If you've spent any time reading the round-up of 2018 technology predictions, you've likely seen artificial intelligence (AI) highlighted in nearly every one. The reason for this is that AI has a seemingly limitless number of applications and use cases for the enterprise. In fact, according to Gartner, over 85% of customer interactions will be managed without a human by 2020. While AI is definitely a hot topic to watch in 2018, there are also a few other tech areas that will have equally exciting momentum and just as big an impact on the enterprise in the year ahead. Following we'll take a deeper look at what some of those will be and how they might shape 2018.

With February finally here, it can't be ignored that Mobile World Congress (#MWC18) is just around the corner, taking place in Barcelona from 26 Feb to 1 Mar. The rate of attendees has been climbing up steadily year-on-year attracting over 108,000 attendees last year of which 74% is senior-level decision makers. Apart from the annual product launches by players like Huawei and Samsung, there's always a lot more going on and this year promises to be no different... AI has been a constant talking point in Tech for some time now and a number of interesting topics will be discussed by industry leaders at the event this year. AI technology has advanced rapidly raising questions about the ethical issues and effect on society at large. Social profiling, privacy and security are some of the most common concerns.

Amazon Alexa users can now send SMS messages through the voice assistant, the company announced via TechCrunch. The Amazon feature comes as Apple takes pre-orders for its own smart speaker: the HomePod. The Apple device will allow users to send iMessages and SMS text messages by using Siri. As of Tuesday, U.S. Alexa users can send text messages to their contacts in the Alexa app by simply asking the voice assistant. Alexa already has a voice calling and its own messaging system.

So much for needing your phone to send text messages. Thanks to a new software update, you can now use Alexa to deliver SMS text messages to any phone. There are some caveats, however. It only works for Alexa users in the US with an Android device that also have the Alexa app installed on their phone. You also can't use the feature to text 911 or participate in group text messages.

Axios recently reported that it had discovered a document that revealed something very interesting: The Trump administration was considering a government-run 5G network. According to the memo, this was in order to fight China's upcoming dominance in the wireless 5G space, and would ensure a safe network for self-driving cars, AI, VR and other cutting-edge technologies. This kind of state-run network is completely antithetical to the administration's public stance on deregulation and privatization. It even prompted FCC Chairman Ajit Pai to come down strongly in opposition. It turns out, however, that the document was outdated, and the Trump administration strongly denies it ever seriously considered such a proposal.

Artificial Intelligence (AI) is being groomed, says Rethink Technology Research to partner with self-optimising networks (SON) to create cellular networks that know the user, perform brilliantly and defy complexity. But 50% of network providers worry they will not be able to attract sufficient AI skills. While everyone today is aware of the race to build a self-driving car, the race to build a self-driving cellular network is far less of a public property, but nonetheless, it is a race that is critical to the survival of existing mobile network operators (MNOs). The rise in self-optimising networks, along with a huge increase in the total number of cells, will lead to a radical uptake of virtualised Software Defined Networks. This will make it possible to dial network resources up and down on-demand, but only if MNOs can cope with another level of network complexity.

Recent Galaxy S9 leaks, many coming from the ever-reliable Evan Blass, tell us pretty much all there is to know about Samsung's upcoming flagship: It'll have a better chip, a better camera, and a repositioned fingerprint sensor. The S9 doesn't look groundbreaking, but it should be a nice upgrade for people still rocking an S7. But this being the smartphone wars, Samsung can't just let the iPhone X go unnoticed. While it's almost certain the S9 won't have a 3D sensing camera like Apple's flagship phone, a new feature hidden inside Samsung's Oreo beta called Intelligent Scan shines light on a new biometric that many will compare to Face ID. Intelligent Scan reportedly combines iris and face scanning to "to improve accuracy and security even in low or very bright light," according to messages hidden in the Oreo beta.

Samsung has hinted that the Galaxy S9 might include more advanced face recognition, but we're now getting clues as to what's involved. SamCentral's sleuthing in the settings APK for the Galaxy Note 8's Oreo beta has discovered a hidden Intelligent Scan feature that uses both camera-based face detection and the iris scanner in tandem for "better accuracy and security" and improved results in "low or very bright" lighting. Given that the iris scanning on the S8 and Note 8 can be finnicky, this could deliver a much more consistent experience when you're unlocking your phone or accessing secure info. Just how it works isn't immediately apparent. A video included with the feature suggests that both the iris scanner and camera are active at the same time regardless of the conditions, but it's not certain whether this means combining their data or using one as a backup for the other.

Management teams often assume they can leapfrog best practices for basic data analytics by going directly to adopting artificial intelligence and other advanced technologies. But companies that rush into sophisticated artificial intelligence before reaching a critical mass of automated processes and structured analytics can end up paralyzed. They can become saddled with expensive start-up partnerships, impenetrable black-box systems, cumbersome cloud computational clusters, and open-source toolkits without programmers to write code for them. By contrast, companies with strong basic analytics -- such as sales data and market trends -- make breakthroughs in complex and critical areas after layering in artificial intelligence. For example, one telecommunications company we worked with can now predict with 75 times more accuracy whether its customers are about to bolt using machine learning.

Startup Gyrfalcon is moving fast with a chip for inferencing on deep neural networks, but it faces an increasingly crowded market in AI silicon. A year after it got its first funding, the company is showing a working chip and claiming design wins in smartphones, security cameras and industrial automation equipment. Data centers typically train deep neural networks and run inference tasks on them using banks of servers. Increasingly, client and embedded systems from cars to handsets are adopting accelerators to speed the inferencing jobs. Apple, Google and Huawei are already shipping smartphones with inferencing blocks in their custom SoCs.