Now is the time for enterprises to have internal discussions using clear language and, at least, monitoring developments. However, in the long term, Gartner believes this technology will lead to a reformation of whole industries. Bitcoin is historically volatile, and enterprises are struggling with a lack of proven use cases. But realistically, most initiatives are still in the alpha or beta stage. With the price of Bitcoin over US$4,000, it might seem like blockchain is something every enterprise is doing (or should be). Besides AR, companies should look to digital workspaces, connected homes, virtual reality and 4D printing in this realm. As technology evolves to be more adaptive, contextual and fluid, it will become more human-centric. When it comes to transparently immersive experiences, technology is introducing transparency between people, businesses and things. Enterprises should create an AR strategy in the business, with specific goals and tasks for trials and benchmarks. For example, instead of relying on printed paper or separate screens, AR could overlay a maintenance schematic on a broken lamp post. The business world needs better technology and better use cases but many enterprises are exploring pilot projects. While the popularity of Pokemon Go brought augmented reality (AR) to the forefront of people’s minds, enterprises are still struggling with useful applications. Organizations with these technologies will harness the data to solve currently nonexistent challenges. With data management a challenge simply given the amount of data, machine learning will allow for useful data extractions.ĪI technologies will be the most disruptive class of technologies for the next decade due to the amount of data and the evolution of neural networks.

Machine learning, one of the hottest concepts in technology, has the potential to change industries ranging from individual supply chains to drug research. However, the media hype and inflated expectations for autonomous vehicles have led to an increase in development for AI and machine-learning algorithms, which in turn evolve the technology further.

Gartner hype cycle 2017