnecessary and an overkill. The advantage of high-resolution maps will only last while autonomous systems are still much dumber than humans, and after that, their high costs of maintenance will make them more of a liability than an asset.

I point this out because there are apparently some who think that the current superiority of Google Maps compared to say Apple Maps provides an insurmountable moat for the future. While this may be true from a pure data volume and accuracy perspective, one should keep in mind that the disruptions that we have seen in the past decades are often those where the incumbent maintained an advantage in performance or sophistication, but nonetheless lost because the difference no longer mattered.

Android Wearables

Two and a half years since its introduction, Apple Watch is seeing increased momentum as market analysts suggest both rising market share and significant growth in sales. Android Wear on the other hand has not been so fortunate with decreased attention from both Google and their hardware partners.

It is one thing to say that Apple has won this first round of the wearables battle. However, it is still very very early in the game. The larger question is what will the landscape look like when wearables reach say 50 percent market penetration, because it is only until then that the winners will become so consolidated, entrenched and seemingly invincible. Before that, markets tend to remain a battle among many where anybody could win the next day.

We know that Apple has continued to refine the Apple Watch. Notable progress has been made in both performance and battery life. Recently, it has become possible to fit LTE connectivity without making the device unmanageably huge. On the marketing and value proposition side, Apple has shifted away from luxury and has moved towards fitness and health. On top of this, they are increasingly using AI to surface relevant information on the small screen, and making small but significant UI tweaks. As a result, we are quickly approaching the point where the value of a wearable would become easy to understand and widely recognised.

On the other hand, Apple still refuses to link the Apple Watch to Android smartphones. The only way to enjoy the Apple Watch remains to own an iPhone. This will create a gap in the market where Android users will increasingly want to own a good smartwatch, but cannot find anything that is compatible with their phone. This gap will only widen in 2018, as the Apple Watch enjoys further success.

OEMs will rush in to fill in this gap. With the lacklustre progress in VR headsets, drones and other gadgets that distracted them for the last couple of years, they will come back to the device that Apple has demonstrated a market exists for. I predict that in at least the later half of 2018, we will see hardware OEMs come back to smartphones.

Google’s attention is a bit more difficult to predict. They are preoccupied with AI and following Amazon’s lead in smart speakers. If so, we might see improved Android Wear hardware, but very little progress in the OS.

From my point of view, it is inevitable that Android users will start to want to have an Apple Watch equivalent. What I’m not sure about is whether their needs will be satisfied by Android Wear or by Samsung’s Tizen, but the fact remains that a significant chunk of the 80% of total smartphone users who don’t have an iPhone, will want a nice smartwatch too.

Why Does Google Collect Personal Data?

DuckDuckGo has this to say.

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Let’s think about what this means for a second.

  1. If DuckDuckGo can make enough money to turn a profit, then imagine what Google could earn even if they did the same as DuckDuckGo. Given Google’s vastly larger resources, reach, brand and advertiser relations, they might even be earning as much as they do now.
  2. Personal information collection is most useful in the cases where the user has not explicitly expressed intent. For example, personal information can be used to choose which ads to show a user in a banner ad or a feed. Since the user will already have provided intent in a search, the additional benefit of personal information is actually quite small, as demonstrated by the solidness of DuckDuckGo’s revenues.
  3. Google makes money most off search. Their display ads (AdSense) are barely growing and only a small fraction of total ad revenue.

Apparently, Google could be almost as profitable as it is now even without personal data collection.

Then why do they do it? What would happen if certain regulations like the GPDR come in effect and outlaw rampant data collection? What would happen if Apple continued to improve its privacy protecting features and prevented Google from collecting this?

DuckDuckGo shows us that Google’s revenues might not be harmed at all.

Bottlenecks and Google’s Acquisition of HTC’s Design Team

It has been reported by IDC that Google’s Pixel phones sold only about 2.8 million devices since launch a year ago, which is less than 1% of the total market, and totally unfitting for a company of Google’s wealth, dominant position and brand recognition.

It was not the appeal of the phone, the hardware, the software, nor the integration of the two that caused mediocre sales. Indeed, the Pixel phone was met with rave reviews and was sold out at least during the early launch period in the places where it was sold. Instead most people believe that it was the meagre supply and the dearth of distribution channels that made it very difficult for people to get hold of them.

If this is true, then what Google needs to do is to fix this bottleneck. It needs to fix manufacturing, component procurement, distribution and marketing and not the design of the phone. It needs to make sure that people can purchase them without undue difficulty. If Google can manufacture tens of millions of phones and make them available through the regular channels, then they will have a winner.

In short, instead of purchasing the hardware design division of HTC which will probably not help the supply and distribution issues at all, Google should hire people like Tim Cook, Phil Schiller and Eddy Cue.

Thoughts on AR and Smartphones

Apple’s recent announcement at WWDC 2017 of ARKit has suddenly sparked a new interest in AR, and just a few days ago, Google responded with their ARCore API which does basically the same things. These APIs promise to bring sophisticated AR to all owners of compatible smartphone, dramatically enlarging the addressable market. This has excited pundits and developers alike, and it is now very likely that we will see AR breaking out of the early adopter market and into the early majority.

I would like to jot down my thoughts on this, regarding how innovation tends to happen, and also regarding how this affects the smartphone market as a whole.

The innovation trajectory

Innovation usually starts out as basic research or a new invention somewhere in a lab setting, with specialised and extremely expensive equipment. Then it becomes a specialised instrument that is somewhat cheaper, but still  very hard to use, catering only to the enthusiasts. Finally, it becomes cheap and easy enough to use for the majority of the market, leading to an explosion of usage.

If you look at the PC market for example, it started out when computers like the ENIAC were first invented. Then after revolutions in semiconductors, the computer became cheap enough for enthusiasts to own and tinker with, but still the people who used them were tinkerers. This was the era of the Apple II, Commodore and Amiga. Then as the IBM PC and clones came out, the price came down whilst performance improved dramatically and application software became available, making the PC both useful and affordable thus bringing it into the mainstream.

What we are seeing with ARKit very much mirrors this. We started out with work that was done in the labs, and we recently started to see implementations that require special headsets and powerful PCs connected to them. It was clear at this point that these devices would not go to the mainstream, and the developer community in general did not yet think that it was a market worth pursuing. With ARKit, we are likely to see an IBM PC moment where AR goes mainstream on devices that are affordable and where the developers are also excited to reach large audiences.

One interesting thing to observe is, although the innovation in the lab tends to follow a steady path, the introduction into the mainstream can feel very abrupt, caused by new products being introduced into the market. ARKit is one of these examples. Windows 95 is another. So is the iPhone of course. Sometimes the company introducing the product if far ahead in technology, but this is not necessarily the case. Looking at Windows 95, one could argue that you could be technically behind, but still make a huge and abrupt impact to the market. Judging by how quick Google was to introduce ARCore, it would be fair to say that Apple’s ARKit team was not also necessarily ahead of Google’s, but simply had the right marketing priorities in place.

Implication for smartphone sales

Until very recently, the general narrative was that innovation in smartphones had winded down, and that there was increasingly little to differentiate the new high-end flagships from the models from previous years, or those from mid-tier vendors. However if ARKit and ARCore become mainstream and are adopted by major developers, this changes the whole game. Apple’s ARKit reportedly only works with A9 chips and above, which means that any models prior to the iPhone 6s are not eligible. The iPhone 6 which was introduced in 2014 will not be able to run ARKit apps and neither will the iPad Air 2 (also introduced in 2014). The situation on the Android side is even more dire (as usual) with only the Pixel (introduced in late 2016) and the Samsung Galaxy S8 (introduced in 2017) being eligible to date. Therefore these two platforms may become a strong differentiator for the newest and greatest models, and drive customers who would have otherwise have been content with an old or midrange model to look upmarket.

This has quite a few implications.

  1. Since we know that the high-end smartphone market is generally dominated by Apple and Samsung, this trend will strongly favour these two companies.
  2. Regarding the iOS vs. Android balance, in the high-end (dependent on country) this often is tipped towards iOS. Therefore, we might see a rise of iOS market share.
  3. The interesting thing is that since ARCore currently only supports the Pixel and the Galaxy S8, and since sales of the Pixel are minuscule to date, in reality the vast bulk of ARCore capable smartphones will be Samsung models. As a result, depending on how Samsung plays its cards, it may be possible for Samsung to exert a huge amount of power over Google. Samsung might customise or add proprietary features and APIs to ARCore that would take advantage of the specific hardware on their devices (which might be Samsung silicon), and since the bulk of the market will be Samsung devices anyway, the developers might bite this time. Samsung has been flexing its muscles looking for a chance to break away from Google’s control for quite some time (Tizen, Samsung Pay, security features, etc.), so it would be interesting to see how they plan to take advantage of this situation.

According to Clayton Christensen’s theories on integration and modularity, markets where customers are still looking for innovation should generally favour integration due to the capabilities that this makes possible, and in the smartphone market, the integrated players are Apple and Samsung (Sony is also interesting in that it is integrated around the hardware that matters most – the imaging sensors). It will be interesting to see how this all plays out.

Predicting Technology Adoption

Today we see many new ideas and product categories being introduced into the market. We see smart speakers, AI assistants, self-driving cars, wearables, VR headsets, smart homes and many more. Not all of these will be successful and become a part of our future lives. Surely some eventually will, but only after many years of mediocre sales mainly as an enthusiast’s toy. Others will become instant hits, and will be used by the majority of people within a decade or even shorter. Despite all of these sharing a common early enthusiasm, the eventual fates will be very different, and predicting which trajectory each product category will take is not an easy task. However there are some frameworks and theories which we can apply, so here, as an excercise to test my own understanding, I will try to do just that.

Smart Speakers

This is a very interesting product category to test and apply the Chasm theory of Geoffrey Moore and the Disruption theory of Clayton Christensen.

The Chasm theory applies to new category products that require customers to learn and change their behaviour. Essentially, the Chasm theory states that there is a very wide divide between the early adopters and the early majority, due to the lack of connection between these two different types of customer. The early adopters do not act as reliable references for the early majority, and hence technology diffusion cannot rely on word-of-mouth. Thus a deliberate and focused strategy is required to bridge this gap. On the other hand, Disruption occurs when the core appeal of a preexisting product that caters to advanced users is made available to a wider audience through technology or business model advancements. As a result the market share of the preexisting product is significantly reduced (hence the word Disruption), often not necessarily by stealing the preexisting product’s customers, but instead dramatically increasing the size of the pie. Often in Disruption, the benefits of the preexisting product will already have been defined and will be very apparent to the new users, and so there will not be a Chasm to cross. This can make adoption very rapid.

In the smart speaker market, and with the introduction of Apple’s HomePod, we will witness both of these theories simultaneously at work.

For the Amazon Echo and Google Home products, we will see the effect of the Chasm. Both of these products stress the AI assistant features which are new and without precedent in the market. Therefore the companies will struggle to define the must-have value proposition, and to educate consumers as to why they should own one. Geoffrey Moore advocates a whole product approach to overcome this, something that neither company is particularly known for. I therefore predict that both these products will seriously struggle to be widely adopted.

On the other hand, we see Apple’s HomePod taking a more Low-end Disruption approach. Instead of touting AI assistant capabilities, the HomePod takes aim at high-end audio and making that accessible to people who would appreciate high-quality sound, but who are unwilling to invest in the learning and the equipment. Therefore, this approach will not experience a Chasm. Potential customers already know what they are getting and do not need to be educated on why they would enjoy good sound. All they need to decide is when they are going to save up, and therefore we are likely to see a much faster adoption rate with this marketing focus.

As a result, my prediction is that the HomePod will be a hit akin to the AirPods, easily surpassing Amazon Echo sales in revenue and even units. As a result we will see both Amazon and Google changing direction and copying Apple’s approach by making speakers with at least acceptable sound. The smart speaker market will rapidly expand as a result, but only because the marketing approach is not about the AI assistant capabilities but the high-quality music.

Self-driving cars

Self-driving technology is also likely to follow a Chasm trajectory. Without a preexisting product with a similar value proposition, people will have to be educated on the benefits, especially if regulations require that the driver cannot fully delegate the role of driving to the AI, and must be available to intervene at any time. We will see a lot of early adopters, but for a long while, that is likely to be all. Even if full autonomy becomes a reality soon and regulations allow the computers to work without human supervision, I am not convinced that many people will immediately recognise the benefits since there is no preexisting market.

Wearables

This is product category that we know is in the Chasm. The benefits of the Apple Watch for example have been hard for even Apple to define, and consumers have yet to be educated of the benefits. Apple is certainly the most experienced company when it comes to crossing the Chasm (it was the company that succeeded in popularising the mouse and the GUI), but still it will take time.

The problem for wearables is that there is no preexisting product to disrupt. For example, except for a very limited number of people, tracking your heartbeat is hardly necessary regardless of how expensive or complicated the devices may be. Notifications on your wrist is also something that most people cannot immediately grasp the benefit of. On the other hand, it is also obvious that with only a minuscule screen size, a watch cannot replace the current day smartphone, no matter how powerful it may be or even if it is connected to an LTE network. Without a preexisting product, it’s very hard to understand what a wearable is good for. It is difficult to understand what benefit it can provide to a customer.

Remember that Apple initially positioned the Apple Watch as a fashion item and a high precision timepiece. The significance of this strategy was that they adopted the value proposition of a preexisting product, which enabled them to connect to customers who were not typical early adopters, thereby speeding up adoption and leaving Android Wear in the dust. Also note that while the regular smartphone manufacturers like LG have recently decided to wind down their smartwatch efforts, traditional watch vendors have started to do the opposite. Regardless of whatever tech is included in the product, at this early point in time where most consumers have no idea what tech can do for them, the value proposition of SmartWatches remain mostly the same as traditional ones and therefore the traditional vendors are the ones that have a story to sell.

Smart homes

Again, this is a product category with no predecessor. Even if you were rich enough to employ a maid or a butler, I suspect switching on the lights would not be typically something that you would do via voice commands. What has been much more critical and aligned better with what people typically hired maids for, was cleaning up and vacuuming the floors, something that Roombas do quite well without any need for a voice controlled “smart” UI. This is why we have seen pretty rapid adoption of these vacuum robots whereas Smart homes are still very much an enthusiast’s toy.

Smart homes will predictably hit a Chasm. The benefits are not clear and therefore only early adopters will buy these things. This will continue to be the case for at least several years. Early majority customers will not understand the benefits without a whole product strategy around a key use case, whatever that might be. Adoption will take a long time, if ever. On the other hand, we will continue to see innovations that use computer, sensor and software technologies to make household chores easier and quicker to do. It’s just that switching on lights is not one of those chores that is a recognised burden on our day-to-day lives.

Summary

The key framework that I’ve used above is to first identify if there is a precursor to a new product category and to see if that has already made consumers aware of the features and benefits. If so, and if the new product has the potential to dramatically increase the market, then I predict that we will see rapid adoption (whether its will be Disruptive or Sustaining depends on whether the incentives to pursue the new product aligns with the business models of the incumbents). Otherwise, we can expect the new product category to follow the technology adoption life cycle and to hit the Chasm. Since the Chasm can be overcome with a whole product strategy, whether or not the market players have experience in this is key to adoption speed.

With this framework, we can predict the rapid adoption of smart speakers by virtue of Apple’s high-quality music strategy, the relatively good adoption of smart watches due to Apple’s experience in whole product strategies and marketing, and the slow adoption of self-driving cars & smart homes due to the current lack of either.

It is also important to note that the key players during the early adopter phase are not necessarily the ones that will make it through to the early majority phase. The Commodores and Amigas of the early PC market did not thrive when PCs became mainstream. Likewise, it is a fallacy to assume that the companies that are currently “winning” in smart speakers and self-driving cars or even Artificial Intelligence in general will enjoy their early lead as the market goes mainstream. More likely than not, other companies that are better positioned for the early majority market and the specific use cases will take it from them.

Out of the markets that I have described here, the smart speaker market is the one that is most likely to see significant action in a year or two due to Apple’s fresh approach. I expect to revisit this post and review my predictions mid or at the very latest late-2018. Other ones will probably still be stuck in the early adopter market and it will be harder to say whether my predictions were right or not.