January 2018 began with a true tech blockbuster – Blue Hill Research and AOTMP merged to create and deliver an exciting and new emerging technology, mobile and telecom management research and advisory service! What an amazing way to start a new year of working within the realm of advanced technology!
Personally, I am thrilled to be an insider on this deal. AOTMP’s acquisition of Blue Hill augers an awesome opportunity to provide both enterprises and vendors with the critical actionable insights they need to achieve true strategic value through the use of advanced and emerging technology. The Research and Advisory team is full-on psyched to deliver on it.
As a way to bring my own little bit of celebration to our combined new company, I’ve pulled together my thoughts on the tech trends that are moving towards real and large scale enterprise implementation in 2018.
After you’ve read it through let me know: Agree? Disagree? Let’s start a conversation!
Mobile technology continues to move forward at a rapid pace, but it’s “guise” as an actual device users carry will begin – has already begun – to change. Sure, we’ll always have our mobile devices – nothing here changes in 2018, aside from moving to Apple’s FaceID and whatever Samsung has up its sleeve for the Galaxy S9 that will be announced in late February at Mobile World Congress 2018. But there are plenty of new and different devices to think about and many new ways mobility will drive our futures..
Before getting into details here is my short trends list for 2018 that I believe will see large scale implementation:
- Wearable Technology
- Internet of Things (IoT)
- Augmented Reality (AR) and Virtual Reality (VR)
- Machine Learning
- Artificial Intelligence (AI)
- Cybersecurity and Cyber-attacks
- Mobile Security – Unified Endpoint Management (UEM)
- Unlocked Phones and eSims
- Automated Mobile Workforce Support and Self Service
- Bitcoin and Blockchain (a bonus trend/prediction!)
Some of these trends are co-dependent. For example, cyber-attacks will become far more prevalent as mobile access points into enterprise networks increase exponentially through IoT and wearable technology. Automated service support will grow based on the combined growing market penetration of machine learning, virtual reality and the first real stages of artificial intelligence (AI).
The one sure constant in all of this is a fast proliferation of enterprise options for deployment, implementation, ongoing maintenance and upgrade cycles and workforce support. Before digging in, here is one last general thought: all of the trends below (aside from my bonus blockchain prediction) lead to the transformation within the enterprise to full-fledged IT Expense Management (ITEM as we refer to it). Keep that firmly in mind when reading through my POVs below.
Wearable Technology in the Enterprise
Wearable technology has, for the most part, been driven by consumer and personal use, typically in the form of Fitbits and Apple Watch kinds of tech. More prevalent in the enterprise has been the use of such devices as eye wear from Epson and Vuzix, which make use of augmented reality to visually enhance the physical, existing workplace, and devices with dedicated functionality for specific work environments, such as retail shop floors and healthcare provider ecosystems. I’ve been covering wearable tech since 2012 and aside from a lot of consumer hype, enterprise use outside of healthcare has been slow to take off. But I am predicting that 2018 is the enterprise inflection point year for the technology. Look for a major explosion of use everywhere in the enterprise, from the retail shop to the manufacturing floor and all points in between.
Internet of Things (for real)
IoT has long risen past the point of buzzword status. From the early days of serving as simple field-based machine to machine (M2M) alerting devices (e.g. sense a predefined temperature range and issue an alert to a human via a low bandwidth network such as 2G) we now have complex tools that are able to communicate directly not only with other IoT devices but with entire systems of devices that in many cases generate their own actions and workflows based on real time and real world conditions.
As with wearable tech hardware – all of which can be considered IoT devices in their own right, IoT device penetration will explode in 2018. Enterprises will create many dynamic operations that will become business-critical on a 24 hour, seven day a week basis. These devices, networks of devices and systems of interactive devices will also generate big data on a massive scale that in turn will feed machine learning systems (more on this shortly).
Augmented and Virtual Reality
It’s important to understand the difference between augmented reality (AR) and virtual reality (VR) – the former literally “augments” existing environments, while the latter creates environments that do not actually exist, even though they may be based on real environments. AR’s first real use in the enterprise dates back to 2013 as a wearable device – that is, the eye wear was more important than the rudimentary underlying apps supporting the devices.
Today we have IoT-enhanced access to the work place that adds substantial information to the apps used with the eye wear and related tech such as sensor-enabled gloves. An example of a particularly useful AR application is its use in guiding medical technicians – utilizing AR eye wear with built-in infrared capabilities – to locate real veins in real arms for intravenous applications. Hospitals have seen tremendous clinician IV productivity improvements here that also deliver directly to the holy grail of enhanced patient satisfaction. This example scratches the surface of what will be created in 2018.
Virtual reality creates virtual spaces and images that do not actually exist, and allows users to interact with those systems. This of course plays enormously well for consumer gaming but the real money in VR will be found in enterprise use – especially in IoT-driven environments, where the combination of IoT sensor information and VR-driven environments will simplify field-based repairs, demonstrate for technicians different exploded parts of a complex system or machine, and allow them to make repairs or other modifications as needed.
There have been rudimentary wearable tech-driven systems available for doing such things since 2012 or so (Motorola was a first driver) but VR now benefits from visuals provided through sophisticated head-mounted displays and sensors that provide near-real experiences virtually. 2018 will only see the first of these systems emerge but think of it as the year the enterprise VR trend begins.
A misnomer of sorts, “machine” learning is really about extracting valuable and actionable business information from big data stores that in turn helps enterprises to automate a variety of service- and sales-related business processes. In 2018 we will see businesses aggressively develop and ramp up automated advisors and assistants that can both receive calls and proactively initiate calls, delivered with near-human interactive capabilities. For the most part these efforts will center on reducing the enormous amounts of “routine” and common things the human workforce currently handles. The chief productivity goal is to free up the workforce to focus on more important and personalized work and workflow processes that go beyond routine and common towards achieving high levels of customer satisfaction.
From an IoT perspective, machine learning-based automated advisers will take advantage of the data being reported ongoing from the field and be able to determine when service calls are necessary and when parts need to be replaced in complicated machinery (e.g. high speed elevators in skyscrapers) – ahead of actual failure. 2018 will bring major new efforts in creating standards for infrastructure and machinery maintenance and support – with the goal of driving productivity up and significantly reducing the costs of doing business.
In 2017 we spent an entire year following the AI hiring practices and M&A activity of the major tech vendors. To be sure, it was all about gaining access to engineers and scientists with expertise in artificial intelligence (AI) or buying companies focused on AI. Meanwhile, IBM spent 2017 pushing the term “cognitive” across all of its technology platforms – by which it means delivering capabilities that begin to “think” for themselves. Whereas machine learning is about extracting valuable intelligence based on real world info and facts and reacting to them in useful ways, AI begins to address understanding the potential interconnections between our ever expanding bases of knowledge.
Machine learning uses data extraction and correlations to tell us that a part is due to be replaced. AI will tell us why that part is likely to need replacing, what the likely causes of the wear on a part might be, and offer some “thoughts” on reducing that wear. Machine learning will tell you what your next chess move should be based on data and brute force. AI will tell you the rules of the game based on actually self-divining the rules and behaviors of the game and elegantly determining moves without brute force.
I’ll leave it at that – there isn’t much more I can say here. But in 2018 we will see the first real world AI implementations that from a business perspective will begin to provide recommendations for solving business problems rather than merely eliminating routine and repeated processes from requiring human interactions.
Cyber-attacks and Cybersecurity
Unfortunately and sadly 2018 is going to see a significant uptick in cyber-attacks. We heard a great deal in 2017 about large scale attacks against major companies (think Equifax) – some of them on a global scale. My own concern however lies in the ability of hackers and cyber evil-doers to attack any business, and especially SMBs with limited tech resources – something that can easily destroy those companies and wreck massive havoc with personal user data. The proliferation of mobile and IoT devices ups the hacking ante and creates myriad opportunities to get inside networks, and in 2018 the counter-trend must be to become super-vigilant about such attacks, all while ensuring that enterprises can deliver security solutions with true agility.
Mobile Security – Unified Endpoint Management (UEM)
A year never goes by where mobile security does not deliver a new acronym, and 2017 was no different. Unified endpoint management – UEM, is the new mobile security buzzword de jour. In 2018 however, UEM will evolve from buzzword to stand operating procedure. The proliferation of user mobile hardware, wearable technology and IoT devices will require any business to extend their MDM or EMM platforms to provide a comprehensive and cohesive strategy for managing this collective set of endpoints. Still hanging on to that old 2010 era MDM solution? 2018 will require many businesses to finally upgrade to UEM.
eSims and Unlocked Phones
I need to underscore that in 2018 we will see a proliferation of unlocked mobile phones specifically in the US market. This will be driven in good part by subsidies that are now beginning to dry up and that will likely completely disappear. This isn’t a problem but an opportunity and avenue to cost-effective hardware acquisition and related short and long term financial planning around device procurement.
In 2018 we will also see eSIM technology go mainstream. This means that it will become much easier to electronically switch mobile devices from one telco to another, with no physical access necessary. Telco operator automation will become available simply by utilizing their platform APIs. This is another opportunity but one that will only become viable through having a detailed understanding of the efforts that will be required to take advantage of it, including understanding myriad security-related issues and defending against them.
Automated Mobile Workforce Support and Self Service
It will be virtually impossible to operate a business in 2018 – regardless of size – without implementing some form of automated workforce support, whether directly or through a reliable mobile partner. The proliferation of machine learning services as well as automated advisors and assistants will demand that businesses deliver automated support and services. As unlocked mobile phones and eSims become prevalent in 2018 the sheer diversity of hardware will overwhelm any human-driven system in the form of greatly wasted workforce time.
The clear warning message in 2017 as the US economy revs up is that businesses are already finding it difficult to land new workers with the skills and training necessary to operate in today’s business world. In particular businesses need to be very aware of maintaining high levels of workforce satisfaction in 2018 as a competitive advantage. Failure to do so will drive competitive disadvantages and workforce defections to those businesses that provide those high levels of satisfaction.
Bitcoin and Blockchain – A Special Prediction
In my very humble opinion the cryptocurrency Bitcoin is in the midst of a “massively massive” bubble that can only be compared to the Dutch Tulip Bulb mania of the mid-1600s. A Bitcoin is literally nothing more than an entry in a ledger. To be sure there has to be some “mathematical mining” to uncover a legitimate Bitcoin entry, and future Bitcoins (the total number of which are finite in number) become harder and harder to uncover (that is, to mine) and require tremendous amounts of expensive super computing power.
I am very interested to see quantum computing applied to Bitcoin mining – it may reduce the value of Bitcoins to pennies. Yes, something is worth anything a market will bear at any given point, but sooner than later those ascribing a value of $17,000 (or more!) to a Bitcoin (that is, an entry in a ledger) today will be in for a very rude awakening. Last I looked as I tweak this blog post in mid-January there are many already holding a $17,000+ bag that is today worth less than $10,000.
As an aside, it is currently estimated that the energy required to mine a single Bitcoin today (it gets harder and harder as we end the mining lifecycle over the next few years) literally requires the equivalent energy it takes to run an entire average household for two years. Quantum computing cannot come to bitcoin mining soon enough!
The real importance of Bitcoin, and the reason I mention it is that the underlying blockchain technology that secures the entire Bitcoin ecosystem is the real gold in the Bitcoin mania. Blockchain offers a deep level of both security and transparency that can be used to protect transactions as well as the ownership and provenance of actual things (such as diamonds, or say mobile devices) – essentially anything. I mention it as a bonus trend here because I am anticipating – no, I am predicting – that we will see the introduction in 2018 of blockchain-based mobile security. Major companies with global reach – such as IBM – are already heavily invested in blockchain and are working to drive the technology into every aspect of business. The first mobile security vendor on the blockchain block will show up in 2018 – that is my prediction and I’m sticking with it.
A Concluding Thought
There are certainly other trends predictions to include here, along with a hundred thousand words to detail their implications for both the enterprise and vendor communities. I and the rest of the AOTMP and Blue Hill research and advisory team will be digging into all of it throughout the year – stay tuned!
Meanwhile, as I noted at the top of this post, let me hear from you! Share your thoughts, tell me I’m wrong or why you might agree with me. Finding the common ground to actionable technology insight within the technology, mobility and telecom management world is what I and the research team are here for!