Category: Analysis

Samsung just hosted a press conference in Korea to share the findings of an investigation into what caused several Galaxy Note7 smartphones to catch fire. You can find all the details of the findings here but, in summary, there were two distinct battery issues, from two different manufacturers, that lead to the positive and negative electrodes to touch.

Getting to the root cause of the issue was paramount but what we learned from this process has ramifications, not only for Samsung, but for the industry because Lithium-ion batteries are not going away anytime soon. The actual investigation process Samsung went through over these past few months would have been quite difficult for a manufacturer without Samsung’s scale, capital, R&D facilities and work force. Dedicating 700 researchers to evaluate 200,000 smartphones and 30,000 batteries in a newly built testing facility is dedication.

Of course, a lot was on the line here for the world’s leading smartphone maker. Trust of both users and employees was at risk and winning that trust back was paramount.

Winning Back Trust that Samsung will Continue to Innovate

In early October, we at Creative Strategies conducted a study to assess the US smartphone market. Among the areas we wanted to evaluate was the impact, if any, the Galaxy Note7 incident had on the brand’s smartphone market. We were bullish then, and we are bullish now, that Samsung will recover from the Note7 recall. Only 28% of US Android owners said the Note7 caused them to have a more negative opinion of the Samsung brand. Numbers were even lower among Samsung owners.

Consumers are generally quite forgiving and have a relatively short memory. The car industry has seen several recalls over the years, yet consumers continue to buy. The mobile industry has also seen recalls but nothing to the extent of the Note7. Of course, what made the Note7 such a test case is how passionate its users are and how unwilling they were to give up their units, pushing Samsung and carriers the extra mile to get the phones back.

Samsung was quick to take responsibility and step into action. Communication is where the smartphone leader could have done with more clarity. Whether due to cultural differences in communication styles or due to having the complexity of bringing together the Consumer Product Safety Commission, carriers and retailers, Samsung’s messaging was not as direct as it could have been. Digital messages, however, were pretty clear, from warnings being displayed every time the phone was charged to limiting the charging capacity of the phone to ultimately bricking the phone.

Samsung, like any vendor in every sector that has ever had a recall, cannot promise its products will never again suffer from a malfunction. What can be done, however, it to show the necessary steps have been taken to limit the chance of that happening again.

What is even more important when we are talking about a market leader, especially one that has gained that position by adopting new technologies early, is to show their innovation streak will not be limited by fear. Samsung must show consumers they have set in place checks and balances that will allow them to continue to bring new technology, new designs, and new features into the market in a safe and effective way. The new 8-point battery safety check Samsung will implement going forward is an important step in recognizing that innovation should also come to QA, testing, safety and manufacturing processes.

A Market Leader Acting like a Leader

The fact that made the Note7 recall also unusual is the cause of the issue involved several parties: Samsung and two battery suppliers. While we do not know the names of the suppliers, it would be safe to believe they are not exclusive Samsung suppliers. The use of Lithium-ion batteries is also not limited to Samsung or these two suppliers.

Samsung’s President of Mobile Communications Business, Mr. DJ Koh, stated during the press conference that, during in the investigation, the researchers filed several patents in battery technology, patents that will be shared with the industry. We would need more details to understand the significance of these patents but this is the kind of action we would expect from a market leader, especially one that has a pretty substantial battery business.

Despite the many stories that broke on Friday about Samsung putting the blame on its suppliers, I did not hear that in the press conference. Although I am confident Samsung will require changes in the QA process implemented by its supplier, the focus of the messaging was centered on the changes Samsung will implement going forward, including the appointment of a battery advisory group. As much as there is skepticism around how two different suppliers could have two independent battery issues, I do not believe Samsung cut corners in bringing the Note7 to market. As the industry pushes more designs and features and as users push the capabilities of these devices, making sure all that can be done in a safe manner is paramount.

Innovation needs to involve all aspects of the production process and Samsung is making this point very clear. While adding steps to the process adds costs and time, I expect Samsung to be able to integrate the new steps without adding considerable development time or costs on to new products.

What is Next?

I had initially thought Samsung should move on from the Note franchise and deliver a different product with similar capabilities. After months on hearing countless airport announcements referring to the banned phone as the “Galaxy Note7”, “a Samsung phone”, “the Galaxy phone” and anything in between, I no longer think the Note8 would suffer as much as I initially thought. Better put, anything that will come after the Note7 will equally suffer whether it is related to it or not.

Samsung apologized, provided answers and solutions. What remains to be done is to make sure users who returned their Note7 receive the phone they want and a little extra love from Samsung. If indeed there will be a Note8 on the market in 2017, there is a lot Samsung can do to butter up those users from incentives on upgrades to limited editions to early access, etc.

While I can already read the headlines referring to the next Galaxy phone as “the one that hopefully will not blow up” or “not as hot as the Note7”, I am hoping we will move on — like most consumers will.

This week, I attended the first-ever AR in Action conference at the MIT Media Lab in Cambridge, Massachusetts, where an extensive list of current (and likely future) tech luminaries talked about the past, present, and future of Augmented Reality. There are plenty of skeptics who doubt the viability of AR and Hollywood-produced visions of the technology set an awfully high bar. I’ve long felt AR will become a crucial technology; after spending time with this group, I’m even more convinced of this. It is not a matter of if, but when.

John Werner, known for the TEDxBeaconStreet events in Boston, orchestrated AR in Action so that the talks, panels, and demonstrations were all short and highly targeted. As a result, in the span of two days, I saw more than a dozen current and emerging use cases for AR, from both the academic and corporate worlds. There was much discussion about the potential ramifications of AR across numerous industries and there were many technology demonstrations. Finally, I had the opportunity to test out the segment’s hottest new hardware: the Meta 2 (it did not disappoint).

Frankly, the volume of information I absorbed will take weeks to process, but a few key takeaways follow.

Plenty of Companies are Already Testing AR
Last year I wrote about an IDC survey that showed US IT decision makers were already looking at AR for their business. One of the key platforms for commercial AR is Vuforia, which PTC acquired from Qualcomm in late 2015. During the conference, PTC’s CEO James Heppelmann talked about the intersection of the Internet of Things and AR and noted that PTC now has thousands of customers in active pilots of AR technology, primarily on smartphones and tablets. PTC also says more than 250,000 developers are using Vuforia. During day two, PTC’s Mike Campbell showed how to create a working piece of AR software—tied to real world object (in this case, a coffee maker)—in the span of about 15 minutes.

A Few Organizations are Moving Beyond Pilots
Patrick Ryan, the engineering manager at Newport News Shipbuilding, discussed the rollout of AR at his 130-year old company. At present, the firm has completed over 60 AR industrial projects and it is currently working on the rollout of permanent shipbuilding process changes using AR. On stage, Ryan showed a video and talked about using AR to facilitate such seemingly mundane tasks as painting a ship. Mind you, we’re talking about painting aircraft carriers. NNS workers are using AR on connected tablets to visualize parts of the ship before they’re completely built to eliminate errors and decrease waste during the process.

During the discussion on AR in museums, the panel—Giovanni Landi, Rus Gant, and Toshi Hoo—noted museums have been using augmented reality, in the form of audio guided tours, for decades. Many museums have begun experimenting with head-mounted AR to bring staid museum exhibits to life for visitors. Panel members noted that, as the prevalence of mobile AR increases, with more visitors walking in the door with capable devices, the opportunities to utilize the technology will also increase. One of the key ways they expect to use AR in the future is through the digitization of rare objects, which will allow museums to “show” a far larger number of items than can be physically displayed to the public.

AR is More Than Just Visual
Numerous speakers talked about the fact there are more ways to augment reality than through visual systems, including auditory and touch. Intel’s Christopher Croteau, GM of Head Worn Products, talked about his company’s product collaboration with Oakley. The Radar Pace is a set of glasses but there is no screen—all interactions occur through voice commands and audio feedback. The glasses, introduced in October, provide real-time feedback for runners and cyclists without visually distracting them. In addition to a spirited talk on the potential of AR technologies, Croteau also presented Intel’s forecast of the market stretching all the way to 2031. Like most forecasters, Intel sees the near-term opportunity for AR in the enterprise. But, by 2027, it predicts consumer shipments will move ahead of commercial and, four years later, the former will out ship the latter by a 4 to 1 margin.

The Right Interface is Crucial
There was a great deal of discussion about the challenges (and folly) of bringing legacy interaction models to AR but not a lot of consensus on what the right approach should be. One thing is clear: hand tracking and voice technology are both likely to play crucial roles but both have a long way to go before they’re ready for mainstream users. The panel on haptics was also enlightening, with executives from firms such as Ultrahaptics and Tactai discussing the critical role they expect touch to play as AR evolves.

More to Come, Exciting Times
The downside to an event like AR in Action is a person can only attend one track at a time (there were three running concurrently on both days). The upside is event organizers recorded everything, which means, hopefully in the near future, I will get a chance to watch all the tracks I couldn’t attend in person. Just as important, Werner made it clear this was just the first of what he expects to be many meetups of this kind, which I think is a good sign for this nascent but incredibly important market.

Amazon’s Alexa voice assistant was clearly the star of CES this year. No single consumer electronics device dominated coverage but lots of individual devices incorporated Alexa as their voice assistant of choice. The announcements ranged from Echo clones to home robots to cars and smartphones. It was clear Amazon had entirely captured the market for voice platforms. Only one or two integrations of the Google Assistant were announced and those are both future rather than present integrations.

It would be easy off the back of all this to say Amazon had won the voice assistant battle once and for all but I actually see two possible futures for Alexa, with very different outcomes for Amazon and its many partners.

Future 1: Amazon continues to dominate

The first possible future for Alexa is one where the current trends mostly continue and even accelerate. Amazon’s own Alexa-based products continue to sell well, with Dot probably taking a greater share of sales going forward relative to Echo (or Tap), selling into the tens of millions of installed units in the next couple of years. On top of that, the adoption by third parties that was so evident at CES continues, with even more devices offering integration. Importantly, Alexa starts to make an appearance in Android smartphones, making it as pervasive and ubiquitous as existing smartphone-based assistants, possibly even making an appearance in another round of Amazon smartphones.

What we end up with in this scenario is a massive ecosystem of devices which all offer users access to Alexa and its functionality. These devices perform their functions well, recognizing voice commands effectively, responding appropriately, and adding value to users’ lives. Because they’re all part of the same ecosystem, they work the same way — commands issued through one are reflected on the others. Amazon benefits from owning a massive new user interface and platform which can be used not just to push its e-commerce sales but to take an increasingly large share of media and content consumption across video, music, audiobooks, and more.

This scenario also assumes major competitors either don’t launch competing products or those products fail to take off. Google has, of course, already launched its Home device but, thus far, sales are far lower than Amazon’s and are handicapped by a lack of awareness and the lack of a major e-commerce channel. The Google Assistant, meanwhile, should be the default option for Android OEMs in all their devices but the way in which Google has held it back as it promotes its own hardware has also held it back, perhaps fatally, as a third party voice platform. If that doesn’t change, if Microsoft’s Windows-based Cortana strategy falls short, and Apple’s reticence to participate in this market continues, Amazon dominates with its devices and those third party products using its ecosystem.

Future 2: Cracks start to appear in the Alexa ecosystem

The secrets of Echo’s success

I want, though, to paint an alternative future for Alexa, one which is less rosy and more complex. Amazon’s genius in launching the Echo and Alexa was to pick a blank slate rather than an existing category for its experiments with voice. Instead of competing with another smartphone-based voice assistant, Amazon chose to compete in the home, with its relative quiet and better internet connectivity, and a device that was optimized for specific use cases: fantastic voice recognition and great audio output, even from across the room. That had two major advantages: first, it wasn’t going head to head with powerful entrenched competitors and second, it could deliver far better performance around voice recognition than smartphone-based systems.

The Echo performs fantastically well at what it does. Its voice recognition is indeed very good, inviting highly favorable comparisons to Siri and the like. It’s this success in providing great voice experiences that have propelled sales of its own devices and prompted other companies to build their own as well. The assumption on all sides is it’s Alexa that powers these phenomenal experiences and the Alexa Voice Service for device makers will power similar experiences on other devices.

Amazon’s limited control over Alexa devices

However, one look at Amazon’s guidelines for those wishing to incorporate Alexa Voice Service into their devices should prompt at least some skepticism. Echo and Echo Dot famously have a 7-mic array built into the top of the device, with beam forming, enhanced noise cancelation, and more helping to ensure the device does a phenomenal job of picking up your voice from up to 20 feet away. But look at the minimum specs for Alexa-powered devices and you quickly realize many of these devices won’t match up on hardware – the minimum standard for microphones is just one and additional technologies like noise reduction, acoustic echo cancellation, and beam forming are entirely optional.

Also optional is “wake word” support – in other words, the always-listening function that waits to hear Alexa (or another word of the user’s choice) and then springs into life. The Amazon Tap doesn’t offer this feature (and was hammered in reviews for it) because the “across the room” use case is a key part of Echo’s appeal. Even when a wake word is supported, Amazon only requires a minimum of one microphone for near-field recognition and just two for far-field (20 foot) recognition.

Where this second future scenario diverges from the first is the sheer range of Alexa-enabled hardware starts to put many devices into the market that don’t have nearly the appeal of Amazon’s own. Lenovo’s Echo clones appear to be using an 8-mic array and may very well perform at exactly the same level or better but the Huawei Mate 9 smartphone, which is due to incorporate Alexa later this year, has just 4 microphones and the device obviously wasn’t built with optimal voice recognition in mind. In a rush to get products to market, we’ll see many vendors putting out devices with the bare minimum specs and prominent Alexa-related branding.

All it will take at this point is a handful of terrible reviews for Alexa-powered speakers and other devices and the Alexa brand will quickly become tarnished. At that point, Amazon’s admirable openness with the Alexa tools may come to be seen as a huge mistake because it’s set so few limits on what can be done with the service and its brand. Even if third parties are committed to providing the best possible experience, voice recognition on a smartphone or other smaller devices likely is never going to match up to the Echo’s quality, which means the true Alexa experience will likely remain elusive outside of the home. Any perceived quality advantage will, therefore, fade as well, making Alexa a lot less appealing.

More compelling competitors

Meanwhile, competitors will move past their slow start in responding to the Echo and Alexa and will begin producing more compelling alternatives. I see no reason why competitors shouldn’t be able to build devices which perform at least as well, in terms of voice recognition, as Echo given the same parameters (home use, large devices, mic arrays designed for voice recognition). Indeed, Google’s Home has already demonstrated there’s no special magic there. In addition, players like Google and Apple have one huge advantage – they already own massive installed bases of hundreds of millions of devices running their operating systems and integrated voice assistants.

Google’s early misstep in limiting the Google Assistant to its own devices will be overcome in the next few months as it makes it available to Android OEMs more broadly and, at that point, its Home device will become a lot more compelling. Apple, too, has the potential to do really interesting things in the home speaker space should it choose to do so, given the increasing scope and availability of Siri and its AirPlay audio and video casting technology. Again, the appeal of using the same assistant everywhere, tightly integrated into devices, will be a big advantage over Amazon’s looser Alexa ecosystem.

Which future plays out?

On balance, I’m inclined to think the future will look rather more like the second scenario I’ve painted than the first. That is to say, I think Amazon’s advantages in the field of voice assistants are mostly temporary and, to some extent, illusory. Competitors will catch up fast in the home and exceed its capabilities outside it. That doesn’t mean Amazon can’t build a decent business with a more limited scope of opportunity around its first party devices and a handful of really compelling third party devices in an ecosystem but I suspect its future will be a lot less bright than its present in this space.

This weekend, I finally watched Hidden Figures. I took my 9-year-old daughter with me to witness how instrumental women of color were to the success of several NASA missions — something that historically has been associated with white male achievement. If you have not seen it yet I highly recommend it. The acting is superb and the story offers so much education, both on race relations and women in the workplace. What I want to focus on is possibly something the director and the cast never imagined could matter. I do, not because it is the most important aspect but simply because it is very relevant to the tech transition we are experiencing right now.

All the talk surrounding artificial intelligence is as much about the technology itself as it is the impact its adoption will have on different aspects of our lives. Business models in the automotive industry, insurance business, public transportation, search and advertising as well as more personal consequences such as human to human interaction, sources of knowledge, and education. Change will not come overnight but we better be prepared because it will come.

New Tech Requires New Skills

Change came in 1962 for the segregated West Area Computer Division of Langley Research Center in Virginia where the three women who are the main protagonists of the story worked. Mathematician Katherine Goble and de facto supervisor Dorothy Vaughan are both directly affected by new tech rolling into the facility in the form of the IBM 7090. If you are not familiar with the IBM 7090 (I was not before this weekend), it was the third member of the IBM 700/7000 series of computers designed for large-scale scientific and technological applications. In layman terms, the 7090 would be able to perform in a blink of an eye all the calculations that took the computer division hours. Dorothy understood the threat and, armed with her wit and a book on programming languages, was able to help program the IBM 7090, taught her team to do the same, shifted their skills and saved their jobs.

I realize part of this story might be for the benefit of the screenplay and the world is much more complicated. However, I do think that what is at the core is very relevant — the creation of new skill sets.

Although AI has the potential to affect not only manual jobs that can be automated but also, theoretically, jobs that require learning and decision making, the immediate threat is certainly on the former.

We focus a lot, and rightly so, on the job loss AI will cause but we have not yet started to focus on teaching new skills so such losses can be limited. As I said, AI will not magically appear overnight but we would be fools to think we have plenty of time to create the skills our “augmented” world will require. From new programming languages to new branches of law and insurance, Q&A testing and more. Empowering people with new skills will be key not only to having a job but also keeping our income at pace with the higher cost these new worlds will entail. Providing a framework for education is a political responsibility as well as a corporate one.

Who Will We Trust?

The IBM 7090 replaces Katherine when it comes to checking calculations but, just as Friendship 7 is ready to launch, some discrepancies arise in the electronic calculations for the capsule’s recovery coordinates. Astronaut John Glenn asks the director of the Space Task Group to have Katherine recheck the numbers. When Katherine confirms the coordinates, Glenn thanks the director saying: “You know, you cannot trust something you cannot look in the eyes.”

I don’t know if Glenn actually said that or if it is a screenplay liberty but, when I heard it, I immediately thought of AI. Who will consumers trust? Many think AI is not going to be any different than it has been with any prior technology but I believe such thinking undermines where AI could actually take us. Autonomous cars are the scenario we most often refer to. We might trust the car to park itself or to alert us if a car is in our blind spot. We might even try a semi-autonomous setting on an empty motorway. But are we ready to trust the car and take out eyes off the road and our hands off the wheel? How will brands earn our trust? Will it be the number of accidents they are involved in? The assurance that, in case of an accident, their computers are programmed to save whoever is in the car?

What if we changed scenarios and talked about a medical diagnosis. Today, we tend to pick our doctors and specialists based on our insurance’s recommendation, a friend recommendation or even the comments on Yelp. Bed manners, courteous receptionists, short wait times all play a role. But, for anything more serious, what it all boils down to is the track record of right diagnosis and saving lives. Will we trust a machine alone? Or will we still want a doctor, who we can look in the eyes, coupled with the machine? A recent White House report mentioned by Fortune talks about the idea of linking human and machine. While they do so as part of the discussion of job losses, I think the formula also applies to our human nature of building trust with another human being.

The same issue of trust will also apply to other scenarios where not our life but our privacy and security could potentially be in danger. Here too, trust will matter. Who do we trust with our digital assistant, with our home automation? When life is not at risk, at least not directly, I feel consumers will show more flexibility, especially when the full implications are not grasped and convenience and possibly price are what matters the most.

In both cases, though, I strongly believe AI will drive consumers to consider more than technology alone and look for traits in brands that have been more traditionally associated with humans: honesty, empathy, loyalty, and service.

Writing about security is kind of like writing about insurance. As a responsible adult, you know it’s something you should do every now then, but deep down, you’re really worried that many readers won’t make it past the second sentence. (I hope you’re still here.)

Having recently had the privilege of moderating a panel entitled “Inside the Mind of a Hacker” at the CyberSecurity Forum event that occurred as part of CES, however, I’ve decided it’s time. The panel was loaded with four smart and opinionated security professionals who hotly debated a variety of topics related to security and hacking.

Speaking to the theme of the panel, it became immediately clear that the motivations for the “bad guy” hackers (there was, of course, a brief, but strong show of support for the white hat “good” hackers) are exactly what you’d expect them to be: money, politics, pride, power and revenge.

Beyond some of the basics, however, I was surprised to hear the amount of dissent on the topics discussed, even by those with some impressive credentials (including work at the NSA, managing cyber intelligence for Fortune 500 companies and government agencies, etc.). One particularly interesting point, for example, highlighted that hackers are people too—meaning, they make mistakes. In fact, thankfully, apparently quite a lot of them. While in retrospect that seems rather obvious, given the aura of invincibility commonly attributed to hackers through popular media, it wasn’t something I expected to hear.

Another key point was the methodology used by most hackers. Most agreed that the top threat is from phishing attacks, where employees at a company or individuals at home are lured into opening an attachment or clicking on a link that triggers a series of, well, unfortunate events. Even with up-to-date anti-malware software and security-enhanced browsers, virtually everyone (and every company) is vulnerable to these increasingly sophisticated and tricky attacks. However, several panelists pointed out that too much attention is spent trying to remedy the bad situations created by phishing attacks, instead of educating people about how to avoid them in the first place.

Looking forward, the rapid growth of ransomware, when companies or individuals are locked out of their systems and/or data until a ransom is paid to unlock it, was one of the panelists’ biggest concerns. Attacks of this sort are growing quickly and most believe the problem will get much worse in 2017. In many cases, organized crime is behind these types of incidents, and with the popularity of demanding payment in bitcoin or other payment methods that are nearly impossible to trace, the issue is very challenging.

Another concern the panel tackled was security issues for Internet of Things (IoT) devices. Many companies getting involved with IoT have little to no security experience or knowledge and that’s led to some gaping security holes that automated hacking tools are quick to find and exploit. Thankfully, the group agreed there is some progress happening here with newer IoT devices, but given the wide range of products already in market, this problem will be with us for some time. One potential solution that was discussed was the idea of an IoT security standard (along the lines of a UL approval), which is a topic I wrote about several months back. (See “It’s Time for an IoT Security Standard”)[pullquote]There are few if any things that can be completely blocked from hacking efforts, but huge progress could be made in cyber security if companies and people would just start actually using some of the tools already available.”[/pullquote]

Another potential benefit could come from improved implementations of biometric authentication, such as fingerprint and iris scans, as well as leveraging what are commonly called “hardware roots of trust.” Essentially, this provides a kind of digital ID that can be used to verify the authenticity of a device, just as biometrics can help verify the authenticity of an individual. Both of these concepts enable more active use of multi-factor authentication, which can greatly strengthen security efforts when combined with encryption, stronger security software perimeters, and other common sense guidelines.

As the panel was quick to point out, there are few if any things that can be completely blocked from hacking efforts. Nevertheless, huge progress could be made in cyber security if companies and people would just start actually using some of the tools already available. Instead of worrying about solving the toughest corner cases, good security needs to start with the basics and build from there.

Merriam-Webster defines a “bully pulpit” as:

Bully pulpit comes from the 26th U.S. President, Theodore Roosevelt, who observed that the White House was a bully pulpit. For Roosevelt, bully was an adjective meaning “excellent” or “first-rate”—not the noun bully (“a blustering, browbeating person”) that’s so common today. Roosevelt understood the modern presidency’s power of persuasion and recognized that it gave the incumbent the opportunity to exhort, instruct, or inspire. He took full advantage of his bully pulpit, speaking out about the danger of monopolies, the nation’s growing role as a world power, and other issues important to him. Since the 1970s, bully pulpit has been used as a term for an office—especially a political office—that provides one with the opportunity to share one’s views.

Roosevelt’s use of this term as an adjective and not a noun made the bully pulpit term OK for the time and, if the person using that pulpit for good, the term can be an endearing one. However, I am not sure we can see President-Elect Trump in that light yet, given his history of “blustering and browbeating” people to get his way.

I took a call from a reporter last week who was asking me about Apple’s decision to have their servers in a single data center location instead of at each of the major data centers they have around the US and the world. This will be done in Arizona and the reporter asked if Apple did this to help get a better position, in Trump’s eyes, by doing the manufacturing in the US. All told, it will only add 10-20 jobs and I told the reporter this was more strategic and had nothing to do with wanting to gain favor with Trump.

But other companies, such as Ford and Carrier, have made decisions to move jobs from planned facilities outside of the US back to America. On the surface, it does appear Trump “bullied” them into doing it. It seems very clear to me that Jack Ma, CEO of Alibaba, who met with Trump at Trump Tower and pledged to bring one million jobs to the US, had being in Trump’s good graces in mind.

Last week, Amazon announced they would add 100,000 jobs in the US. When this was announced, and because of Trump’s bully pulpit, I was asked by reporters if this decision was because of pressure from Trump or something more related to strategic growth.

I would hope it was because it was a strategic decision but I have a sneaky feeling Amazon and many others do not want to rile Trump. What he says and does from his “bully pulpit” could hurt them during his time in office. Let’s be clear: I am 100% behind creating more jobs in the US but I believe this should come as result of great business conditions, innovation, a true need for these companies, and that it is strategic to their business growth. I also believe they should not be doing it because they were bullied into it. I am of the school that believes bullying them to create jobs may be a temporary fix. Unless it’s done with the right motive, conditions, and strategy, it will not deliver the fundamental change needed for these jobs to be long lasting.

I believe strongly the tech industry and companies should not succumb to the bullying tactics of President-Elect Trump in any way when it comes to the issue of strategic planning, growth, innovation, and even jobs.

That does not mean they should not want to work with him and, when necessary, lobby to influence Mr. Trump’s policies so he and his administration do not stand in the way of growing our tech economy. But, if any of their moves are done just to placate Trump, then they are building foundations that will crumble under the weight of forced motivations. Unless strategic to their growth, it will set them back, not move them forward.

In a recent piece I did for Fast Company, I outlined my involvement with a council of independent tech influencers that helped shape President Bush’s tech agenda. In the article, I suggested some of the types of councils I believe President Trump needs to help him understand tech and, more importantly, use them to help develop a tech agenda of his own that would benefit his economic goals and get these companies to help support an agenda that moves our industry forward.

I believe working with President Trump in a civil, proactive manner should be the goal of every tech company but not kowtowing to him because he bullied them into some action. The tech industry needs the resolve to stand up against any bully pulpit and only do what is right for them to grow their market. Anything less than that won’t have a lasting impact on them or our industry.

I spent last week at CES and a couple of days this week at the North American International Auto Show in Detroit. In both cases, I spent a lot of time listening and talking to carmakers and others in the industry. What I’ve come away with from these two weeks is a lot of optimism about the future of cars for several different reasons.

Both the industry and outsiders are pushing change

The biggest reason I’m positive about the future is both the legacy industry players and newcomers and outsiders are pushing for change. There’s nothing more frustrating than seeing an industry where lots of good ideas are coming from outside and they’re all being squashed by the incumbents – we’ve seen this happen in the music industry, the PC industry, and we’re still seeing it in the TV industry. Though there has been some resistance in the past to the big shifts facing the automotive industry, almost all the major carmakers are accepting of the new realities and, in many cases, actively embracing the three big shifts: electrification, autonomous driving, and new ownership models.

The carmakers are actually engaging in their own efforts around autonomous driving and car and ride sharing. In the vast majority of cases, they’re also embracing electrification as one of several powertrain technologies. None of this is to say these companies will end up owning all of this themselves – at the very least, the disrupters from outside the industry and newcomers like Tesla have pushed the incumbents to innovate faster and they may well end up owning some of the end result too. But I heard from company after company about their investments and experiments in a variety of car and ride sharing models, even in urban mobility projects which don’t involve cars at all, such as bike and bus programs.

There is realism about challenges, at least behind closed doors

At both the shows I’ve attended in the last two weeks, there have been lots of high profile proclamations about the glorious future we’re all headed to, many of them with specific timelines attached. Looking at the headlines that result from these statements, it’s easy to despair at a lack of realism from many of the companies involved. Claims about fully autonomous vehicles rolling off production lines as soon as 2021 seem absurd on the face of them but, when you dig beneath the surface and talk to the actual engineers behind the technologies, you get a sense of nuance that’s often missing from those public proclamations.

What I found this week in particular was the carmakers are incredibly realistic about the very real challenges involved in bringing autonomous vehicles to market. There is definitely a headline-grabbing push to establish leadership in electrification and autonomous driving but those actually working on the technologies will tell you about all the complexities and challenges that exist. The real plans of the major carmakers around these topics are far more realistic about the actual timelines, which are much further out than the headlines would lead you to believe, at least for full-time Level 5 autonomous driving without geographic limits. When it comes to electrification, there are also far more sanguine views about the effect of current low gas prices on demand for EVs, the need for more charging infrastructure, and the limits of current battery technology. That realism is a good thing, because it means that, even as these companies embrace change, they’re going to do it in a way that prioritizes safety and the customer experience.

The future looks exciting

At the end of the day, I’m most optimistic because the future of cars looks generally very positive. Tesla has already shown us both the enormous potential for high-performance electric cars and for limited autonomous driving. I used Uber and Lyft extensively over the last two weeks and those services, and many others around the world, demonstrate the potential for far lower car ownership and more flexible mobility models. What I saw at NAIAS this week also reassured me we’re going to get great technology from the incumbent carmakers when it comes to all three of the major shifts, including increasingly high-performance electric and hybrid vehicles and assisted driving technology that helps pave the way for future autonomous driving technologies. We, and especially our children, are going to be able to drive (or be driven by) cars which are much safer, more comfortable, more connected, and better for the environment than the ones we drive today. The competition between the legacy industry and a whole variety of new players is pushing both sides to move faster in delivering that reality. That’s going to be good for all of us.

I survived CES 2017 to tell this story. From the very first day of press conferences and CES Unveiled, it was obvious connected-anytime-anywhere was what we were going to see at the show. It soon became clear that, if we played the drinking game for every time AI was mentioned by a vendor, we would not be sober for very long. Press conference after press conference, pitch after pitch, Artificial Intelligence was mentioned as a key trend for 2017 and one vendors were working on. Although in most cases, there was nothing concrete to see linked to the product they were announcing.

Everything Is Connected Even When It Should Not

A quick Google search pins the origins of the Internet of Things to Peter T. Lewis back in 1985 when he gave a speech at a FCC-supported conference where he defined IoT as “The integration of people, processes and technology with connectable devices and sensors to enable remote monitoring, status, manipulation and evaluation of trends of such devices.”

Over the past two to three years, IoT has started to materialize as more and more devices were connected to the internet. How this is developing might be different than how vendors intended it a few years ago. If we rewind a little, after smartphones, many thought wearables were going to be the most pervasive devices, making humans the most connected ‘things’ of the Internet of Things. As it turned out, wearables penetration is ramping up very slowly and it seems the focus of the vendors and the attention of the consumers have both shifted to connecting our homes.

What gets connected, however, is questionable. Not everything that is connected should be. Sometimes, even if a device is connected with good reason, the value of that connection is not immediately clear to the customer. In 2013, the HAPIFork took CES by storm. The connected fork let users know when they ate too much or too fast and was one of the most talked about device of the show. In 2017, one of the most talked about devices at CES was the L’Oréal Smart Brush. Developed with Withings, the Kérastase Hair Coach uses sensors and a microphone to count hair strokes and listen for hair breakage. Aside from the brush, I saw connected showers promising to keep your water warm (and save you water and money as well), windows that can sense when the air is getting too stuffy and open on their own, smart locks, voice activated garbage cans and so much more. There was so much connected “stuff” that I started to mentally file gadgets into three categories — Tech for the sake of tech, tech for the sake of lazy, and tech for the sake of humanity.

Sadly, I saw more gadgets and solutions falling into the first two categories than into the last. There were many products searching for a problem to solve and many that offered to replicate something we already do today with just less effort on our part. What was interesting, however, was the common underlying selling point was the smartness, not the connectivity.

IoT Is No Longer Cool for Consumers

I came away from CES with the clear impression that, although we are still talking about the Internet of Things, vendors, and more importantly PR gurus, have moved on from the connectivity part to the brain part of the devices.

While enterprise is still very much talking about IoT as it looks to empower, manage and, most of all, monetize all these devices, it was as if the term was tired when it came to consumers. It could also be for consumers, being connected is a given nowadays and it is the value of connectivity that needs to be highlighted in order to drive a premium. Unfortunately, not everything that is connected is necessarily smart and not everything that is smart is necessarily intelligent. As I talked to people, I noticed the line between these three concepts was very blurred and, in most cases, the blurring was quite intentional.

For me, a smart device is not only a device that is connected to the internet and/or other devices but one that can interact with other devices and enable some degree of autonomy. In order to be smart, a device does not necessarily need Artificial Intelligence, at least if you think of AI in terms of a device that mimics “cognitive” functions that humans associate with other human brain such as “learning” and “problem solving. This does not make the device less smart or less useful. To give you an example, let’s look at the iPhone 7 Plus camera experience. The iPhone 7 Plus takes great pictures thanks to the two lenses, the software, the sensors, and the processing power. AI or, more specifically, Machine Learning, only comes in to deliver the portrait effect by recognizing where the subject of the picture ends and where the background begins. Think about maps as another example. The Estimated Time of Arrival (ETA) we are given when we set a destination comes from a series of data from average speeds, actual travel time, traffic prediction, speed limits, and historical averages. These are all combined to get a projection of your ETA between two points. AI is what makes it possible for my phone to analyze my commute pattern and, as I connect to the car at a given time of day, offer me the ETA to the most likely location — my daughter’s school in the morning, the office after that or the Karate Dojo in the afternoon.

The Risk of AI-Washing

Internet of Things, Artificial Intelligence, Machine Learning are all trends that will develop over time, not over-night. While the temptation of keeping things fresh might get vendors to chase the next buzzwords, I think it is very risky to do so. Talking prematurely about features and capabilities might just bore consumers sooner rather than excite them. Talk about what your products can deliver. Better yet, showing what they deliver is more effective than labelling features with sexy buzzwords. Don’t tell your users your device uses AI, show them what your device can actually do and, if it looks like a bit of magic, let them think this is how you do it. Sometimes, talking too much about what is under the hood might raise more questions than you have answers for — especially when it comes to security and privacy – something we should all concern ourselves with as everything gets connected and smart around us.

By now you’ve undoubtedly read or viewed several different CES stories across a wide range of publications and media sites. So, there’s no need to rehash the details about all the cool, crazy, or just plain interesting new products that were introduced at or around this year’s show.

But it usually takes a few days to think through the potential impact of what these announcements mean from a big picture perspective. Having spent time doing that, here are some thoughts.

The impact of technology on nearly all aspects of our lives continues to grow. Yes, I realize that seems somewhat obvious, but to actually see or at least read about the enormous range of products and services on display at this year’s show makes what is typically just a conceptual observation, very real. From food to sleep to shelter to work to entertainment (of all kinds!) to health to transportation and beyond, it’s nearly impossible to imagine an activity that humans engage in that wasn’t somehow addressed at this year’s show. Having attended approximately half of the 50 CES shows that have now occurred, the expanding breadth of the show never ceases to amaze me. In a related way, the range of companies that are now participating in some way, shape, or form is surprisingly diverse (and will only increase over time).

Software is essential, but hardware still matters. At the end of the day, it’s the experience with a product that ultimately determines its success or failure. However, when you’re surrounded by the products and services that will drive the tech industry’s agenda for the next 12 months, it’s immediately clear that hardware plays an enormously critical role. From subtle distinctions like the look and feel of materials, to the introduction of entirely new types of tech products, the importance of hardware devices and key hardware components continues to grow, not shrink (as some have suggested).

What’s old can be new again. Though TVs and PCs may sound like products from a different era to some, this year’s show once again proved that the right technological developments combined with human ingenuity can produce some very compelling new products. Even long-forgotten technologies like front projection can be transformed in ways that make them very intriguing once again. Plus, it’s becoming increasingly clear that, just like the fashion and music industries, the tech industry is developing a love affair with retro trends. From vinyl to Game Boys and beyond, it seems many types of older tech are going to be revisited and renewed.

We are on the cusp of some of the biggest changes in technology that we’ve seen in some time. The integration of “invisible” technologies that we can’t directly see but still interact with is going to drive some of the most profound developments, power shifts, and overall restructuring that’s ever occurred in the tech industry. Oh, and it’ll make for some incredibly useful and compelling new product experiences too.[pullquote]The integration of “invisible” technologies that we can’t directly see but still interact with is going to drive some of the most profound developments, power shifts, and overall restructuring that’s ever occurred in the tech industry.”[/pullquote]

Voice-control will certainly be part of this, but there will be much more. In fact, the range of new products and services, as well as enhancements and recreations of existing products and services that AI, deep learning, and other advanced types of software technologies can enable in combination with sensors, connectivity, and powerful distributing computing is going to be transformational. Sure, there’s been talk of adding intelligence to everything for quite some time, but many of the announcements from this year’s CES demonstrate that this promise is now becoming real.

Finally, trade shows still matter, even in tech. Yes, virtual reality may one day provide us with the freedom to avoid the crowds, hassles, and frustrations of trekking to an alternative location, and seemingly everyone who goes likes to complain about attending CES, but there’s nothing quite like being there. From serendipitous run-ins with industry contacts, to seeing how others react to products and technologies you find interesting, there are lots of reasons why it’s going to be difficult to completely virtualize a trade show for some time to come.

On Christmas morning, as my mom and I hurriedly rushed around my kitchen making final preparations, a third voice would occasionally interject into our conversations. Sitting at my counter was Alexa, helping me through the process by answering questions, setting timers and even flipping on holiday music at our request.

I’ve been living with Alexa for roughly two years now and have grown accustomed to our constant banter. But, for my mom, it’s still a very new and novel experience. When my mom speaks to Alexa, she might recognize she’s speaking to a computer, but she probably doesn’t consider that computer is actually thousands of miles away and she probably doesn’t realize the way we talked to that computer on Christmas morning is the new face of computing.

The graphical user interface (GUI) wasn’t new when it was introduced in 1981 by Xerox and popularized to the masses in 1984 by Apple’s Macintosh computer. A GUI didn’t represent a new technical way of computing but it was a crucial evolution in how we interact with computers. Think of the impact the GUI had on how we used computers and what we used computers for. Think of how it changed our conception of computing.

The smartphone was created in the 1990s but it wasn’t until 2007, with the advent of Apple’s iPhone, that smartphones reached an important inflection point in consumer adoption. Today, 75 percent of U.S. households own a smartphone, according to research from the Consumer Technology Association (CTA).

The touchscreen interface represented the next paradigm shift in computing, ushering in a new way of thinking about computing and bringing into existence new applications.

Smartphone computing shares an important heritage and legacy with the GUI introduced in the early 1980s. If you’re old enough to remember computing before GUIs, can you imagine computing on a smartphone using command prompts? GUIs in the era of desktops improved computing. It was the transformation to a graphic interface that ultimately launched the smartphone era of apps.

Vocal computing will do the same thing for the future of computing. Vocal computing isn’t perfect. Alexa isn’t always certain what I’m asking. Google Home doesn’t always provide an answer. Siri can’t always help my sons when they ask complex questions. Like a first date, we are still learning each other.

Software layers and form factors change our computing experience. We’ve seen this throughout the history of computing – from the earliest mainframes to the computers we call phones and carry in our pockets. In all the same ways, vocal computing is just an extension of what we already know – it’s a more natural and intuitive interface.

Let’s not overlook just how transformative this new interface can be. Imagine someday computing on our bikes, in our cars, while we are walking or lying in bed. With voice, every environment can be touched by computing.

Along with much of the Tech.pinions team, I’m at CES this week and, as usual, TVs and TV-connected devices are a big theme. Streaming video providers are also present and making announcements of various kinds. Yet I’m struck again this week, as I have been before, by the fact technology isn’t really the biggest challenge in disrupting the traditional TV and video industry. Yes, there are advances being made in technology which are improving the user experience of watching video, but it’s content rights that are still the biggest barrier to really giving consumers what they want.

Working with – and around – the current system

A lot of the TV-related technology on display at CES either works with or around the current system. An increasing number of connected TV devices are incorporating some kind of over-the-air element. I saw boxes and other hardware from Mohu, Sling, and others designed to capture OTA broadcast signals and incorporate them into a next-generation user interface. This is hardly dramatic new technology – broadcast has been around for decades – but it’s often still the easiest way for cord cutters to access sports and local content.

It’s ironic we’re falling back on older technology to supplant newer coax, fiber, and satellite-based delivery, but this is the state of the TV industry today. Some of the best options simply have to work with what they’ve got – that’s an admirable reality but it often means disjointed experiences which combine OTA signals with internet-delivered streams, multiple user interfaces, and local or cloud-based storage. The new devices on offer at CES attempt to bring some harmony to all this, including the Mohu and Sling hardware devices I mentioned. But, in many cases, these solutions merely cobble back together bundles that end up looking very similar to what they’re replacing. And of course, OTA solutions don’t work for some people at all (I have a big mountain sitting between my house and the local broadcasters, meaning I get no signal at all).

Rights remain the biggest barrier

I’ve been using AT&T’s DirecTV Now since it launched late last year and I’ve largely been enjoying it, though I’ve seen a few technical hiccups here and there. But there are several non-technical things that detract from the experience – TV Everywhere authentication as offered by traditional pay TV services is a bit lacking and commercial breaks often display a “commercial break in progress” placeholder rather than actual commercials. The latter doesn’t bother me overly much, but both of these are entirely down to rights issues. Contracts signed years ago haven’t yet been renewed, so AT&T doesn’t have the rights in some cases to do its own ad insertion or to authenticate users on this service for TV Everywhere apps.

Hulu made some news at CES because it has apparently signed CBS as part of its pay TV replacement service. The fact that a single broadcaster signing on is news is more evidence of how fragmented this whole space is and how important rights negotiations are. The reality is that, even if people balk at the high prices of traditional pay TV services, they still want a lot of the content and that means paying directly or indirectly to access it. CBS has its own digital streaming service – CBS All Access – and has been a holdout from several of the other streaming services including DirecTV Now. Hulu getting CBS on board is therefore something of a coup but we’ve yet to see what other content it has secured and what its reported $40 per month price will include.

The reality is that some of this is merely a matter of contract renegotiations and will get worked out in the coming years, while other elements are down to content owners deliberately resisting or blocking some of the changes to the traditional business models. The major traditional pay TV providers are part of this picture too, though of course Sling and DirecTV Now come from two of the biggest. Cable operators have been the slowest to embrace this change, largely because they dominate the historical market.

User interfaces and video quality can still help

Having said all that, we’re still seeing innovation around user interfaces and video quality and they are making a difference even as the rights issues get worked out. Some of the new streaming pay TV services have much better UIs than the services they’re replacing. Interactive programming guides still often make an appearance, but search, recommendations, and on-demand options make these interfaces more compelling. In addition, we’re seeing innovation around content formats like 4K and HDR, from both TV manufacturers and content providers. Here, too, the newer over-the-top services are taking the lead, with Netflix and Amazon offering some of the first mass market 4K content. But some of the pay TV providers are dabbling with 4K too, and even Samsung is now going to be selling 4K TV through its smart TVs.

A tipping point is coming

At some point in the next year or two, I predict we’ll see a tipping point when it will become apparent to everyone, including the current holdouts, that digital delivery is the future and that it’s coming far faster than many of them thought. We’re already seeing the mainstreaming of streamed pay TV services, with the DirecTV Now launch just the first of a new raft of services, to be joined by Hulu, Amazon, and YouTube in the near future. But we’re also seeing accelerated cord cutting (with the pay TV industry losing well over a million subscribers per year at this point) and many individual cable networks losing subscribers at a much faster rate due to skinnier bundles and rising rights costs. All of this, taken together, will cause a crisis in the TV industry which will finally drive it to embrace new business models and broader distribution. And then the rights side of the equation will finally catch up with the advances in TV technology.

Predicting the future is more art than science, yet it’s always an interesting exercise to engage in as a new year comes upon us. So with the close of what was a difficult, though interesting year in the technology business, here’s a look at my predictions for the top 10 tech developments of 2017.

Prediction 1: Device Categories Start to Disappear

One of the key metrics for the relative health of the tech industry has always been the measurement of unit shipments and/or revenues for various categories of hardware-based tech devices. From PCs, tablets and smartphones, through smartwatches, smart TVs and head-mounted displays, there’s been a decades-long obsession with counting the numbers and drawing conclusions from how the results end up. The problem is, the lines between these categories have been getting murkier and more difficult to distinguish for years, making what once seemed like well-defined groupings become increasingly arbitrary.

In 2017, I expect the lines between product categories to become even blurrier. If, for example, vendors build hand-held devices running desktop operating systems that can also snap into or serve as the primary interface for a connected car and/or a smart home system, what would you call that and how would you count it? With increasing options for high-speed wireless connectivity to accessories and other computing devices, combined with OS-independent tech services, bots, and other new types of software interaction models, everything is changing.

Even what first appear as fairly traditional devices are going to start being used and thought of in very different ways. The net result is that the possibility for completely blowing up traditional categorizations will become real in the new year. Because of that, it’s going to be time to start having conversations on redefining how the industry thinks about measuring, sizing, and assessing its health moving forward.

Prediction 2: VR/AR Hardware Surpasses Wearables

Though it’s still early days for head-mounted virtual reality (VR) and augmented reality (AR) products, the interest and excitement about these types of devices is palpable. Yes, the technologies need to improve, prices need to decrease, and the range of software options needs to widen, but people who have had the opportunity to spend some time with a quality system from the likes of HTC, Oculus, or Sony are nearly universally convinced that they’ve witnessed and partaken in the future. From kids playing games to older adults exploring the globe, the range of experiences is growing, and the level of interest is starting to bubble up past enthusiasts into the mainstream.

Wearables, on the other hand, continue to face lackluster demand from most consumers, even after years of mainstream exposure. Sure, there are some bright spots and 2017 is bound to bring some interesting new wearable options, particularly around smart, connected earbuds (or “hearables” as some have dubbed them). Overall, though, the universal appeal for wearables just isn’t there. In fact, it increasingly looks like smartwatches and other widely hyped wearables are already on the decline.

As a result, I expect revenues for virtual reality and augmented reality-based hardware devices (and accessories) will surpass revenues for the wearables market in 2017. While a clear accounting is certainly challenging (see Prediction 1), we can expect about $4 billion worldwide for AR/VR hardware versus $3 billion for wearables. Because of lower prices per unit for fitness-focused wearables, the unit shipments for wearables will still be higher, but from a business perspective, it’s clear that AR/VR will steal the spotlight from wearables in 2017.[pullquote]From a business perspective, it’s clear that AR/VR will steal the spotlight from wearables in 2017.”[/pullquote]

Prediction 3: Mobile App Installs Will Decline as Tech Services Grow

The incredible growth enabler and platform driver that mobile applications have proven to be over most of the last decade makes it hard to imagine a time when they won’t be that relevant, but I believe 2017 will mark the beginning of that unfathomable era. The reasons are many: worldwide smartphone growth has stalled, app stores have become bloated and difficult to navigate, and, most importantly, the general excitement level about mobile applications has dropped to nearly zero. Study after study has shown that the vast majority of apps that get downloaded rarely, if ever, get used, and most people consistently rely on a tiny handful of apps.

Against that depressing backdrop, let’s also not forget that the platform wars are over and lots of people won, which means, really, that nobody won. It’s much more important for companies who previously focused on applications to offer a service that can be used across multiple platforms and multiple devices. Sure, they may still make applications, but those applications are just front-ends and entry points for the real focus of their business: a cloud-based service.

Popular subscription-based tech services such as Netflix and Spotify are certainly both great example and beneficiaries of this kind of move, but I expect to see many different flavors of services grow stronger in 2017. From new types of bot-based software to “invisible” voice-driven interaction models, the types services that we spend a lot of our 2017 computing time on will be much different than in the mobile apps era.

Prediction 4: Autonomous Drive Slows, But Assisted Driving Soars

There’s no question that autonomous driving is going to be a critical trend for tech industry and automotive players in 2017, but as the reality of the technical, regulatory, and standards-based challenges of creating truly autonomous cars becomes more obvious in the new year, there’s also no question that timelines for these kinds of automobiles will be extended in 2017. Already, some of the early predictions for the end of the decade or 2020 have been moved into 2021, and I predict we’ll see several more of these delays in the new year.

This doesn’t mean a lot of companies—both mainstream and startup—won’t be working on getting these cars out sooner. They certainly will, and we should hear an avalanche of new announcements in the autonomous driving field throughout the year from component makers, Tier 1 suppliers, traditional tech companies, auto makers and more. Still, this is very hard stuff (both technically and legally) and technology that potentially places people’s lives at stake is a lot different than what’s required to generate a new gadget. It cannot, nor should it be, released at the same pace that we’ve come to expect from other consumer devices. If, God forbid, we see some additional fatalities in the new year that stem from faulty autonomous driving features, the delays in deployment could get much worse, especially if they happen via a ridesharing service or other situation where ultimate liability isn’t very clear.

In spite of these concerns, however, I am convinced that we will see some critical new advancements in the slightly less sexy, but still incredibly important field of assisted driving technologies. Automatic breaking, car-assisted crash avoidance and other practical assisted driving benefits that can leverage the same kind of hardware and artificial intelligence (AI)-based software that’s being touted for fully autonomous driving will likely have a much more realistic impact in 2017. Truth be told, findings from a TECHnalysis Research study show that most consumers are more interested in these incremental enhancements anyway, so this could (and should) be a case where the current technologies actually match the market’s real needs.

Prediction 5: Smart Home Products Consolidate

Most of the early discussions around the smart home market has been for standalone products, designed to do a specific function and meant to be installed by the homeowner or tenant. The Nest thermostat, August smart lock, and various security camera systems are classic examples of this. Individually, many of these products work just fine, but as interested consumers start to piece together different elements into a more complete smart home system, problems quickly become apparent. The bewildering array of different technical standards, platforms, connectivity requirements and more often turn what should be a fun, productive experience into a nightmare. Unfortunately, the issue shows few signs of getting better for most people (though Prediction 6 offers one potential solution.)

Despite these concerns, there is growing interest in several areas related to smart homes including distributed audio systems (a la Sonos), WiFi extenders and other mesh networking products, and smart speakers, such as Amazon’s Echo. Again, connecting all these products can be an issue, but so are more basic concerns such as physical space, additional power adapters/outlets, and all the other aspects of owning lots of individual devices.

Because of these issues, I predict we’ll start to see new “converged” versions of these products that combine a lot of functionality in 2017. Imagine a device, for example, that is a high-quality connected audio speaker, WiFi extender and smart speaker all in one. Not only will these ease the setup and reduce the physical requirements of multiple smart home products, they should provide the kind of additional capabilities that the smart home category needs to start appealing to a wider audience.

Another possibility (and something that’s likely to occur simultaneously anyway), is that the DIY market for smart home products stalls out and any potential growth gets shifted over to service providers like AT&T, Comcast, Vivint and others who offer completely integrated smart home systems. Not only do these services now incorporate several of the most popular individual smart home items, they’ve been tested to work together and give consumers a single place to go for support.

Prediction 6: Amazon Echo Becomes De Facto Gateway for Smart Homes

As mentioned in Prediction 5, one of the biggest challenges facing the smart home market is the incredibly confusing set of different standards, platforms, and protocols that need to be dealt with in order to make multiple smart home products work together. Since it’s extremely unlikely that any of these battles will be resolved by companies giving up on their own efforts and working with others (as logical and user-friendly as that would be), the only realistic scenario is if one device becomes a de facto standard.

As luck would have it, the Amazon Echo seems to have earned itself that de facto linchpin role in the modern smart home. Though the Echo and its siblings are expected to see a great deal of competition in 2017, the device’s overall capabilities, in conjunction with the open-ended Skills platform that Amazon created for it, are proving a winning combination. Most importantly, the Echo’s Smart Home Skill API is becoming the center point through which many other smart home devices can work together. In essence, this is turning the Echo into the key gateway device in the home, allowing it to essentially “translate” between devices that might not otherwise be able to easily work together.

While other devices and dedicated gateways have tried to offer these capabilities, the ongoing success and interest in the Echo (and any ensuing variants) will likely make it the critical component in smart homes for 2017.[pullquote]The Amazon Echo’s Skills platform is becoming the center point through which other smart home devices can work together.”[/pullquote]

Prediction 7: Large Scale IoT Projects Slow, But Small Projects Explode

The Internet of Things (IoT) is all the buzz in large businesses today, with lots of companies spending a great deal of time and money to try to cash in on the hot new trend. As a number of companies have started to discover, however, the reality of IoT isn’t nearly as glamorous as the hype. Not only do many IoT projects require bringing together disparate parts of an organization that don’t always like, or trust, each other (notably, IT and operations), but measuring the “success” of these projects can be even harder than the project itself.

On top of that, many IoT projects are seen as a critical part of larger business transformations, a designation that nearly guarantees their failure. Even if they aren’t part of a major transformation, they still face the difficulty of making sense of the enormous amount of data that instrumenting the physical world (a fancy way of saying collecting lots of sensor data) entails. They may generate big data, but that certainly doesn’t always translate to big value. Even though analytics tools are improving, sometimes it’s just the simple findings that make the biggest difference.

For this reason, the potential for IoT amongst small or even tiny businesses is even larger. While data scientists may be required for big projects at big companies, just a little common sense in conjunction with only a few of the right data points can make an enormous difference with these small companies. Given this opportunity, I expect a wide range of simple IoT solutions focused on traditional business like agriculture and small-scale manufacturing to make a big impact in 2017.

Prediction 8: AI-Based Bots Move to the Mainstream

It’s certainly easy to predict that Artificial Intelligence (AI) and Deep Learning will have a major impact on the tech market in 2017, but it’s not necessarily easy to know exactly where the biggest benefits from these technologies will occur. The clear early leaders are applications involving image recognition and processing (often called machine vision), which includes everything from populating names onto photos posted to social media, to assisted and autonomous driving features in connected cars.

Another area of major development is with natural language processing, which is used to analyze audio and recognize and respond to spoken words. Exciting, practical applications of deep learning applied to audio and language include automated, real-time translation services which can allow people who speak different languages to communicate with each other using their own, familiar native tongue.

Natural language processing algorithms are also essential elements for chatbots and other types of automated assistance systems that are bound to get significantly more popular in 2017, particularly in the US (which is a bit behind China in this area). From customer assistance and technical support agents, through more intelligent personal assistants that move with you from device to device, expect to have a lot more interactions with AI-driven bots in 2017.

Prediction 9: Non-Gaming Applications for AR and VR Grow Faster than Gaming

Though much of the early attention in the AR/VR market has rightfully been focused on gaming, one of the main reasons I expect to see a healthy AR/VR hardware environment in the new year is because of the non-gaming applications I believe will be released in 2017. The Google Earth experience for the HTC Vive gave us an early inkling of the possibilities, but it’s clear that educational, training, travel and experiential applications for these devices offer potential for widespread appeal beyond the strong, but still limited, hard-core gaming market.

Development tools for non-gaming AR and VR applications are still in their infancy, so this prediction might take two years to completely play itself out. However, I’m convinced that just as gaming plays a critical but not overwhelming role in the usage of smartphones, PCs and other computing devices, so too will it play an important but not primary role for AR and VR devices. Also, in the near term, the non-gaming portion of AR and VR applications is quite small, so from a growth perspective, it should be relatively easy for these types of both consumer and business-focused applications to grow at a faster pace than gaming apps this year.

Prediction 10: Tech Firms Place More Emphasis on Non-Tech Fields

While many in the tech industry have great trepidation about working under a Trump administration for the next several years, the incoming president’s impact could lead to some surprisingly different means of thinking and focus in the tech industry. Most importantly, if the early chatter about improvements to infrastructure and enhancements to average citizen’s day-to-day lives come to pass, I predict we will see more tech companies making focused efforts on applying their technologies to non-tech fields, including agriculture, fishing, construction, manufacturing, and many more.

While the projects may not be as big, as sexy or as exciting as building the coolest new gadgets, the collective potential benefits could prove to be much greater over time. Whether it’s through simple IoT-based initiatives or other kinds of clever applications of existing or new technologies, the opportunity for the tech industry to help drive the greater good is very real. It’s also something I hope they take seriously. Practical technologies that could improve the crop yields by only a few percent of not just a few of the richest farms, but of all the smallest farms in the US, for example, could have an enormously positive impact on the US economy, as well as the general population’s view of the tech industry.

Some of these types of efforts are already underway with smaller agro tech firms, but I expect more partnerships or endeavors from bigger firms in 2017.

With the mass proliferation of smartphones and a rapidly maturing consumer base making their smartphones their primary computing devices, there is a fascinating new dynamic emerging. Our company, Creative Strategies, spent a lot of time in the late 80s modeling adoption cycles of new technologies. Using the market data in hand, along with discussions with academics and people like Geoffrey Moore who published a seminal book on the subject called Crossing the Chasm, models were built to understand the conditions that drove technologies into the mainstream. In those days, decades were used in models to predict how technologies went from the early innovators into the hands of average consumers.

Then, much of the effort was built around adoption cycles for personal computers that fit on desks and, eventually, ones that fit on your lap. It took decades just to get to the point where it was common for a single household to have a personal computer in their house. Now, around 3 billion humans across the globe have a computer that fits in their hands and goes with them everywhere. We are in uncharted territory and at a unique point in technology history with this many people owning such a powerful pocket computer, continually connected to the internet and other people, with instant access to buying and selling, and a wealth of information and data accessible at all times. Put all this together and we are watching technology diffuse and become adopted into the mass mainstream at unprecedented rates. This is happening with both hardware and software.

I first started thinking about this trend several years after Apple released the iPad. As that product launched, we were still using traditional models to predict and anticipate adoption cycles of new technology. We shortened the time span some, due to more mature market dynamics, but we did not expect the iPad to become the fastest adopted new technology product of all time and forecasts were well under what iPads sales rates were. So, we focused our research and analysis on why this happened and what we can learn. This was the first time we needed to step back and honestly look at how much has changed in the market to rethink how technology will diffuse in the modern age.

The iPad was a useful case study in adoption cycles for more than just how quickly it went mainstream but also how quickly it seemed to hit its addressable market. Once the iPad’s S-curve was on a steep incline, forecasters began to modify their underestimated forecasts but then began to overestimate. Some people were predicting a potential market size north of one billion tablets. Sales started to slow and it quickly became a replacement market with a total active installed base of around 350-400 million units, well short of the billion plus forecasts and well short of the PC installed base of ~1.5 billion and smartphone installed base of ~3 billion. While the iPad went mainstream faster than any tech hardware product in history, it also hit its max total addressable market extremely quickly. This is the new dynamic I think we are to expect as we move into a cycle of rapidly diffusing technology.

We can make some of the same observations about the wearable market. Specifically, things like smart watches and fitness wearables. This market shot off like a rocket but then slowed very quickly. This dynamic made predicting its exact market size difficult. The slowing year over year growth of the category came quickly and, while the market size for wearables may still be larger than it appears it is today, it also diffused quickly in certain developed markets.

We also see this trend in software. Perhaps one of recent example was the fascinating phenomena of Pokemon Go. There has never been software which went from zero to 500 million as fast as Pokemon Go. While not all of those 500 million people are still using the app, we saw a fascinating phenomenon of diffusion of software in the form of hoards of people walking around public spaces hunting for digital creatures hiding in the physical world.

The groundwork has been laid for technology, both hardware and software, to diffuse rapidly in short periods of time. Which again, makes it very difficult to predict their market size. A product, app, or service may appear to be addressing a larger market than it is in its early stages. This means metrics around hardware sales, app downloads, service subscriptions, etc., may be extremely misleading. The problem is, we have no idea the degree to which they are misleading or not.

Twitter, Fitbit, and GoPro are just recent examples of things that grew quick but also hit their max market opportunity just as quickly. As these companies went public, it was on the basis of a much larger market opportunity than it appears is the case. It’s possible Snapchat may fall into this category, but we don’t know, which is the new challenge of our modern era.

One last point. There are clearly things which will not diffuse as quickly because they are truly new and groundbreaking types of technologies (AR and VR for example) and may spread more slowly since consumers have less familiarity or context with the new technology. In those cases, I believe, we can still assume some type of longer than usual adoption metrics. I’m also not saying the mentioned companies or categories can not still grow their market opportunity with innovations. Only that the “easy” growth was over and over quicker than anticipated.

All in all, I’m convinced those of us who study these markets are in for new challenges in our approach as we try to size market potential for consumer technology. It means we need to address research with new methodologies, ask different sets of questions, understand deeper nuances of each consumer segment and, overall, be willing to abandon old practices and assumptions to create new ones for the modern era.