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The enterprise technologies to watch in 2. Enterprise IT in 2. This is particularly the case in areas like blockchain, digital twins, marketing integration solutions, and digital transformation target platforms. Not too many items fell off this year's enterprise tech to watch list either, as organizations continue to struggle to adopt the growing raft of relevant new technologies that have steadily arrived on the scene recently.

Consequently, the portfolio of emerging tech that must be managed continues to grow quickly, even as IT spending - - and overall tech absorption capacity - - is increasing only in the low single digits. This is an untenable proposition that's putting more and more IT organizations under stress. Most significantly, this is creating service backlogs that are pushing "edge IT" implementation and acquisition - - or systems that are not considered mission critical enterprise- wide - - out into lines of business for realization as they see fit, as well as fueling so- called shadow IT projects at the departmental level. As a result, I currently find that IT organizations are seeking novel ways to learn about and adopt emerging tech to ride the exponential curve of digital change.

That's a whole separate conversation however, but one that is becoming urgent as we see the CIO under significant and steady pressure to deliver far more quickly in 2. For this year's list of enterprise tech to watch, I've attempted to synthesize data from all available sources, particularly industry trend data. In general, I prefer to include technologies on the list that are expected to grow in the double digits every year for a half decade or more from now. However, I'll sometimes include important new technology categories if they clearly warrant it based on early importance, even if forecasts aren't readily available.

As a result, we've seen the steady shift from SMAC (social, mobile, analytics, cloud) that dominated this list at its inception to one that is more focused on artificial intelligence, Internet of Things, distributed ledgers, immersive digital experiences (AR/VR), edge computing, low code tools, and much more. That's not to say that essentially mainstream technology bases like public cloud, cybersecurity, or big data are staid and therefore are about to come off the list. In fact, they are shifting and evolving more now than ever before and should remain at the top of the technologies that most enterprises should be watching very closely today. Based on my analysis then, here is the short list of enterprise technologies that organizations should be tracking for building skills, assessing their strategic and tactical impact, experimenting with, and subsequently preparing for wider- scale adoption, often as part of a more systematic program of digital transformation. As in previous years, I've also included a horizons list in this year's tech to watch, which shows technologies that are almost certainly going to be significant in coming years, but should now be relegated primarily to tracking and monitoring, unless it's impactful for your core business in the near term. The enterprise technologies to watch in 2.

In roughly clockwise order, here's the breakdown, with a brief note on why each enterprise technology to watch this year is significant, with data on its outlook if available: Machine learning. Separating out the topic of machine learning from artificial intelligence is still a tricky task. However, I categorize machine learning as the ability for systems to learn from data in an unsupervised manner and with minimal guidance, while artificial intelligence represents systems that can improve themselves through more abstract reasoning not necessarily dependent on data. It's tougher to tease apart the forecasts for the two, as they are often lumped together, however one leading report this year, citing the expectation that use of machine learning will become common to support activities in the workplace (a sentiment I very much concur with), expects 4. Contextual computing. Earth Girls Are Easy Full Movie on this page.

The increasing desire to augment productivity and collaboration by supplying information on- demand, usually just as it's needed and before it's explicitly asked for, has already become big business. Established industry players such as Apple, Intel, and Nokia are working on and/or offering context- aware APIs already, while a raft of startups is competing to make the early market.

Contextual computing is now expected to grow 3. Virtual reality. Still a niche technology despite the support from major industry players such as Samsung with its inexpensive yet high quality Gear VR set and Apple with its new ARKit, virtual reality is poised to grow dramatically for a growing percent of end- user experience as the technology becomes more refined, and especially, less bulky and intrusive. While just a small half billion dollar market today, virtual reality is expected to grow at the blistering pace of 1. D and 4. D printing. While evolving in fits and starts, 3.

D printing has already become important to a wide range of industries, from aerospace and energy to electronics and even culinary uses. D printing is remaking the logistics industry as well by moving manufacturing directly to the point of use and making it on- demand. D printing will become a significant industry quite soon, growing by 2. D printing, which are objects whose shapes can be changed over time, is a much smaller industry but as a result is growing quickly at 3.

G wireless. Few mobile technologies are as anticipated as 5. G, the next generation of wireless telecommunications standards and infrastructure, which will bring revolutionary bandwidth increases (potentially up to 1. GB per second in some cases) and enable new high value business scenarios including immersive virtual reality telepresence, 4. K/8. K video streaming, and other very high bandwidth uses. While still not expected to commercialize until at least 2. G is widely expected to impact numerous industries and markets, despite real challenges in beaming millimeter waves significant distances, fueling futuristic experimental 5.

G projects like Google Skybender. G spending is expected to grow by 7.

Real- time stream processing and analytics. Best exemplified by software and cloud services like Apache Spark and Amazon Kinesis, the Internet of Things revolution and rich media in general is fueling the need to process and analyze massive amounts of data without any delay - - both event metadata and the data itself - - that flows in from services and devices on the edge of the network. While not quite the white hot item it was last year, stream processing remains a critical technology for data- driven companies. Stream processing and analytics is expected to grow 3. Low code tools and platforms. While developing sophisticated software will remain the purview of professional developers for the foreseeable future, it's getting easier all the time for anyone to code basic applications using low code development solutions. Services like Mendix, Appian, and Outsystems - - although there are now dozens of credible entrants including the new Microsoft Power.

Apps - - now make it easy to build real apps with minimal skill. This can greatly offload IT in simpler business situations and can even make it possible for digital transformation to occur in a far more decentralized manner than in the past, all by giving local business experts the self- service tools they need to meet their more basic needs. Recent data on market performance of low code is fairly limited, but the industry is generally expected to exceed a respectable $1. Wearable IT. The market for enterprise wearables remains quite small and is still limited to niche applications like corporate wellness, hands- free scenarios, situational customer/workforce experiences (typically location- based or rapid notifications), and just- in- time decision making. Yet this belies the anticipated growth of the category, which is expected to expand by over 7.