tomorrow is here

To stay competitive it is important for companies to understand how the top strategic technology trends may impact their business model.  In a world where increased security threats evolve alongside the emergence of an intelligent digital mesh brings with it the potential for a sweeping range of successes and disasters. Here are eight Gartner-identified trends that caught our eye.


The continuing evolution of a sophisticated “hacker industry” increases the threat level against corporate assets. The traditional strategy of perimeter defense and rule-based security must be augmented by technology that detects and responds to patterns of behavior and anomalies. Security-aware applications and behavior analytics can trigger alarms and automatic responses to attacks. In addition, instead of being the final effort prior to new system or application release security should now be integrated into the development process.


The most easily understood application of digital twin technology would be in manufacturing where a manufacturing plant and its assets are replicated and tracked as a digital system. In addition to physical properties and meta data the digital twin would also use analytics to predict events such as equipment failure. The digital twin could plan preventative maintenance, run existing manufacturing processes and predict the cost-effectiveness of new processes.


Artificial Intelligence (AI) is the ability of technological systems to understand, learn, predict, adapt and potentially operate with little or no human input. Machine Learning utilizes AI to improve its own performance. Machine learning can also take advantage of available databases improving its speed of adaptation and reducing error rates. AI and advanced learning machines give rise to robots, self-driving autos and other smart consumers electronics.


VI and AR give rise to new ways humans interact with computing systems and with each other via a variety of devices. The massive success of Nintendo’s Pokemon Go is a indicator of how augmented reality will become an increasingly popular use of smartphone technology. AR can blend the use of virtual and real-world reality for business use. For example, mapping see-through surfaces that reveal physical virtual structures beneath. Virtual reality, which also has its roots in gaming and entertainment has many business applications such as training for real world scenarios.


A distributed ledger is a database that is consensually shared and synchronized across network spread across multiple sites, institutions or geographies. It allows transactions to have public “witnesses,” thereby making a cyberattack more difficult. The participant at each node of the network can access the recordings shared across that network and can own an identical copy of it. Further, any changes or additions made to the ledger are reflected and copied to all participants in a matter of seconds or minutes. Underlying the distributed ledger technology is the blockchain, which is the technology that underlies bitcoin.


Like Apple’s Siri and Google’s Google Now conversational UI will grow in complexity and functionality. Besides voice recognition and response the device mesh will evolve ‘conversation systems’ beyond voice-enabled solutions to include other senses like touch, taste and smell. Interactions will move from voice-enabled to rich conversations with systems and vice versa.


Today’s problem: When you have a ton of different apps and networks all firing information at each other, how do you make it look like one seamless, coherent experience for the user. According to Gartner*, the mesh app and service architecture (MASA) is a multichannel solution architecture that supports multiple users in multiple roles using multiple devices and communicating over multiple networks to access application functions. This would allow effective and efficient on the move work, across a range of networks, sensors, and technologies.



Intelligent things are physical things that are designed to exploit applied AI and machine learning like robots, drones and autonomous vehicles. AI and machine learning will increasingly be embedded into everyday things, Even appliances, speakers and hospital equipment will be increasingly embedded with AI and machine learning for example today’s digital stethoscope can record and store heartbeat and respiratory sounds. Gartner forsees a shift from stand-alone intelligent things to a collaborative intelligent things model. For example, our military is studying the use of drone swarms that interact intelligently with each other and their surroundings to attack or defend military targets.