The 10 main strategic technological trends of Gartner

Gartner predicts that AI-driven devices, processes, products and services will converge to form "the intelligent digital mesh." This convergence will result in the interrelation of people, devices and services to support more fluid, secure and digital business operations, reinforced by a “continuous innovation process”.

In 2017, Gartner identified AI and its impact on the smart digital mesh in 2017  as key trends to observe, suggesting that these trends will take several years to realize its full effect.

  1. Intelligent:  AI will penetrate virtually all existing technologies and create completely new technology categories.
  2. Digital:  Digital combines the digital and physical worlds to create hybrid and enveloping experiences.
  3. Mesh:  Mesh is the connective tissue, which exploits the connections between expanding sets of people, companies, devices, content and services.
  1. Intelligent.
    1. Autonomous things. Autonomous things use AI technology to drive new hardware and software capabilities: these things work with "varying degrees of capacity, coordination and intelligence," Gartner wrote in a  brief about his top 10 technology trends  , also stressing that these things are used. best. for "narrowly defined purposes" instead of generalized uses.

      There are five categories of autonomous things:

      • Robotics
      • Vehicles
      • Drones
      • accessories
      • Conversational Agents
    2. Increased analytics Analytics has become an integral part of business processes, but the increasing volume and complexity of data is a burden for data scientists that is impossible to maintain. The increased analytics It helps ease this burden by providing data scientists with automated algorithms to explore more hypotheses and better manage their data analysis. 
      Gartner predicts that by 2020, more than 40% of data science tasks will be automated, which will result in increased productivity and wider use by  citizen data scientists  : lay people who have the tools To analyze data.
      It is not about replacing people but about increasing them through AI. Using natural language interfaces, vendors can ask if they are on track to reach the quota. The system can deliver data, as well as contribute ideas.
    3. AI driven development  . AI-enabled development processes facilitate the incorporation of artificial intelligence into applications through tools, technologies and best practices.
  2. Digital.
    1. Digital twin A  digital  twin  is a replica of physical assets, processes, people, places, systems and devices that can be used for various purposes. Digital twins allow proactive monitoring of systems before problems develop and provide new development opportunities through simulation. While digital twins are not new, AI elevates simulations to identify opportunities. In addition, the closer link between virtual and real allows for greater interaction with hypothetical scenarios.
    2. Enhanced Edge Perimeter computing is an architecture to complement cloud computing and reduce data latency by  bringing capabilities to users, devices and data that need these resources  . Much of the focus of the perimeter computation is the result of the need for  the  systems  of Internet of Things  (IoT) provide distributed capabilities. Perimeter computing connected to the IoT consists of  empowering cutting-edge AI devices  with better chip technology, greater computing, more storage and other resources, and communicating with  architectures such as 5G  , which will increase next year.
    3. Immersive experiences. Immersive experiences encompass augmented, mixed virtual reality environments, as well as conversation interfaces and voice-activated smart devices. Gartner predicts that, by 2022, 70% of companies will experiment  with immersive technologies for consumer and business use, and 25% will have implemented these production environments.
  3. Mesh.
    1. Blockchain This shared and distributed book allows the secure and digital exchange of value. Using a trust model, transactions can be made, tracked and validated without a centralized party to negotiate the exchange. Blockchain technologies could reduce costs, improve transparency and allow those who do not have access to centralized resources to get involved in transactions, all while maintaining the security of the parties involved. Today, however, blockchain is still incipient and has not been tested.
    2. Smart spaces Smart spaces bring together technologies and trends. Human beings and technology-enabled systems interact in increasingly open, connected, coordinated and intelligent ecosystems. These smart spaces, designed to be  innovative, more environmentally friendly and livable  in the case of smart cities and more  productive and collaborative in the case of  smart workspaces , are designed to be  efficient, more environmentally friendly environment  and with IoT  .
    3. Privacy and ethics. Numerous violations of consumer data have raised awareness about the risks to individuals and businesses that are not good data managers. 
      Companies that are not responsible for consumer data risk the reaction. 
      To forge continuous success in customer relationships and to protect the company's brand (and data), companies must safeguard customer data and keep abreast of regulations. Otherwise, they risk customer rotation or financial and legal repercussions.
    4. Quantum computing This architecture involves a type of non-traditional computing that represents information as elements denoted as quantum bits, or "qubits." The result of quantum computing is  faster and more complex computational possibilities  . A classic computer, for example, would read all books linearly, very fast. Quantum computing allows a computer to read all books simultaneously. Quantum computing and AI need intensive computational resources to perform their tasks.

AI, displacement and interruption.

While these trends are gaining strength, not all of them are prepared for the company or are widely used. Many will continue to evolve in the coming years. And it is essential to keep in mind that even for the underlying technology in question, artificial intelligence, most of the artificial intelligence business projects are still in the making.

According to a  survey conducted by Gartner in 2018  , 37% of organizations still need to define their artificial intelligence strategies, while 35% have difficulties in identifying appropriate use cases for AI in their environments. Another  Gartner Cart survey found that only 4% of respondents had deployed AI. However, the survey also found that one fifth of CIOs are already piloting or planning to pilot AI in the short term.

Figure 2 on the global perceptions of AI Source: Global Attitudes Survey of Spring 2018, Pew Research Center

The slow pace may be due to organizations lacking internal experience to guide more widespread AI projects. In  the 2018 Gartner CIO survey  , 47% of CIOs reported that they needed new skills for artificial intelligence projects.

There is also great anxiety about the massive displacement of AI in human works. A  Pew Research Center study in September 2018  indicated that large majorities in 10 countries surveyed said that automation "definitely" or "probably" would lead to significant job losses. The lowest percentage was recorded in the United States, where 65% of people held that opinion, according to the report. (See Figure 2 on global perceptions of AI.)

Companies see the emergence of artificial intelligence as a cost reduction tool, but a better strategy, Gartner advises in »  Lessons from the pioneers of artificial intelligence  «, is to consider AI as a way to create applications that help and improve human efforts AI promises benefits  that go well beyond automation, and organizations that adopt this perspective are more likely to find workers willing to embrace AI.

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